CN111812744B

CN111812744B - Formation compressibility determination method, device and computer storage medium

Info

Publication number: CN111812744B
Application number: CN201910288211.2A
Authority: CN
Inventors: 李忠诚; 王志文; 宋鹏; 孙文铁; 肖丽佳; 周萍; 张慧宇; 周俊廷; 李金池
Original assignee: Petrochina Co Ltd
Current assignee: Petrochina Co Ltd
Priority date: 2019-04-11
Filing date: 2019-04-11
Publication date: 2023-10-31
Anticipated expiration: 2039-04-11
Also published as: CN111812744A

Abstract

This application discloses a method, device and computer storage medium for determining formation compressibility, which belongs to the technical field of oil and gas field development. In this application, based on the full wave train logging data of each well in N wells, the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer is determined, as well as the relationship between the shear wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir. The relationship between the longitudinal wave travel time, based on the relationship between the shear wave travel time and the longitudinal wave travel time of the stable marker layer, determine the brittleness index of the non-reservoir in the first well, based on the shear wave travel time difference and the longitudinal wave travel time difference of each type of reservoir in at least one type of reservoir relationship between each other to determine the brittleness index of each type of reservoir in at least one type of reservoir in the first well. This makes the determined brittleness index of the non-reservoir layer and the reservoir brittleness index more accurate, improves the accuracy of determining the brittleness index of the formation in the first well, and accordingly improves the accuracy of determining the compressibility of the formation in the first well.

Description

Formation compressibility determination method and device and computer storage medium

Technical Field

The application relates to the technical field of oil and gas field development, in particular to a stratum compressibility determining method and device and a computer storage medium.

Background

Currently, in the production of petroleum, it is often necessary to fracture the formation. And prior to fracturing the formation, it is often necessary to determine the compressibility of the formation. The compressibility of the formation depends on the brittleness of the rock in the formation. Brittleness of rock in a formation refers to how easily the rock in the formation breaks. The brittleness of rock in a formation is often expressed by a formation brittleness index. Wherein formation compressibility, i.e., formation brittleness index, is determined.

In the related art, full wave train logging data of well a in a well in which full wave train logging has been performed in a study area is generally selected when determining a brittleness index of a formation. And determining the transverse wave time difference of the well A in all the formations and the longitudinal wave time difference of the well A in all the formations according to the full-wave train logging data of the well A. And selecting a stable mark layer from the well A, and determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer according to the transverse wave time difference of the well A in all the strata and the longitudinal wave time difference of the well A in all the strata. The stability mark layer refers to that all formations in the well in the research area contain one type of formation, such as a mudstone layer.

And acquiring acoustic logging data of the well B except for full-wave train logging in the research area, wherein the acoustic logging data comprise longitudinal wave time differences corresponding to different depths in the well B. And determining the transverse wave time difference corresponding to the different depths of the well B according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the longitudinal wave time difference corresponding to the different depths of the well B. And determining the stratum brittleness index of the well B according to the longitudinal wave time differences corresponding to different depths in the well B and the transverse wave time differences corresponding to different depths in the well B. Wherein all formations include reservoirs and non-reservoirs, and mudstone layers belong to the non-reservoirs. The shear and longitudinal wave time differences are used to represent the velocity of the acoustic wave traveling through the rock in the formation. Because the densities of different rocks in the stratum are different, the propagation speed of sound waves in the stratum is different, and the brittleness of the rocks is influenced by the density of the rocks, so that the stratum brittleness index can be determined according to the longitudinal wave time difference and the transverse wave time difference.

Since the formation brittleness index of the well B is determined according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer in the related art. While the lithology of different types of formations in the formation may be different, the formation brittleness index of well B, as determined by the relationship between the shear and longitudinal wave time differences of the stable marker layer, may not be suitable for all types of formations in well B. That is, the accuracy of the formation brittleness index determined in the related art is low, so that the accuracy of the finally determined formation compressibility is also low.

Content of the application

The embodiment of the application provides a stratum compressibility determining method, a stratum compressibility determining device and a computer storage medium, which can improve the accuracy of determining stratum compressibility. The technical scheme is as follows:

in a first aspect, there is provided a method of formation compressibility determination, the method comprising:

determining a relation between a transverse wave time difference and a longitudinal wave time difference of a stable marker layer and a relation between a transverse wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to full-wave train logging data of each of N wells for full-wave train logging in a research area, wherein the full-wave train logging data are used for representing propagation time differences of sound waves at different depths of a stratum, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir;

Determining the brittleness index of a non-reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well, wherein the first well is any well outside a well for performing full wave train logging in the research area;

and determining the brittleness index of each type of reservoir in the at least one type of reservoir according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data is used for indicating the longitudinal wave time difference corresponding to the acoustic wave at different depths of the stratum.

Optionally, the determining the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer according to the full wave train logging data of each of the N wells performing full wave train logging in the research area includes:

determining a longitudinal wave time difference of the stable marker layer in each of the N wells and a transverse wave time difference of the stable marker layer in each of the N wells according to the full-wave train logging data of each of the N wells;

and determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each of the N wells and the transverse wave time difference of the stable marker layer in each well.

Optionally, the determining a relationship between a shear wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to the full wave train logging data of each of N wells performing full wave train logging in the research area includes:

for a first type of reservoir in the at least one type of reservoir, determining a longitudinal wave time difference of the first type of reservoir in each of the N wells and a transverse wave time difference of the first type of reservoir in each of the N wells according to full-wave column logging data of each of the N wells, wherein the first type of reservoir is any type of reservoir in the at least one type of reservoir;

and determining the relation between the shear wave time difference and the longitudinal wave time difference of the first-type reservoir according to the longitudinal wave time difference of the first-type reservoir in each well of the N wells and the shear wave time difference of the first-type reservoir in each well.

Optionally, the determining the brittleness index of the non-reservoir in the first well according to the relation between the shear wave time difference and the longitudinal wave time difference of the stable mark layer and the sonic logging data of the first well includes:

acquiring density log data of the first well, the density log data being used to indicate rock densities at different depths of a formation;

Determining a plurality of dynamic Young modulus and a plurality of dynamic Poisson ratios of the first well, wherein the dynamic Young modulus is Young modulus obtained through a dynamic method and used for indicating supporting capacity after rock fracture, the dynamic Poisson ratio is Poisson ratio obtained through a dynamic method and used for indicating the rock fracture capacity under the stress effect, the dynamic Young modulus and the dynamic Poisson ratio are in one-to-one correspondence, and each dynamic Young modulus and corresponding dynamic Poisson ratio correspond to one stratum depth;

determining a static Young's modulus according to each dynamic Young's modulus of the plurality of dynamic Young's moduli to obtain a plurality of static Young's moduli;

determining a static poisson ratio according to each dynamic poisson ratio in the dynamic poisson ratios to obtain a plurality of static poisson ratios, wherein the static Young modulus refers to the Young modulus obtained through a static method, the static poisson ratio refers to the poisson ratio obtained through the static method, the static Young modulus corresponds to the static poisson ratios one by one, and each static Young modulus corresponds to one stratum depth;

Based on each static young's modulus and the corresponding static poisson's ratio, a formation brittleness index at a corresponding formation depth is determined.

Optionally, the determining the brittleness index of each type of the at least one type of reservoir according to the relation between the shear wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the sonic logging data of the first well includes:

acquiring density logging data of the first well;

for a first reservoir in the at least one reservoir, determining a plurality of dynamic young modulus and a plurality of dynamic poisson ratios of the first reservoir according to the relation between the transverse wave time difference and the longitudinal wave time difference of the first reservoir, the acoustic logging data of the first well and the density logging data of the first well, wherein the dynamic young modulus and the dynamic poisson ratios are in one-to-one correspondence, and each dynamic young modulus and the corresponding dynamic poisson ratio are in one-to-one correspondence with one stratum depth;

determining a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios to obtain a plurality of static poisson ratios, wherein the plurality of static Young modulus corresponds to the plurality of static poisson ratios one by one, and each static Young modulus corresponds to a stratum depth;

In a second aspect, there is provided a formation compressibility determining apparatus, the apparatus comprising:

the system comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of a stable mark layer and the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to the full wave train logging data of each of N wells for carrying out full wave train logging in a research area, the full wave train logging data are used for representing the propagation time differences of sound waves at different depths of a stratum, N is a positive integer greater than or equal to 1, and the stable mark layer is a non-reservoir;

the second determining module is used for determining the brittleness index of the non-reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well, wherein the first well is any well outside the well for performing full wave train logging in the research area;

and the third determining module is used for determining the brittleness index of each type of reservoir in the at least one type of reservoir according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data are used for indicating the longitudinal wave time differences corresponding to different depths.

