CN119475817B - A method and system for quantitative characterization of oil reservoir parameters - Google Patents

Abstract

The invention provides a method and system for quantitatively characterizing reservoir parameters in an oil region, and relates to the technical field of petroleum engineering. The invention collects historical oil region reserve information, core data and well logging data of oil region geological data, extracts features from the core data and well logging data to obtain porosity, permeability and water saturation, and generates oil region recoverability through the features; trains and optimizes a model with oil region recoverability and oil region reserves as labels and historical core data and well logging data as data sets, inputs the core data and well logging data of the oil region to be evaluated into the optimized model to obtain oil region recoverability and oil region reserves, analyzes the oil region recoverability to obtain safe oil region recoverability, generates an oil region potential index through the core data, constructs an oil region revenue model according to the oil region reserves, the oil region potential index and the safe oil region recoverability, and generates an oil region revenue index; and quantitatively evaluates the exploitation revenue of the oil region through the oil region revenue index.

Description

Quantitative characterization method and system for reservoir parameters of oil area

Technical Field

The invention relates to the technical field of petroleum engineering, in particular to a quantitative characterization method and system for reservoir parameters of an oil area.

Background

In the field of petroleum exploration and exploitation, accurate assessment of reservoir characteristics of an oil region is not only a key for improving exploitation efficiency and economic benefits, but also a foundation for ensuring sustainable utilization of resources and environmental protection. Traditional reservoir evaluation methods, such as relying on limited geological data and empirical judgment, often have difficulty in fully reflecting the complexity and dynamic changes of the reservoir. This limitation is particularly pronounced in the face of increasingly complex reservoir conditions and ever increasing amounts of data. As oilfield development proceeds, reservoir conditions become more complex and variable, including diversity of geologic structures, variability of fluid properties, dynamic changes in reservoir response during production, etc., which place greater demands on reservoir evaluation.

When the traditional method is used for processing the complex situations, the accuracy and reliability of the evaluation result are often insufficient due to the problems of limited data processing capacity, insufficient model complexity, poor dynamic adaptability and the like. For example, conventional methods may not be effective in dealing with the flow behavior of multiphase fluids in complex geologic structures or lack sufficient accuracy in predicting reservoir dynamics. In addition, with advances in exploration technology, applications of technologies such as three-dimensional seismic imaging, high resolution logging, and core analysis, have resulted in large amounts of high-dimensional data that are difficult to use effectively in conventional methods.

Therefore, developing a method for quantitatively characterizing reservoir parameters by comprehensively utilizing multi-source data and adopting advanced mathematical models and machine learning technology becomes a technical problem which needs to be solved urgently in the petroleum industry. The method not only needs to be able to process and analyze large amounts of complex data, but also needs to be able to construct accurate mathematical models to simulate reservoir behavior and to continuously optimize model parameters through machine learning techniques to accommodate dynamic changes in the reservoir. By the method, the reservoir can be more accurately evaluated for the producibility, the exploitation strategy is optimized, the resource utilization rate is improved, the environmental risk is reduced, and the sustainable development of petroleum exploration and exploitation is realized.

In the prior art, publication number CN112304843B discloses a quantitative characterization method for the adsorption quantity of shale gas in shale, which relates to the technical field of shale gas development, and a shale core sample is taken along a vertical surface of a stratum, and after oil removal and drying treatment, the total specific surface area of the shale core sample is obtained by utilizing a liquid nitrogen adsorption test experiment; the method comprises the steps of obtaining a pore type distribution diagram of a shale core sample by utilizing a scanning electron microscope, obtaining the occupied proportion of each pore type, obtaining the specific surface area of each pore type according to the total specific surface area of the shale core sample and the occupied proportion of each pore type, obtaining the shale gas adsorption quantity of the single pore type core sample by taking the single pore type core sample and carrying out shale gas adsorption test, obtaining the shale gas adsorption quantity of the shale core sample according to the specific surface area of the shale core sample, the specific surface area of each pore type in the shale core sample and the shale gas adsorption quantity of the single pore type core sample, wherein the prior art still has the defects that firstly, only one shale core sample is collected, the sampling of the method is too single and the occasional problem cannot be effectively removed, therefore, the result is difficult to comprehensively reflect the shale gas adsorption quantity characteristics of the whole shale, and secondly, the factors influencing the shale gas adsorption quantity, including but not limited by pore structure, pressure, temperature, water content and organic matter content have obvious influence on the adsorption quantity. However, in the prior art, quantitative analysis is performed only by pore structure when quantitatively characterizing the adsorption amount of shale gas, and the method is obviously insufficient in convincing that the comprehensive effect of other key factors is not comprehensively considered.