Optionally, the first determining module includes:

a first determining unit, configured to determine a longitudinal wave time difference of the stable marker layer in each of the N wells and a transverse wave time difference of the stable marker layer in each of the N wells according to full-wave-column logging data of each of the N wells;

and the second determining unit is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each of the N wells and the transverse wave time difference of the stable marker layer in each well.

Optionally, the first determining module further includes:

a third determining unit, configured to determine, for a first type of reservoir in the at least one type of reservoir, a longitudinal wave time difference of the first type of reservoir in each of the N wells and a transverse wave time difference of the first type of reservoir in each of the N wells according to full-wave column logging data of each of the N wells, where the first type of reservoir is any type of reservoir in the at least one type of reservoir;

and the fourth determining unit is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of the first-type reservoir according to the longitudinal wave time difference of the first-type reservoir in each of the N wells and the transverse wave time difference of the first-type reservoir in each well.

Optionally, the second determining module includes:

a first acquisition unit for acquiring density log data of the first well, the density log data being indicative of rock densities at different depths in a formation;

a fifth determining unit, configured to determine, according to a relationship between a shear wave time difference and a longitudinal wave time difference of the stable marker layer, acoustic logging data of the first well, and density logging data of the first well, a plurality of dynamic young modulus of a non-reservoir in the first well and a plurality of dynamic poisson ratios, where the dynamic young modulus is young modulus obtained by a dynamic method and is used to indicate a supporting capability after a rock fracture, the dynamic poisson ratio is poisson ratio obtained by a dynamic method and is used to indicate a fracture capability of the rock under a stress, the dynamic young modulus and the dynamic poisson ratio are in one-to-one correspondence, and each dynamic young modulus and the corresponding dynamic poisson ratio are corresponding to a stratum depth;

a sixth determining unit configured to determine a static young's modulus according to each of the plurality of dynamic young's moduli, to obtain a plurality of static young's moduli;

A seventh determining unit, configured to determine a static poisson ratio according to each of the plurality of dynamic poisson ratios, to obtain a plurality of static poisson ratios, where the static young modulus refers to a young modulus obtained by a static method, the static poisson ratio refers to a poisson ratio obtained by a static method, the plurality of static young modulus and the plurality of static poisson ratios are in one-to-one correspondence, and each static young modulus and the corresponding static poisson ratio correspond to a stratum depth;

and an eighth determining unit, configured to determine a formation brittleness index at a corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio.

Optionally, the third determining module includes:

a second acquisition unit for acquiring density logging data of the first well;

a ninth determining unit, configured to determine, for a first type of reservoir in the at least one type of reservoir, a plurality of dynamic young modulus and a plurality of dynamic poisson ratios of the first type of reservoir according to a relationship between a shear wave time difference and a longitudinal wave time difference of the first type of reservoir, sonic logging data of the first well, and density logging data of the first well, where each dynamic young modulus and a corresponding dynamic poisson ratio correspond to one formation depth;

A tenth determination unit configured to determine a static young's modulus according to each of the plurality of dynamic young's moduli, to obtain a plurality of static young's moduli;

an eleventh determining unit, configured to determine a static poisson ratio according to each of the plurality of dynamic poisson ratios, to obtain a plurality of static poisson ratios, where the plurality of static young modulus corresponds to the plurality of static poisson ratios one to one, and each static young modulus corresponds to a formation depth with a corresponding static poisson ratio;

and a twelfth determining unit for determining the stratum brittleness index at the corresponding stratum depth according to each static Young's modulus and the corresponding static Poisson ratio.

In a third aspect, a formation compressibility determination apparatus, the apparatus comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to perform the steps of any of the methods of the first aspect above.

In a fourth aspect, a computer readable storage medium has stored thereon instructions which, when executed by a processor, implement the steps of any of the methods of the first aspect above.

In a fifth aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the steps of any of the methods described in the first aspect above.

The technical scheme provided by the embodiment of the application has the beneficial effects that:

in the application, the stratum of each of N wells for performing full wave train logging in a research area is divided into a reservoir and a non-reservoir, and the relation between the transverse wave time difference and the longitudinal wave time difference of a stable mark layer and the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir are respectively determined according to the full wave train logging data of each of the N wells. And determining the brittleness index of the non-reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the sonic logging data of the first well. And determining the brittleness index of each type of reservoir in at least one type of reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the acoustic logging data of the first well. That is, in the present application, when determining the brittleness index of the formation in the first well, the brittleness index of the non-reservoir is determined according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer, and the brittleness index of the reservoir is determined according to the relationship between the shear wave time difference and the longitudinal wave time difference of the reservoir. The determined brittleness index of the non-reservoir and the reservoir are more accurate, the accuracy of determining the brittleness index of the stratum in the first well is improved, and correspondingly, the accuracy of determining the compressibility of the stratum in the first well is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for determining formation compressibility provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of performing data fitting between a longitudinal wave time difference of a stable marker layer and a transverse wave time difference of the stable marker layer according to an embodiment of the present application;

FIG. 3 is a schematic diagram of data fitting between a longitudinal wave time difference of an air layer and a transverse wave time difference of the air layer according to an embodiment of the present application;

FIG. 4 is a schematic diagram of performing data fitting on a longitudinal wave time difference of a dry layer and a transverse wave time difference of the dry layer according to an embodiment of the present application;

FIG. 5 is a schematic diagram of data fitting of dynamic Young's modulus of a stable marker layer with laboratory measured static Young's modulus provided by an embodiment of the present application;

FIG. 6 is a schematic diagram of data fitting of dynamic Poisson's ratio of a stable marker layer to laboratory-determined static Poisson's ratio, provided by an embodiment of the present application;

FIG. 7 is a schematic illustration of a log and various formations provided by an embodiment of the present application;

FIG. 8 is a schematic structural view of a device for determining formation compressibility according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of a terminal according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.

Before explaining the formation compressibility determining method provided by the application, an application scenario of the formation compressibility determining method provided by the application is briefly introduced. The formation may generally be divided into a reservoir and a non-reservoir according to the porosity of the formation. In general, a formation may be divided into reservoirs when its porosity is greater than a numerical threshold, and may be divided into non-reservoirs when its porosity is less than or equal to the numerical threshold, where the porosity of a formation refers to the ratio of the volume of pores in the rock in the formation to the total volume of rock. Meanwhile, a reservoir may be divided into oil reservoirs or gas reservoirs according to substances stored in the reservoir. In the gas storage layer, the gas storage layer can be divided into a gas layer, a gas difference layer and a dry layer according to different gas saturation of the gas storage layer. The gas layer is that the gas saturation of the gas storage layer is larger than the saturation threshold, the gas difference layer is that the gas saturation of the gas storage layer is smaller than the saturation threshold, and the dry layer is that the gas saturation of the gas storage layer is 0. The gas saturation refers to the ratio of the volume of gas in the gas storage layer to the volume of pores in the gas storage layer.

Prior to fracturing a well in a zone of interest, the compressibility of the reservoir in the well needs to be determined, and sonic logging data is typically used in determining the compressibility of the reservoir in the well, i.e., determining the brittleness index of the reservoir in the well. Since sonic logging data is used to indicate the time difference of longitudinal waves corresponding to different depths in the well, when determining the brittleness index of the reservoir using sonic logging data, the determined brittleness index of the reservoir is also indicative of the brittleness index corresponding to different depths in the well.

Fig. 1 is a flowchart of a method for determining formation compressibility according to an embodiment of the present application, as shown in fig. 1, where the method includes the following steps:

step 101: and determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer and the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir according to the full wave train logging data of each of N wells for full wave train logging in a research area, wherein the full wave train logging data are used for representing the propagation time differences of sound waves at different depths of the stratum, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir.

Since the stability marker layer is a non-reservoir layer, the lithology of the non-reservoir layer is generally different from the lithology of the reservoir layer, therefore, when determining the brittleness index of the stratum, the stratum needs to be divided into a reservoir layer and a non-reservoir layer, and the brittleness index of the reservoir layer and the brittleness index of the non-reservoir layer are respectively determined. And the brittleness index of the reservoir is related to the relationship between the shear wave and the longitudinal wave in the acoustic transit time of the reservoir, and the brittleness index of the non-reservoir is related to the relationship between the shear wave and the longitudinal wave in the acoustic transit time of the non-reservoir, thereby respectively determining the relationship between the shear wave transit time and the longitudinal wave transit time in the acoustic transit time of the reservoir and the relationship between the shear wave transit time and the longitudinal wave transit time in the acoustic transit time of the stable mark layer.

(1) And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer.

In one possible implementation manner, according to the full wave train logging data of each of N wells performing full wave train logging in the research area, the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer may be specifically determined as follows: and determining the longitudinal wave time difference of the stable mark layer in each of the N wells and the transverse wave time difference of the stable mark layer in each of the N wells according to the full-wave train logging data of each of the N wells. And determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each of the N wells and the transverse wave time difference of the stable marker layer in each well.

When the full wave train logging is performed on each of the N wells, the obtained full wave train logging data of each well contains the transverse wave time difference of each well in all stratum and the longitudinal wave time difference of each well in all stratum, so that the full wave train logging data of each well can be separated, and the longitudinal wave time difference of the stable marker layer in each well and the transverse wave time difference of the stable marker layer in each well can be separated. The longitudinal wave time differences for each well stability marker layer and the transverse wave time differences for each well stability marker layer may then be determined based on the full wave train log data for each well.

In one possible implementation manner, according to the longitudinal wave time difference of each stable mark layer in each well and the transverse wave time difference of each stable mark layer in each well, the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer may be specifically determined as follows: constructing a first longitudinal wave time difference set from the longitudinal wave time differences of each well stable marker layer, constructing a first transverse wave time difference set from the transverse wave time differences of each well stable marker layer, performing data fitting according to the first longitudinal wave time difference set and the first transverse wave time difference set, and taking the result after the data fitting as the relation between the transverse wave time differences and the longitudinal wave time differences of the stable marker layers. The data fitting may be performed with the longitudinal wave time difference as the abscissa and the transverse wave time difference as the ordinate.

For example, full-wave train logging is performed on 3 wells in the investigation region, resulting in full-wave train logging data for each of the 3 wells. And determining the transverse wave time difference of the stable mark layer in each well and the longitudinal wave time difference of the stable mark layer in each well according to the full-wave-train logging data of each well. And constructing a first transverse wave time difference set by using the transverse wave time differences of the stable mark layers in each well, and constructing a first longitudinal wave time difference set by using the longitudinal wave time differences of the stable mark layers in each well. As shown in fig. 2, with the longitudinal wave time difference as the abscissa and the transverse wave time difference as the ordinate, performing data fitting on all the transverse wave time differences in the first transverse wave time difference set and all the longitudinal wave time differences in the second longitudinal wave time difference set to obtain the relationship between the transverse wave time differences and the longitudinal wave time differences of the stable mark layer as follows:

y＝1.2527x+105.57

In the above expression, y represents a shear wave time difference, and x represents a longitudinal wave time difference. R is R ² Representing the fitting accuracy. Typically, Δt is used for transverse wave time difference _s The difference in longitudinal wave time is expressed as Δt _p The expression, therefore, can also be:

Δt _s ＝1.2527Δt _p +105.57

optionally, in another possible implementation manner, the determining the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of each well stable marker layer and the shear wave time difference of each well stable marker layer may specifically be further: and for any well C in each well, performing data fitting on the transverse wave time difference of the stable marker layer in the well C and the longitudinal wave time difference of the stable marker layer in the well C, and taking the result of the data fitting as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in the well C. For each well other than well C, the relationship between the shear wave time differences and the longitudinal wave time differences of the stable marker layers in the other wells can be determined according to the relationship between the shear wave time differences and the longitudinal wave time differences of the stable marker layers in well C. After determining the relationship between the shear wave and longitudinal wave moveout for each of the well stable marker layers, the relationship between the shear wave and longitudinal wave moveout for each of the well stable marker layers is compared. If the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer in each well is similar, the relationship between the transverse wave time difference and the longitudinal wave time difference of any well in each well is used as the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer. If the relation difference between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in each well is obvious, selecting any fitting result of fitting results which are of the same type and similar in the type from the fitting results of the transverse wave time difference and the longitudinal wave time difference data of the stable mark layer in each well, and taking the fitting result as the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in each well.

The close relationship between the transverse wave time difference and the longitudinal wave time difference means that every two adjacent fitting results in the fitting results are the same type of fitting result. The difference of the relationship between the transverse wave time difference and the longitudinal wave time difference obviously means that the fitting result is of different types, or the difference between coefficients corresponding to the same parameter in a plurality of functions of the same type used for representing the fitting result is larger than a numerical threshold. Wherein, the fitting result of the same type means that the functions after fitting are the functions of the same type. A close fit result means that the difference between the coefficients of the same parameter among the plurality of functions used to represent the fit result is less than the numerical threshold. For example, y=2x+3 and y=2.01x+3 are functions of the same type, and the difference between the coefficients of the parameter x being 2 and 2.01,2 and 2.01, respectively, is 0.01 less than the value threshold value of 0.1, then y=2x+3 and y=2.01x+3 are close fitting results.

For example, 3 wells performing full wave train logging in the investigation region are well X, well Y and well Z, respectively, and the transverse wave time difference of the stable marker layer and the longitudinal wave time difference of the stable marker layer in well X, the transverse wave time difference of the stable marker layer and the longitudinal wave time difference of the stable marker layer in well Y and the transverse wave time difference of the stable marker layer and the longitudinal wave time difference of the stable marker layer in well Z are determined based on the full wave train logging data of well X, the full wave train logging data of well Y and the full wave train logging data of well Z, respectively. Determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well X as Y according to the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well X and the stable mark layer in the well Y ₁ ＝a ₁ x+b ₁ The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well Y is Y ₂ ＝a ₂ x+b ₂ The relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer in the well Z is y ₃ ＝a ₃ x+b ₃ 。

Since the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer in the well X, the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer in the well Y and the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer in the well Z are all one-time functions, the comparison a ₁ 、a ₂ And a ₃ ，b ₁ 、b ₂ And b ₃ . If a is ₁ 、a ₂ And a ₃ The difference between each other is smaller than a first preset threshold value, and b ₁ 、b ₂ And b ₃ The difference between the two values is smaller than a second preset threshold value, then y is calculated ₁ ＝a ₁ x+b ₁ 、y ₂ ＝a ₂ x+b ₂ And y ₃ ＝a ₃ x+b ₃ Any one of the above is used as a relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer. If a is ₁ 、a ₂ And a ₃ The difference between each other being greater than a first preset threshold, b ₁ 、b ₂ And b ₃ The difference between the two is larger than a second preset threshold value, then a ₁ 、a ₂ And a ₃ The average of these three values is taken as the coefficient of the parameter x, b ₁ 、b ₂ And b ₃ The average of these three values serves as a constant in the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer.

If the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer in the well X is y ₁ ＝a ₁ x ² +b ₁ The relationship between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer in the well Y is Y ₂ ＝a ₂ x+b ₂ The relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer in the well Z is y ₃ ＝a ₃ x+b ₃ Comparison a ₂ And a ₃ ，b ₂ And b ₃ . If a is ₂ And a ₃ The difference between them is smaller than a first preset threshold value, b ₂ And b ₃ The difference value between the two is smaller than a second preset threshold value, and y is calculated as follows ₂ ＝a ₂ x+b ₂ And y ₃ ＝a ₃ x+b ₃ Any one of the above is used as a relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer. If a is ₂ And a ₃ The difference between them is greater than a first preset threshold, b ₂ And b ₃ The difference value between the two is larger than a second preset threshold value, and then a is carried out ₂ And a ₃ The average of these two values is taken as the coefficient of the parameter x, b ₂ And b ₃ The average of these two values serves as a constant in the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer.

(2) A relationship between the shear wave time difference and the longitudinal wave time difference of the reservoir is determined.