The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.

Disclosure of Invention

The invention aims to provide a quantitative characterization method and system for reservoir parameters of an oil area, which are used for solving the problems in the background technology.

In order to achieve the above purpose, the present invention provides the following technical solutions:

a quantitative characterization method for reservoir parameters of an oil area comprises the following specific steps:

Step 1, acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprises core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprises stratum water resistivity, stratum resistivity and reservoir thickness;

Step 2, analyzing and processing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating the water saturation according to the analysis result, constructing an oil zone mining degree model by analyzing the water saturation, the permeability and the porosity, and generating the oil zone mining degree;

step 3, forming a data set by core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

Step 4, inputting core data and logging data of an oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

And 5, generating an oil zone potential index by carrying out mathematical analysis on the thickness of the reservoir, the oil gas saturation, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safe oil zone recovery, generating an oil zone benefit index, and quantitatively evaluating the oil zone recovery benefit through the oil zone benefit index.

Further, the specific logic on which the water saturation is generated is that mathematical analysis is performed through formation water resistivity, formation resistivity and porosity, and the water saturation is estimated according to the analysis result, and the specific formula on which the water saturation is generated is as follows:

;

wherein, In order to achieve a water saturation level,The cementing coefficient of the cement-based composite material,For the formation water resistivity to be high,In order to achieve a degree of porosity, the porous material,Is the formation resistivity.

Further, the specific logic on which the oil zone recovery is generated is that the oil zone recovery is generated through the water saturation, the permeability and the porosity, and the specific formula is as follows:

;

wherein, Is the recovery degree of the oil area,In order to achieve a degree of porosity, the porous material,In order to achieve a water saturation level,Is permeability.

Further, the root mean square error is used as a loss function, andRegularization adjusts the loss function, and the specific adjustment function is as follows:

;

wherein, Is a parameter of the model and is a parameter of the model,As a set of parameters of the model,Is the firstThe actual oil area availability corresponding to the group model parameters,Is the firstPredicting the oil area availability corresponding to the group model parameters,Is a regularization parameter which is a function of the data,For the total number of data categories in the model parameters,Is the first of the model parametersCore data or logging data.

Further, the specific logic on which the threshold segmentation of the oil region availability is based is that an oil region availability threshold is set, the oil region availability is compared with the oil region availability threshold, and the oil region availability smaller than or equal to the oil region availability threshold is calibrated to be zero, according to the specific formula:

;

wherein, In order to ensure the recovery degree of the oil area,Is the recovery degree of the oil area,A threshold may be taken for the oil zone.

Further, the specific logic on which the oil zone potential index is generated is that an oil zone potential model is generated through the reservoir thickness, the oil gas saturation, the API gravity and the sulfur content in core data, and the oil zone potential index is obtained according to the specific formula:

;

wherein, As an index of the potential of the oil field,For the thickness of the reservoir layer,Is the saturation degree of oil gas, and the oil gas is saturated,For the API gravity of the sample,Is sulfur content.

Further, the specific logic for generating the oil zone benefit index is that an oil zone benefit model is constructed according to the oil zone reserves, the oil zone potential index and the safe oil zone availability to generate the oil zone benefit index, and the specific formula is as follows:

;

wherein, The oil field benefit index is a measure of the oil field benefit index,In order to ensure the recovery degree of the oil area,As an index of the potential of the oil field,Is the oil field reserve.