In one possible implementation manner, according to the full wave train logging data of each of N wells performing full wave train logging in the research area, the determining a relationship between a transverse wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir may specifically be: for a first type of reservoir in the at least one type of reservoir, determining a longitudinal wave time difference for the first type of reservoir in each of the N wells and a transverse wave time difference for the first type of reservoir in each of the N wells based on the full wave train log data for each of the N wells. And determining the relation between the shear wave time difference and the longitudinal wave time difference of the first-type reservoir according to the longitudinal wave time difference of the first-type reservoir in each of the N wells and the shear wave time difference of the first-type reservoir in each well. Wherein the first type of reservoir is any one of at least one type of reservoir.

Since there are different types of reservoirs in each well, in order to ensure that the compressibility of each of the at least one type of reservoir that is ultimately determined is accurate, the relationship between the shear wave time difference and the longitudinal wave time difference for each of the at least one type of reservoir needs to be determined.

When full wave train logging is performed on each of the N wells, the obtained full wave train logging data of each well contains the transverse wave time difference of each well in all stratum and the longitudinal wave time difference of each well in all stratum, so that the transverse wave time difference of a first type of reservoir in at least one type of reservoir in each well and the longitudinal wave time difference of the first type of reservoir can be determined according to the full wave train logging data of each well. Typically, after full-wave train log data for each well is obtained, the full-wave train log data for each well is separated to separate the longitudinal wave time differences for the first type of reservoir and the transverse wave time differences for the first type of reservoir in each well. For each type of reservoir in at least one type of reservoir in each well, the longitudinal wave time difference and the transverse wave time difference of each type of reservoir can be determined according to the determination mode of the longitudinal wave time difference and the transverse wave time difference of the first type of reservoir.

In addition, in one possible implementation manner, according to the longitudinal wave time difference of the first type of reservoir in each of the N wells and the transverse wave time difference of the first type of reservoir in each of the N wells, the relationship between the transverse wave time difference and the longitudinal wave time difference of the first type of reservoir may be specifically determined as follows: and constructing a second longitudinal wave time difference set from the longitudinal wave time differences of the first type of reservoirs in each well, constructing a second transverse wave time difference set from the transverse wave time differences of the first type of reservoirs in each well, performing data fitting according to the second longitudinal wave time difference set and the second transverse wave time difference set, and taking the result after the data fitting as the relation between the transverse wave time differences and the longitudinal wave time differences of the first type of reservoirs. The data fitting may be performed with the longitudinal wave time difference as the abscissa and the transverse wave time difference as the ordinate.

For example, full-wave train logging is performed on 3 wells in the investigation region, resulting in full-wave train logging data for each of the 3 wells. And determining the transverse wave time difference of the first type of reservoir in each well and the longitudinal wave time difference of the first type of reservoir in each well according to the full wave train logging data of each well. And constructing a second transverse wave time difference set by using the transverse wave time differences of the first type of reservoir in each well, and constructing a second longitudinal wave time difference set by using the longitudinal wave time differences of the first type of reservoir in each well. As shown in fig. 3, when the first type of reservoir is a gas layer, using the longitudinal wave time difference as an abscissa and using the transverse wave time difference as an ordinate, performing data fitting on all the transverse wave time differences in the second transverse wave time difference set and all the longitudinal wave time differences in the second longitudinal wave time difference set to obtain the relationship between the transverse wave time difference and the longitudinal wave time difference of the gas layer as follows:

y＝1.4661x+44.55

Δt _s ＝1.4661Δt _p +44.55

when the first type of reservoir is a dry layer, as shown in fig. 4, with the longitudinal wave time difference as an abscissa and the transverse wave time difference as an ordinate, performing data fitting on all the transverse wave time differences in the second transverse wave time difference set and all the longitudinal wave time differences in the second longitudinal wave time difference set to obtain the relationship between the transverse wave time difference and the longitudinal wave time difference of the dry layer as follows:

y＝1.6345x+14.861

Δt _s ＝1.6345Δt _p +14.861

optionally, in another possible implementation manner, according to the longitudinal wave time difference of the first type of reservoir in each of the N wells and the transverse wave time difference of the first type of reservoir in each of the N wells, an implementation manner of determining the relationship between the transverse wave time difference and the longitudinal wave time difference of the first type of reservoir may refer to another possible implementation manner of determining the relationship between the transverse wave time difference and the longitudinal wave time difference of the stable marker layer according to the longitudinal wave time difference of the stable marker layer in each of the N wells and the transverse wave time difference of the stable marker layer in each of the N wells, which are not described herein.

Step 102: and determining the brittleness index of the non-reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer and the acoustic logging data of the first well, wherein the first well is any well except the well for performing full wave train logging in the research area.

In one possible implementation manner, step 102 may specifically be: density logging data for a first well is acquired. And determining a plurality of dynamic Young modulus and a plurality of dynamic Poisson ratios of the non-reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer, the acoustic logging data of the first well and the density logging data of the first well. A static Young's modulus is determined based on each of the plurality of dynamic Young's moduli, resulting in a plurality of static Young's moduli. And determining a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios to obtain a plurality of static poisson ratios. The formation brittleness index at the corresponding formation depth is determined from each static young's modulus and the corresponding static poisson's ratio.

Wherein the density log data is used to indicate rock densities at different depths in the formation. The dynamic young's modulus refers to young's modulus obtained by a dynamic method, which is used to indicate the supporting ability after rock fracture. The dynamic poisson ratio refers to the poisson ratio obtained by a dynamic method, and the poisson ratio is used for indicating the breaking capacity of rock under the stress. The dynamic Young's moduli and the dynamic Poisson's ratios are in one-to-one correspondence, and each dynamic Young's modulus and the corresponding dynamic Poisson's ratio are in one formation depth. The static Young modulus refers to Young modulus obtained through a static method, the static Poisson ratio refers to Poisson ratio obtained through the static method, the static Young modulus corresponds to the static Poisson ratio one by one, and each static Young modulus corresponds to one stratum depth with the corresponding static Poisson ratio. In addition, the dynamic method refers to determining the young's modulus of the rock by testing the propagation time difference of sound waves in the rock, and the static method refers to applying a constant tensile stress or compressive stress on the rock, determining the young's modulus of the rock according to the applied tensile stress and the strain of the rock under the tensile stress, or determining the young's modulus of the rock according to the applied compressive stress and the strain of the rock under the compressive stress.

Wherein the density log data for the first well may be pre-stored.

In addition, determining the plurality of dynamic young's modulus and the plurality of dynamic poisson's ratios of the non-reservoir in the first well according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer, the sonic logging data of the first well, and the density logging data of the first well may be implemented according to the following formula:

in the above, YME _{Dynamic movement} Represents dynamic Young's modulus, PR _{Dynamic movement} Represents the dynamic poisson ratio, ρ represents the density of the rock, Δt _s Representing transverse wave time difference, deltat _p Representing the longitudinal wave time difference.

In addition, determining a static young's modulus according to each of the plurality of dynamic young's moduli, the implementation manner of obtaining the plurality of static young's moduli may be: the laboratory measured static Young's modulus was obtained for each of the M depths in the stable marker layer. The dynamic Young's modulus corresponding to each of the M depths is found from the plurality of dynamic Young's moduli. And carrying out data fitting on the dynamic Young's modulus corresponding to each depth of the M depths and the static Young's modulus measured by a laboratory corresponding to each depth of the N depths, and taking the result of the data fitting as the relation between the static Young's modulus and the dynamic Young's modulus. A static Young's modulus is determined based on each of the plurality of dynamic Young's moduli and a relationship between the static Young's modulus and the dynamic Young's modulus. Wherein, static Young's modulus can be measured in a laboratory as an abscissa and dynamic Young's modulus as an ordinate.

For example, the static young's modulus measured in a laboratory corresponding to 13 different depths in the stable marker layer is obtained, the dynamic young's modulus corresponding to each depth at the 13 different depths is found from a plurality of dynamic young's moduli, and the 13 dynamic young's modulus and the static young's modulus measured in a laboratory are subjected to data fitting. As shown in fig. 5, data fitting was performed on the static young's modulus and the dynamic young's modulus on the abscissa, and the static young's modulus measured in 13 laboratories, and the result of the data fitting was taken as the relationship between the static young's modulus and the dynamic young's modulus. The following formula is shown:

y＝0.7x+0.772

in the above formula, y represents a static Young's modulus, x represents a dynamic Young's modulus, R ² Representing the fitting accuracy. Typically, YME for dynamic Young's modulus _{Dynamic movement} Represents YME for static Young's modulus _{Static state} Expressed, therefore, the above formula can be expressed again as:

YME _{static state} ＝0.7YME _{Dynamic movement} +0.772

After the relationship between the static Young's modulus and the dynamic Young's modulus is obtained, each dynamic Young's modulus in the plurality of dynamic Young's moduli can be substituted into the relationship between the static Young's modulus and the dynamic Young's modulus to obtain a plurality of static Young's moduli.

In addition, determining a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios may be implemented as follows: a laboratory measured static poisson's ratio corresponding to each of N depths in the stable marker layer is obtained. The dynamic poisson's ratio corresponding to each of the N depths is found from a plurality of dynamic poisson's ratios. And carrying out data fitting on the dynamic poisson ratio corresponding to each depth of the N depths and the static poisson ratio measured in a laboratory corresponding to each depth of the N depths, and taking the result of the data fitting as the relation between the static poisson ratio and the dynamic poisson ratio. A static Poisson ratio is determined based on each of the plurality of dynamic Poisson ratios and a relationship between the static Poisson ratios and the dynamic Poisson ratios. Wherein, static poisson ratio measured in laboratory is taken as an abscissa, and dynamic poisson ratio is taken as an ordinate.

For example, the static poisson ratios measured in the laboratory corresponding to 13 different depths in the stable marker layer are obtained, the dynamic poisson ratio corresponding to each depth of the 13 different depths is searched from a plurality of dynamic poisson ratios, and the 13 dynamic poisson ratios and the static poisson ratios measured in the laboratory are subjected to data fitting. As shown in fig. 6, data fitting is performed on the static poisson ratio measured in 13 laboratories and the 13 dynamic poisson ratios with the static poisson ratio as an abscissa and the dynamic poisson ratio as an ordinate, and the result of the data fitting is taken as a relation between the static poisson ratio and the dynamic poisson ratio. As shown below

y＝1.263x-0.047

In the above formula, y represents static poisson's ratio, x represents dynamic poisson's ratio, R ² Representing the fitting accuracy. In general, dynamic poisson ratio uses PR _{Dynamic movement} Representing static poisson's ratio with PR _{Static state} Expressed, therefore, the above formula can be expressed again as:

PR _{static state} ＝1.263PR _{Dynamic movement} -0.047

After the relation between the static poisson ratio and the dynamic poisson ratio is obtained, each dynamic poisson ratio in the plurality of dynamic poisson ratios can be substituted into the relation between the static poisson ratio and the dynamic poisson ratio to obtain a plurality of static poisson ratios.

In addition, in one possible implementation, determining the formation brittleness index at the corresponding formation depth from each static young's modulus and the corresponding static poisson ratio may specifically be: a maximum and minimum of a plurality of dynamic Young's moduli of the non-reservoir in the first well are obtained. Maximum and minimum values of a plurality of dynamic poisson ratios of a non-reservoir in a first well are obtained. Determining a first normalized Young's modulus of the first well non-reservoir based on a first static Young's modulus of the first well non-reservoir, the first static Young's modulus being any one of a plurality of static Young's moduli of the first well non-reservoir, and a maximum and minimum of the plurality of dynamic Young's moduli. And determining a first normalized plurality of poisson ratios of the first well non-reservoir according to the maximum value and the minimum value of the first static poisson ratio and the dynamic poisson ratio of the first well non-reservoir, wherein the first static poisson ratio is any one of the plurality of static poisson ratios of the first well non-reservoir. A first brittleness index of the first non-reservoir in the first well is determined based on the first normalized young's modulus of the first non-reservoir in the first well and the first normalized poisson's ratio of the first non-reservoir in the first well. For each of the plurality of static young's modulus and the corresponding static poisson ratio for the non-reservoir, a formation brittleness index at the corresponding formation depth may be determined as described above.

Wherein determining a first normalized plurality of young's modulus for the first well non-reservoir based on a first static young's modulus for the first well non-reservoir, a maximum value and a minimum value of the plurality of dynamic young's moduli may be accomplished according to the following equation:

in the above, YME _brit Represents normalized Young's modulus, YME _{Static state} Represents static Young's modulus, YME _max Represents the maximum value of a plurality of dynamic Young's moduli, YME _min Representing the minimum of the plurality of dynamic young's modulus.

In addition, determining the first normalized poisson's ratio for the first well non-reservoir based on the maximum and minimum of the first static poisson's ratio, the dynamic poisson's ratio for the first well non-reservoir may be implemented as follows:

in the above, PR _brit Representing normalized poisson's ratio, PR _{Static state} Representing static poisson's ratio, PR _max Represents the maximum value, PR, of a plurality of dynamic poisson ratios _min Representing the minimum of the plurality of dynamic poisson ratios.

In addition, determining the first brittleness index of the first well non-reservoir based on the first normalized young's modulus of the first well non-reservoir and the first normalized poisson's ratio of the first well non-reservoir may be accomplished according to the following equation:

BRIT＝(YME _brit +PR _brit )/2

in the above formula, BRIT represents the brittleness index, YME _brit Represents normalized Young's modulus, PR _brit Representing normalized poisson's ratio.

Step 103: and determining the brittleness index of each type of reservoir in at least one type of reservoir in the first well according to the relation between the transverse wave time difference and the longitudinal wave time difference of each type of reservoir in at least one type of reservoir and the acoustic logging data of the first well, wherein the acoustic logging data of the first well are used for indicating the longitudinal wave time differences corresponding to different depths in the first well.

In one possible implementation manner, step 103 may specifically be: density logging data for a first well is acquired. For a first type of reservoir in the at least one type of reservoir, determining a plurality of dynamic Young's modulus and a plurality of dynamic Poisson's ratios for the first type of reservoir based on a relationship between a shear wave time difference and a longitudinal wave time difference for the first type of reservoir, sonic log data for the first well, and density log data for the first well. A static Young's modulus is determined based on each of the plurality of dynamic Young's moduli, resulting in a plurality of static Young's moduli. And determining a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios to obtain a plurality of static poisson ratios. The formation brittleness index at the corresponding formation depth is determined from each static young's modulus and the corresponding static poisson's ratio.

The implementation manner of determining the dynamic young's modulus and the dynamic poisson's ratio of the first type of reservoir according to the relationship between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir, the acoustic logging data of the first well, and the density logging data of the first well may refer to the determination of the dynamic young's modulus and the dynamic poisson's ratio of the non-reservoir in the first well according to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer, and the density logging data of the first well, which are not described herein.

In addition, the implementation manner of determining a static young's modulus according to each dynamic young's modulus of the plurality of dynamic young's moduli to obtain the plurality of static young's moduli may refer to the implementation manner of determining a static young's modulus according to each dynamic young's modulus of the plurality of dynamic young's moduli in step 102 to obtain the plurality of static young's moduli, which is not described herein again.

In addition, according to each dynamic poisson ratio in the plurality of dynamic poisson ratios, a static poisson ratio is determined, and an implementation manner of obtaining the plurality of static poisson ratios may refer to determining a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios in step 102, so that an implementation manner of obtaining the plurality of static poisson ratios is not described herein.

In addition, the implementation manner of determining the formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio may refer to the implementation manner of determining the formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio in step 102, which is not described herein.

In order to verify the formation compressibility determination method provided by the embodiment of the application, the following example is used for specific verification.