The invention further provides a quantitative characterization system of the reservoir parameters of the oil area, which is used for realizing the quantitative characterization method of the reservoir parameters of the oil area, and comprises the following steps:

The data acquisition module is used for acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprise core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprise formation water resistivity, formation resistivity and reservoir thickness;

The data analysis module is used for analyzing and processing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating the water saturation according to the analysis result, constructing an oil zone mining degree model by analyzing the water saturation, the permeability and the porosity, and generating the oil zone mining degree;

the modeling optimization module is used for forming a data set from core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

The data processing module is used for inputting core data and logging data of the oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

The quantitative characterization module is used for generating an oil zone potential index through mathematical analysis of the thickness of the reservoir, the saturation of oil gas, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safety oil zone availability, generating an oil zone benefit index, and quantitatively evaluating the oil zone exploitation benefit through the oil zone benefit index.

Compared with the prior art, the invention has the beneficial effects that:

according to the invention, through comprehensively collecting core data and logging data covering the whole reservoir, the limitation of single sampling in the prior art is successfully overcome, and the accident of the result is obviously reduced. When the reservoir parameters are accurately and quantitatively represented, the multi-dimensional parameters affecting the characteristics are comprehensively considered, so that the problem of inaccurate characteristic expression possibly caused by only depending on main parameters is avoided, and the comprehensiveness and the accuracy of the representation result are ensured.

After quantitatively characterizing the oil zone availability and the oil zone potential index, the invention integrates the oil zone availability and the oil zone potential index by combining known data to generate an oil zone benefit index reflecting the benefit obtained by starting the oil production zone, thereby providing an important basis for the evaluation of the oil zone.

Drawings

FIG. 1 is a schematic flow chart of a quantitative characterization method for reservoir parameters of an oil area.

FIG. 2 is a schematic diagram of a system for quantitative characterization of reservoir parameters in an oil zone.

Detailed Description

The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.

It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "up", "down", "left", "right" and the like are used only to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed accordingly.

Examples:

Referring to fig. 1, the present invention provides a technical solution:

a quantitative characterization method for reservoir parameters of an oil area comprises the following specific steps:

Step 1, acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprises core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprises stratum water resistivity, stratum resistivity and reservoir thickness;

In the embodiment, a rock sample in the middle of an oil reservoir is brought to the ground through drilling coring, sent to a laboratory, obtained through a core analyzer, and subjected to core volume, core pore volume, core length, core cross-sectional area, fluid volume flow and fluid pressure difference, raw liquid in pores is extracted, fluid viscosity, API (application program interface) weight and sulfur content are measured through a viscometer, a densimeter and a sulfur analyzer are used for measuring fluid viscosity, API weight and sulfur content, and oil gas saturation is measured through a gamma ray attenuation technology. Formation water resistivity and formation resistivity are measured by resistivity logging tools and reservoir thickness is measured by sonic logging tools.

Step 2, analyzing and processing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating the water saturation according to the analysis result, constructing an oil zone mining degree model by analyzing the water saturation, the permeability and the porosity, and generating the oil zone mining degree;

the specific formula according to which the porosity is obtained is:

;

wherein, In order to achieve a degree of porosity, the porous material,As the pore volume of the core,The porosity reflects the size of the rock pores, and the larger the value is, the larger the pores in the rock are, which is an important parameter for evaluating the characteristics of an oil area.

The formula according to which the permeability is obtained is:

;

wherein, In order for the permeability to be a function of,In terms of the viscosity of the fluid,For the length of the core,Is the cross-sectional area of the core,In the case of a pressure difference of the fluid,For fluid volume flow, permeabilityReflecting the ability of the fluid to pass through the rock, the greater the value thereof, the greater the ability of the fluid to pass through the rock, the easier the exploitation, the permeabilityIs an important parameter for evaluating the performance of an oil zone.

The specific logic on which the water saturation is generated is that mathematical analysis is carried out through formation water resistivity, formation resistivity and porosity, and the water saturation is estimated according to the analysis result, and the specific formula is as follows:

;

wherein, In order to achieve a water saturation level,The cementing coefficient of the cement-based composite material,For the formation water resistivity to be high,In order to achieve a degree of porosity, the porous material,Is the formation resistivity. Saturation of waterThe relative content of water in the rock pore is reflected, and the larger the value is, the larger the volume ratio of water in the rock pore is, and correspondingly, the smaller the volume ratio of oil gas is, so that the method can be used as an important basis for evaluating the performance characteristics of an oil area.

The specific logic for generating the oil region availability is that the oil region availability is generated through the water saturation, the permeability and the porosity, and the specific formula is as follows:

;

wherein, Is the recovery degree of the oil area,In order to achieve a degree of porosity, the porous material,In order to achieve a water saturation level,Is permeability. Oil zone recoveryReflecting the extent of hydrocarbon recovery in hydrocarbon reservoirs, the greater the value, the greater the extent of hydrocarbon recovery, the water saturationThe larger the value of the relative content of water in the rock pore is reflected, which means that the larger the volume ratio of water in the rock pore is, the smaller the volume ratio of oil gas is correspondingly, the harder the exploitation is, and the permeability isReflecting the ability of the fluid to pass through the rock, the greater the value thereof, the greater the ability of the fluid to pass through the rock, the easier the exploitation, the porosityThe method reflects the size of the rock pores, the larger the numerical value is, the larger the pores in the rock are, the easier the exploitation is, the formula reflects the comprehensive influence of the parameters on the exploitation degree of the oil zone, and an important basis is provided for evaluating the exploitation condition of the oil zone.

Step 3, forming a data set by core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

Using root mean square error as a loss function Regularization adjusts the loss function, and the specific adjustment function is as follows:

;

wherein, Is a parameter of the model and is a parameter of the model,As a set of parameters of the model,Is the firstThe actual oil area availability corresponding to the group model parameters,Is the firstPredicting the oil area availability corresponding to the group model parameters,Is a regularization parameter which is a function of the data,For the total number of data categories in the model parameters,Is the first of the model parametersCore data or logging data. The model parametersIs a vector composed of core data and logging data;

when the label is oil zone reserves, the oil zone availability in the formula is replaced by the oil zone reserves. The two labels are independently operated, and the total loss is calculated by adding according to the proportion of 1:1;

Step 4, inputting core data and logging data of an oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

The specific logic for threshold segmentation of the oil zone availability is that an oil zone availability threshold is set, the oil zone availability is compared with the oil zone availability threshold, and the oil zone availability less than or equal to the oil zone availability threshold is calibrated to be zero, according to the specific formula:

;

wherein, In order to ensure the recovery degree of the oil area,Is the recovery degree of the oil area,A threshold may be taken for the oil zone. Safety oil zone recoveryReflecting the safe exploitation degree of oil gas in oil and gas reservoir, the greater the value, the greater the exploitation degree of oil gas, the exploitation degree of oil regionReflecting the degree of oil and gas recovery in oil and gas reservoir, the greater the value, the greater the degree of safe recovery of oil and gas, and when the oil is in the oil zone, the degree of recoveryBelow a preset threshold, the oil zone cannot be safely mined, and the oil zone is not provided with mining value at present, so that the mining degree of the oil zone which cannot be safely mined is marked as 0 through the threshold for mining the oil zone.

And 5, generating an oil zone potential index by carrying out mathematical analysis on the thickness of the reservoir, the oil gas saturation, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safe oil zone recovery, generating an oil zone benefit index, and quantitatively evaluating the oil zone recovery benefit through the oil zone benefit index.