FIG. 7 is a schematic illustration of a log and various formations provided by an embodiment of the present application. As shown in fig. 7, CAL represents a borehole log. GR represents a natural gamma log. RLA1 represents a shallow lateral resistivity log. RLA5 represents a deep lateral resistivity log. CNL represents neutron porosity log. DEN is a density log. AC represents an acoustic log. Young's modulus before optimization represents dynamic Young's modulus. The Young's modulus after optimization represents the static Young's modulus. Poisson's ratio before optimization represents dynamic poisson's ratio. The optimized poisson ratio represents the static poisson ratio. Experimental determination of the brittleness index represents the brittleness index determined in the laboratory. The pre-optimization brittleness index represents the brittleness index determined in the related art. The optimized brittleness index represents the brittleness index determined according to the method of the present application. The integrated interpretation refers to the type of reservoir determined from the plurality of logs. As shown in fig. 7, the lithology section is shown with the first formation being mudstone from top to bottom. The second formation is tuff. The third formation is a brecciated mudstone. The fourth formation is a breccia. The fifth formation is tuff. The sixth formation is tuff. The seventh formation is a brecciated mudstone. The eighth formation is a brecciated tuff. The ninth formation is a brecciated mudstone. The tenth stratum is a brecciated tuff-containing mudstone. The eleventh formation is tuff. Wherein in fig. 7 different strata are represented with different graphics. As shown in fig. 7, in this column, the dry layer is indicated by a plurality of lines in the box of the figure, and the bad layer is indicated by only one line in the box of the figure. That is, in the comprehensive explanation of this column, the first reservoir from top to bottom is a differential reservoir and the second reservoir is a dry reservoir. In fig. 7, at A, B, C and D, the left line represents the brittleness index of the reservoir determined in the related art, and the right line represents the brittleness index of the reservoir determined according to the method of the present application. As can be seen from fig. 7, the brittleness index of the reservoir determined according to the method of the present application matches the brittleness index determined in the laboratory more accurately.

It should be noted that, in a laboratory, a triaxial fracturing experiment or a uniaxial fracturing experiment is usually performed on a core in a well to determine the young modulus and poisson ratio of the core, and when the triaxial fracturing experiment or the uniaxial fracturing experiment is performed, a stress as high as the formation pressure received in the core is applied around the core, so as to simulate the actual stress of the core in the formation. Thus, the laboratory measured Young's modulus and Poisson's ratio of the core are relatively accurate. The static brittleness index, which is determined according to the Young's modulus and Poisson's ratio of the core measured in a laboratory, is also relatively accurate. The brittleness index of the reservoir layer determined by the method provided by the application is high in coincidence with the brittleness index measured by a laboratory, which indicates that the brittleness index of the reservoir layer determined by the method provided by the application is relatively accurate.

In addition, all formations in a well are not typically cored, and thus the brittleness index for all depths in the well cannot be measured in the laboratory.

Fig. 8 is a schematic structural diagram of a device for determining formation compressibility according to an embodiment of the present application, and as shown in fig. 8, a device 800 includes:

a first determining module 801, configured to determine, according to full wave train logging data of each of N wells performing full wave train logging in a research area, a relationship between a transverse wave time difference and a longitudinal wave time difference of a stable marker layer, and a relationship between a transverse wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir, where the full wave train logging data is used to characterize propagation time differences of acoustic waves at different depths of a stratum, N is a positive integer greater than or equal to 1, and the stable marker layer is a non-reservoir;

a second determining module 802, configured to determine a brittleness index of a non-reservoir in a first well according to a relationship between a shear wave time difference and a longitudinal wave time difference of the stable marker layer and sonic logging data of the first well, where the first well is any well outside a well performing full wave train logging in the research area;

and a third determining module 803, configured to determine a brittleness index of each type of reservoir in at least one type of reservoir according to a relationship between a shear wave time difference and a longitudinal wave time difference of each type of reservoir in at least one type of reservoir and sonic logging data of the first well, where the sonic logging data of the first well is used to indicate longitudinal wave time differences corresponding to different depths in the first well.

Optionally, the first determining module 801 includes:

a first determining unit, configured to determine a longitudinal wave time difference of the stable marker layer in each of the N wells and a transverse wave time difference of the stable marker layer in each of the N wells according to full-wave train logging data of each of the N wells;

and the second determining unit is used for determining the relation between the transverse wave time difference and the longitudinal wave time difference of the stable mark layer according to the longitudinal wave time difference of the stable mark layer in each of the N wells and the transverse wave time difference of the stable mark layer in each well.

Optionally, the first determining module 801 further includes:

a third determining unit, configured to determine, for a first type of reservoir in at least one type of reservoir, a longitudinal wave time difference of the first type of reservoir in each of the N wells and a transverse wave time difference of the first type of reservoir in each of the N wells according to full-wave column logging data of each of the N wells, where the first type of reservoir is any type of reservoir in the at least one type of reservoir;

Optionally, the second determining module 802 includes:

A first acquisition unit for acquiring density log data of the first well, the density log data being indicative of rock densities at different depths of the formation;

a fifth determining unit, configured to determine, according to a relationship between a shear wave time difference and a longitudinal wave time difference of the stable marker layer, acoustic logging data of the first well, and density logging data of the first well, a plurality of dynamic young modulus of a non-reservoir in the first well and a plurality of dynamic poisson ratios, where the dynamic young modulus refers to young modulus obtained by a dynamic method, the young modulus is used to indicate a supporting capability after a rock fracture, the dynamic poisson ratio refers to poisson ratio obtained by a dynamic method, the poisson ratio is used to indicate a breaking capability of the rock under a stress, the plurality of dynamic young modulus and the plurality of dynamic poisson ratios are in one-to-one correspondence, and each dynamic young modulus and corresponding dynamic poisson ratio correspond to a formation depth;

a seventh determining unit, configured to determine a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios, to obtain a plurality of static poisson ratios, where the static young modulus refers to a young modulus obtained by a static method, the static poisson ratio refers to a poisson ratio obtained by a static method, the plurality of static young modulus corresponds to the plurality of static poisson ratios one to one, and each static young modulus corresponds to a stratum depth;

Optionally, the third determining module 803 includes:

the second acquisition unit is used for acquiring the density logging data of the first well;

a ninth determining unit, configured to determine, for a first type of reservoir in at least one type of reservoir, a plurality of dynamic young's modulus and a plurality of dynamic poisson ratios of the first type of reservoir according to a relationship between a shear wave time difference and a longitudinal wave time difference of the first type of reservoir, sonic logging data of the first well, and density logging data of the first well, where the plurality of dynamic young's modulus and the plurality of dynamic poisson ratios are in one-to-one correspondence, and each dynamic young's modulus and the corresponding dynamic poisson ratio are corresponding to one formation depth;

an eleventh determining unit, configured to determine a static poisson ratio according to each dynamic poisson ratio in the plurality of dynamic poisson ratios, to obtain a plurality of static poisson ratios, where the plurality of static young modulus corresponds to the plurality of static poisson ratios one to one, and each static young modulus corresponds to a formation depth to the corresponding static poisson ratio;

A twelfth determining unit for determining a formation brittleness index at the corresponding formation depth according to each static young's modulus and the corresponding static poisson ratio.

It should be noted that: in determining the formation compressibility, the formation compressibility determining device provided in the foregoing embodiment is only exemplified by the division of the foregoing functional modules, and in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the apparatus is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the formation compressibility determining device provided in the above embodiment and the formation compressibility determining method embodiment belong to the same concept, and detailed implementation processes of the formation compressibility determining device are detailed in the method embodiment, and are not described herein again.

Fig. 9 shows a block diagram of a terminal 900 according to an exemplary embodiment of the present application. The terminal 900 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion picture expert compression standard audio plane 3), an MP4 (Moving Picture Experts Group Audio Layer IV, motion picture expert compression standard audio plane 4) player, a notebook computer, or a desktop computer. Terminal 900 may also be referred to by other names of user devices, portable terminals, laptop terminals, desktop terminals, etc.

In general, the terminal 900 includes: a processor 901 and a memory 902.

Processor 901 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 901 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 901 may also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also referred to as a CPU (Central Processing Unit ); a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 901 may integrate a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content required to be displayed by the display screen. In some embodiments, the processor 901 may also include an AI (Artificial Intelligence ) processor for processing computing operations related to machine learning.

The memory 902 may include one or more computer-readable storage media, which may be non-transitory. The memory 902 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 902 is used to store at least one instruction for execution by processor 901 to implement the formation compressibility determination methods provided by the method embodiments of the present application.

In some embodiments, the terminal 900 may further optionally include: a peripheral interface 903, and at least one peripheral. The processor 901, memory 902, and peripheral interface 903 may be connected by a bus or signal line. The individual peripheral devices may be connected to the peripheral device interface 903 via buses, signal lines, or circuit boards. Specifically, the peripheral device includes: at least one of radio frequency circuitry 904, a touch display 905, a camera assembly 906, audio circuitry 907, a positioning assembly 908, and a power source 909.