The specific logic on which the oil zone potential index is generated is that an oil zone potential model is generated through the reservoir thickness, the oil gas saturation, the API gravity and the sulfur content in core data, and the oil zone potential index is obtained according to the specific formula:

;

wherein, As an index of the potential of the oil field,For the thickness of the reservoir layer,Is the saturation degree of oil gas, and the oil gas is saturated,For the API gravity of the sample,Is sulfur content. Index of oil field potentialIndex of potential of oil zoneReflecting the development potential and economic value of the oil and gas reservoir, the larger the development potential and economic value of the oil and gas reservoir, and the thickness of the reservoirReflecting the vertical depth of the oil and gas reservoir, the larger the value is, the larger the vertical depth of the oil and gas reservoir is, the more the oil storage capacity of the oil and gas reservoir is, the higher the development potential of the oil and gas reservoir is, and the oil and gas saturation isReflecting the proportion of the volume of oil gas in the rock pores to the total volume of the pores, the larger the value, the higher the proportion of the oil gas in the rock pores, the larger the potential of oil and gas reservoirs, and the API gravityReflecting the density of crude oil, the larger the value, the smaller the density of crude oil, the easier the crude oil is to be extracted and transported, and thus the greater the oil field potential. Sulfur contentReflecting the sulfur content of crude oil, the smaller the value thereof, the higher the quality of crude oil, because crude oil with low sulfur content has less influence on the environment in processing and use and the processing cost is lower.

The specific logic for generating the oil zone benefit index is that an oil zone benefit model is built according to the oil zone reserves, the oil zone potential index and the safe oil zone availability to generate the oil zone benefit index, and the specific formula is as follows:

;

wherein, The oil field benefit index is a measure of the oil field benefit index,In order to ensure the recovery degree of the oil area,As an index of the potential of the oil field,Is the oil field reserve. Oil zone benefit indexReflecting the income situation obtained by the oil extraction area, the larger the value is, the larger the income can be obtained by the oil extraction area, and the safety oil extraction area can produceReflecting the safe recovery degree of oil gas in the oil zone recovery degree oil gas reservoir, the greater the value of the safe recovery degree of the oil gas, the greater the recovery degree of the oil gas, the potential index of the oil zoneReflecting the development potential and economic value of the oil and gas reservoir, the larger the value is, the larger the development potential and economic value of the oil and gas reservoir are, and the reserve of the oil area isReflecting the quantity of oil stored in the oil area, the larger the value is, the more the oil is stored in the oil area, and the greater the income of the oil extraction area is.

Referring to fig. 2, the present invention further provides a system for quantitatively characterizing a reservoir parameter of an oil zone, where the system is configured to implement the method for quantitatively characterizing a reservoir parameter of an oil zone, and the method includes:

The data acquisition module is used for acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprise core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprise formation water resistivity, formation resistivity and reservoir thickness;

The data analysis module is used for analyzing and processing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating the water saturation according to the analysis result, constructing an oil zone mining degree model by analyzing the water saturation, the permeability and the porosity, and generating the oil zone mining degree;

the modeling optimization module is used for forming a data set from core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

The data processing module is used for inputting core data and logging data of the oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

The quantitative characterization module is used for generating an oil zone potential index through mathematical analysis of the thickness of the reservoir, the saturation of oil gas, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safety oil zone availability, generating an oil zone benefit index, and quantitatively evaluating the oil zone exploitation benefit through the oil zone benefit index.

The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.

Claims (8)

1. The quantitative characterization method for the reservoir parameters of the oil area is characterized by comprising the following specific steps of:

Step 1, acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprises core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprises stratum water resistivity, stratum resistivity and reservoir thickness;

Analyzing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating to obtain water saturation according to an analysis result, constructing an oil zone recoverable model by analyzing the water saturation, the permeability and the porosity, and generating oil zone recoverable;

step 3, forming a data set by core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

Step 4, inputting core data and logging data of an oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

And 5, generating an oil zone potential index by carrying out mathematical analysis on the thickness of the reservoir, the oil gas saturation, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safe oil zone recovery, generating an oil zone benefit index, and quantitatively evaluating the oil zone recovery benefit through the oil zone benefit index.

2. The quantitative characterization method of oil area reservoir parameters according to claim 1 is characterized in that the specific logic for generating the water saturation is that mathematical analysis is performed through formation water resistivity, formation resistivity and porosity, and the water saturation is estimated according to the analysis result, and the specific formula is as follows:

;

wherein, In order to achieve a water saturation level,The cementing coefficient of the cement-based composite material,For the formation water resistivity to be high,In order to achieve a degree of porosity, the porous material,Is the formation resistivity.