The peripheral interface 903 may be used to connect at least one peripheral device associated with an I/O (Input/Output) to the processor 901 and the memory 902. In some embodiments, the processor 901, memory 902, and peripheral interface 903 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 901, the memory 902, and the peripheral interface 903 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.

The Radio Frequency circuit 904 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 904 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 904 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 904 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuit 904 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuit 904 may also include NFC (Near Field Communication ) related circuits, which the present application is not limited to.

The display 905 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 905 is a touch display, the display 905 also has the ability to capture touch signals at or above the surface of the display 905. The touch signal may be input as a control signal to the processor 901 for processing. At this time, the display 905 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display 905 may be one, providing a front panel of the terminal 900; in other embodiments, the display 905 may be at least two, respectively disposed on different surfaces of the terminal 900 or in a folded design; in still other embodiments, the display 905 may be a flexible display disposed on a curved surface or a folded surface of the terminal 900. Even more, the display 905 may be arranged in an irregular pattern other than rectangular, i.e., a shaped screen. The display 905 may be made of LCD (Liquid Crystal Display ), OLED (Organic Light-Emitting Diode) or other materials.

The camera assembly 906 is used to capture images or video. Optionally, the camera assembly 906 includes a front camera and a rear camera. Typically, the front camera is disposed on the front panel of the terminal and the rear camera is disposed on the rear surface of the terminal. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, camera assembly 906 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.

The audio circuit 907 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 901 for processing, or inputting the electric signals to the radio frequency circuit 904 for voice communication. For purposes of stereo acquisition or noise reduction, the microphone may be plural and disposed at different portions of the terminal 900. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 901 or the radio frequency circuit 904 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, the audio circuit 907 may also include a headphone jack.

The location component 908 is used to locate the current geographic location of the terminal 900 to enable navigation or LBS (Location Based Service, location-based services). The positioning component 908 may be a positioning component based on the United states GPS (Global Positioning System ), the Beidou system of China, the Granati system of Russia, or the Galileo system of the European Union.

The power supply 909 is used to supply power to the various components in the terminal 900. The power supply 909 may be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 909 includes a rechargeable battery, the rechargeable battery can support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, terminal 900 can further include one or more sensors 910. The one or more sensors 910 include, but are not limited to: acceleration sensor 911, gyroscope sensor 912, pressure sensor 913, fingerprint sensor 914, optical sensor 915, and proximity sensor 916.

The acceleration sensor 911 can detect the magnitudes of accelerations on three coordinate axes of the coordinate system established with the terminal 900. For example, the acceleration sensor 911 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 901 may control the touch display 905 to display a user interface in a landscape view or a portrait view according to the gravitational acceleration signal acquired by the acceleration sensor 911. The acceleration sensor 911 may also be used for the acquisition of motion data of a game or a user.

The gyro sensor 912 may detect a body direction and a rotation angle of the terminal 900, and the gyro sensor 912 may collect a 3D motion of the user on the terminal 900 in cooperation with the acceleration sensor 911. The processor 901 may implement the following functions according to the data collected by the gyro sensor 912: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.

The pressure sensor 913 may be provided at a side frame of the terminal 900 and/or a lower layer of the touch display 905. When the pressure sensor 913 is provided at a side frame of the terminal 900, a grip signal of the user to the terminal 900 may be detected, and the processor 901 performs left-right hand recognition or shortcut operation according to the grip signal collected by the pressure sensor 913. When the pressure sensor 913 is disposed at the lower layer of the touch display 905, the processor 901 performs control of the operability control on the UI interface according to the pressure operation of the user on the touch display 905. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

The fingerprint sensor 914 is used for collecting the fingerprint of the user, and the processor 901 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 914, or the fingerprint sensor 914 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the processor 901 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 914 may be provided on the front, back or side of the terminal 900. When a physical key or a vendor Logo is provided on the terminal 900, the fingerprint sensor 914 may be integrated with the physical key or the vendor Logo.

The optical sensor 915 is used to collect the intensity of ambient light. In one embodiment, the processor 901 may control the display brightness of the touch display 905 based on the intensity of ambient light collected by the optical sensor 915. Specifically, when the ambient light intensity is high, the display brightness of the touch display 905 is turned up; when the ambient light intensity is low, the display brightness of the touch display panel 905 is turned down. In another embodiment, the processor 901 may also dynamically adjust the shooting parameters of the camera assembly 906 based on the ambient light intensity collected by the optical sensor 915.

A proximity sensor 916, also referred to as a distance sensor, is typically provided on the front panel of the terminal 900. Proximity sensor 916 is used to collect the distance between the user and the front of terminal 900. In one embodiment, when the proximity sensor 916 detects that the distance between the user and the front face of the terminal 900 gradually decreases, the processor 901 controls the touch display 905 to switch from the bright screen state to the off screen state; when the proximity sensor 916 detects that the distance between the user and the front surface of the terminal 900 gradually increases, the processor 901 controls the touch display 905 to switch from the off-screen state to the on-screen state.

Those skilled in the art will appreciate that the structure shown in fig. 9 is not limiting and that more or fewer components than shown may be included or certain components may be combined or a different arrangement of components may be employed.

The embodiment of the application also provides a non-transitory computer readable storage medium, which when executed by a processor of a terminal, enables the terminal to execute the method for determining the formation compressibility provided by the embodiment shown in fig. 1.

The embodiment of the application also provides a computer program product containing instructions, which when run on a computer, cause the computer to execute the method for determining the formation compressibility provided by the embodiment shown in fig. 1.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

In summary, the present application is not limited to the preferred embodiments, but includes all modifications, equivalents, and improvements falling within the spirit and principles of the present application.

Claims

1. A method for determining the compressibility of a formation, characterized in that the method includes:

Determine the longitudinal wave transit time of the stable marker layer in each of the N wells and the shear wave transit time of the stable marker layer in each well according to the full wave train logging data of each well in the N wells;

According to the longitudinal wave transit time of the stable marker layer in each of the N wells and the shear wave transit time of the stable marker layer in each well, the relationship between the shear wave transit time and the longitudinal wave transit time of the stable marker layer is determined, and at least one type of reservoir The relationship between the shear wave time difference and the longitudinal wave time difference of each type of reservoir in the reservoir. The full wave train logging data is used to characterize the propagation time difference of sound waves at different depths of the formation. The N is a positive integer greater than or equal to 1, The stable marker layer is a non-reservoir layer. When the porosity of the formation is greater than the numerical threshold, the formation is classified as a reservoir. When the porosity of the formation is less than or equal to the numerical threshold, the formation is classified as a non-reservoir;

Obtaining density log data for the first well, the density log data being indicative of rock density at different depths of the formation;

According to the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marker layer, the sonic logging data of the first well, and the density logging data of the first well, the non-reservoir layer in the first well is determined. Multiple dynamic Young's modulus and multiple dynamic Poisson's ratio are realized according to the following formula:

In the above formula, YME _dynamically represents the dynamic Young's modulus, PR _dynamically represents the dynamic Poisson's ratio, ρ represents the density of the rock, Δt _s represents the shear wave time difference, Δt _p represents the longitudinal wave time difference, and the dynamic Young's modulus refers to the dynamic The Young's modulus obtained by the dynamic method is used to indicate the support capacity of the rock after rupture. The dynamic Poisson's ratio refers to the Poisson's ratio obtained by the dynamic method. The Poisson's ratio is used to indicate the rock's support capacity. The rupture ability under stress, the plurality of dynamic Young's moduli and the plurality of dynamic Poisson's ratios correspond one to one, and each dynamic Young's modulus and the corresponding dynamic Poisson's ratio correspond to a formation depth;

Determine a static Young's modulus according to each dynamic Young's modulus among the plurality of dynamic Young's moduli, and obtain a plurality of static Young's moduli;

According to each dynamic Poisson's ratio among the plurality of dynamic Poisson's ratios, a static Poisson's ratio is determined to obtain a plurality of static Poisson's ratios. The static Young's modulus refers to the Young's modulus obtained by the static method. quantity, the static Poisson's ratio refers to the Poisson's ratio obtained by the static method, the plurality of static Young's moduli correspond to the plurality of static Poisson's ratios, and each static Young's modulus and the corresponding The static Poisson's ratio corresponds to a formation depth;

According to each static Young's modulus and the corresponding static Poisson's ratio, determine the formation brittleness index at the corresponding formation depth, and the first well is any well in the study area other than the well where full wave train logging is performed;

Obtain density logging data of the first well;

For the first type of reservoir in the at least one type of reservoir, according to the relationship between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir, the sonic logging data of the first well, and the first The density logging data of the well is used to determine a plurality of dynamic Young's moduli and a plurality of dynamic Poisson's ratios of the first type of reservoir, and the plurality of dynamic Young's moduli and the plurality of dynamic Poisson's ratios are One correspondence, each dynamic Young's modulus and the corresponding dynamic Poisson's ratio correspond to a formation depth;

According to each dynamic Poisson's ratio in the plurality of dynamic Poisson's ratios, a static Poisson's ratio is determined to obtain a plurality of static Poisson's ratios, the plurality of static Young's moduli and the plurality of static Poisson's ratios. There is a one-to-one correspondence, and each static Young's modulus and the corresponding static Poisson's ratio correspond to a formation depth;

According to each static Young's modulus and the corresponding static Poisson's ratio, the formation brittleness index at the corresponding formation depth is determined, and the acoustic wave logging data is used to indicate the corresponding longitudinal wave time difference of the acoustic wave at different depths of the formation;

Wherein, determining the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marking layer based on the longitudinal wave time difference of the stable marking layer in each of the N wells and the shear wave time difference of the stable marking layer in each well also includes:

The longitudinal wave time difference of each stable marking layer in the well is constructed into a first longitudinal wave time difference set, and the shear wave time difference of each stable marking layer in the well is constructed into a first shear wave time difference set. According to the first longitudinal wave time difference set and the total The first shear wave moveout set is used for data fitting, and the result after data fitting is used as the relationship between the shear wave moveout and the longitudinal wave moveout of the stable marker layer.

2. The method according to claim 1, characterized in that, based on the full wave train logging data of each well in the N wells in the study area, determining each well in at least one type of reservoir. The relationship between the shear wave transit time and longitudinal wave transit time of similar reservoirs includes:

For the first type of reservoir in the at least one type of reservoir, determine the first type of reservoir in each of the N wells based on the full wave train logging data of each of the N wells. longitudinal wave time difference, and shear wave time difference of the first type of reservoir in each well, where the first type of reservoir is any type of reservoir in the at least one type of reservoir;

According to the longitudinal wave time difference of the first type of reservoir in each of the N wells and the shear wave time difference of the first type of reservoir in each well, the shear wave time difference and the longitudinal wave time difference of the first type of reservoir are determined. The relationship between.

3. A device for determining the compressibility of a formation, characterized in that the device includes:

The first determination module is used to determine the relationship between the shear wave time difference and the longitudinal wave time difference of the stable mark layer based on the full wave train logging data of each of the N wells in the study area, and at least one The relationship between the shear wave time difference and the longitudinal wave time difference of each type of reservoir. The full wave train logging data is used to characterize the propagation time difference of sound waves at different depths of the formation. The N is greater than or equal to 1. Positive integer, the stable indicator layer is a non-reservoir layer. When the porosity of the formation is greater than the numerical threshold, the formation is classified as a reservoir. When the porosity of the formation is less than or equal to the numerical threshold, the formation is classified as a non-reservoir. ;

The second determination module is used to determine the brittleness index of the non-reservoir layer in the first well based on the relationship between the shear wave transit time and the longitudinal wave transit time of the stable marker layer and the sonic logging data of the first well. The well is any well in the study area other than the well where full wave train logging is performed;

The third determination module is used to determine the relationship between the shear wave time difference and the longitudinal wave time difference of each type of reservoir in the at least one type of reservoir and the sonic logging data of the first well. The brittleness index of each type of reservoir in the at least one type of reservoir, and the acoustic wave logging data is used to indicate the longitudinal wave time difference corresponding to different depths;

The first determination module includes:

The first determination unit is configured to determine the longitudinal wave time difference of the stable marker layer in each of the N wells and the longitudinal wave time difference of the stable marker layer in each well according to the full wave train logging data of each of the N wells. Transverse wave time difference;

The second determination unit is configured to determine the relationship between the shear wave time difference and the longitudinal wave time difference of the stable marking layer based on the longitudinal wave time difference of the stable marking layer in each of the N wells and the shear wave time difference of the stable marking layer in each well. ,Also includes:

The longitudinal wave time difference of each stable marking layer in the well is constructed into a first longitudinal wave time difference set, and the shear wave time difference of each stable marking layer in the well is constructed into a first shear wave time difference set. According to the first longitudinal wave time difference set and the total The first shear wave moveout set is used for data fitting, and the result after data fitting is used as the relationship between the shear wave moveout and the longitudinal wave moveout of the stable marker layer;

The third determination module includes:

a second acquisition unit, configured to acquire density logging data of the first well;

The ninth determination unit is configured to determine, for the first type of reservoir among the at least one type of reservoir, the relationship between the shear wave time difference and the longitudinal wave time difference of the first type of reservoir, the acoustic wave logging of the first well data, and density logging data of the first well, determining a plurality of dynamic Young's moduli and a plurality of dynamic Poisson's ratios of the first type of reservoir, the plurality of dynamic Young's moduli and the Multiple dynamic Poisson's ratios correspond one to one, and each dynamic Young's modulus and corresponding dynamic Poisson's ratio correspond to a formation depth;

A tenth determination unit, configured to determine a static Young's modulus based on each dynamic Young's modulus among the plurality of dynamic Young's moduli, to obtain multiple static Young's moduli;

An eleventh determination unit, configured to determine a static Poisson's ratio according to each dynamic Poisson's ratio among the plurality of dynamic Poisson's ratios, to obtain a plurality of static Poisson's ratios, the plurality of static Young's moduli There is a one-to-one correspondence with the plurality of static Poisson's ratios, and each static Young's modulus and corresponding static Poisson's ratio corresponds to a formation depth;

The twelfth determination unit is used to determine the formation brittleness index at the corresponding formation depth based on each static Young's modulus and the corresponding static Poisson's ratio;

The second determination module includes:

A first acquisition unit configured to acquire density logging data of the first well, where the density logging data is used to indicate rock densities at different depths of the formation;

The fifth determination unit is configured to determine the said stable mark layer based on the relationship between the shear wave time difference and the longitudinal wave time difference, the sonic logging data of the first well, and the density logging data of the first well. Multiple dynamic Young's moduli and multiple dynamic Poisson's ratios of the non-reservoir in the first well are realized according to the following formula:

A sixth determination unit, configured to determine a static Young's modulus based on each dynamic Young's modulus among the plurality of dynamic Young's moduli, to obtain multiple static Young's moduli;

The seventh determination unit is used to determine a static Poisson's ratio according to each dynamic Poisson's ratio in the plurality of dynamic Poisson's ratios, and obtain a plurality of static Poisson's ratios. The static Young's modulus refers to The Young's modulus obtained by the static method, the static Poisson's ratio refers to the Poisson's ratio obtained by the static method, the plurality of static Young's moduli and the plurality of static Poisson's ratios correspond one to one, each The static Young's modulus and the corresponding static Poisson's ratio correspond to a formation depth;

The eighth determination unit is used to determine the formation brittleness index at the corresponding formation depth based on each static Young's modulus and the corresponding static Poisson's ratio.

4. The device according to claim 3, wherein the first determining module further includes:

The third determination unit is configured to determine, for the first type of reservoir in the at least one type of reservoir, based on the full wave train logging data of each of the N wells, the The longitudinal wave time difference of the first type of reservoir and the shear wave time difference of the first type of reservoir in each well, the first type of reservoir being any one of the at least one type of reservoir;

The fourth determination unit is configured to determine the first type of reservoir based on the longitudinal wave time difference of the first type of reservoir in each of the N wells and the shear wave time difference of the first type of reservoir in each well. The relationship between the shear wave moveout and longitudinal wave moveout of the layer.

5. A device for determining the compressibility of a formation, characterized in that the device includes:

processor;

Memory used to store instructions executable by the processor;

Wherein, the processor is configured to perform the steps of any method described in claim 1 or 2.

6. A computer-readable storage medium, the computer-readable storage medium stores instructions, and when the instructions are executed by a processor, the steps of any one of the methods of claim 1 or 2 are implemented.