3. A quantitative characterization method for reservoir parameters of oil area according to claim 1 is characterized in that the root mean square error is adopted as a loss function, and the method comprises the following steps ofRegularization adjusts the loss function, and the specific adjustment function is as follows:

;

wherein, Is a parameter of the model and is a parameter of the model,As a set of parameters of the model,Is the firstThe actual oil area availability corresponding to the group model parameters,Is the firstPredicting the oil area availability corresponding to the group model parameters,Is a regularization parameter which is a function of the data,For the total number of data categories in the model parameters,Is the first of the model parametersCore data or logging data.

4. The quantitative characterization method of the reservoir parameters of the oil area according to claim 1 is characterized in that the specific logic for generating the recovery rate of the oil area is that the recovery rate of the oil area is generated through the water saturation, the permeability and the porosity according to the specific formula:

;

wherein, Is the recovery degree of the oil area,In order to achieve a degree of porosity, the porous material,In order to achieve a water saturation level,Is permeability.

5. The quantitative characterization method of the reservoir parameters of the oil area according to claim 1 is characterized in that the specific logic based on which the threshold segmentation is carried out on the recovery of the oil area is as follows:

setting an oil zone recoverable threshold, comparing the oil zone recoverable degree with the oil zone recoverable threshold, and calibrating the oil zone recoverable degree smaller than or equal to the oil zone recoverable threshold to be zero according to the following specific formula:

;

wherein, In order to ensure the recovery degree of the oil area,Is the recovery degree of the oil area,A threshold may be taken for the oil zone.

6. The quantitative characterization method of oil region reservoir parameters according to claim 1, wherein the specific logic based on which the oil region potential index is generated is as follows:

Generating an oil zone potential model through reservoir thickness, oil gas saturation, API (application program interface) weight and sulfur content in core data to obtain an oil zone potential index, wherein the specific formula is as follows:

;

wherein, As an index of the potential of the oil field,For the thickness of the reservoir layer,Is the saturation degree of oil gas, and the oil gas is saturated,For the API gravity of the sample,Is sulfur content.

7. The quantitative characterization method of oil zone reservoir parameters according to claim 1 is characterized in that the specific logic for generating the oil zone benefit index is that an oil zone benefit model is constructed according to oil zone reserves, oil zone potential indexes and safe oil zone availability to generate the oil zone benefit index, and the specific formula is as follows:

;

wherein, The oil field benefit index is a measure of the oil field benefit index,In order to ensure the recovery degree of the oil area,As an index of the potential of the oil field,Is the oil field reserve.

8. A quantitative characterization system for oil zone reservoir parameters is characterized in that the system is used for realizing the quantitative characterization method for oil zone reservoir parameters according to any one of claims 1 to 7, and comprises the following steps:

The data acquisition module is used for acquiring historical oil zone reserves information, historical core data and historical logging data of oil zone geological data, wherein the core data comprise core volume, core void volume, fluid viscosity, core length, core cross-sectional area, fluid pressure difference, oil gas saturation, API (application program interface) weight and sulfur content, and the logging data comprise formation water resistivity, formation resistivity and reservoir thickness;

The data analysis module is used for analyzing and processing the rock core data to obtain porosity and permeability, carrying out mathematical analysis on the formation water resistivity, the formation resistivity and the porosity, estimating the water saturation according to the analysis result, constructing an oil zone mining degree model by analyzing the water saturation, the permeability and the porosity, and generating the oil zone mining degree;

the modeling optimization module is used for forming a data set from core data and logging data in the historical geological data, constructing an oil zone assessment model by taking oil zone reserves and oil zone availability as labels, and training and optimizing the oil zone assessment model by using the data set to obtain a final oil zone assessment model;

The data processing module is used for inputting core data and logging data of the oil zone to be analyzed into a final oil zone evaluation model to obtain oil zone reserves and oil zone recovery, carrying out threshold processing on the oil zone recovery in a mode of comparing the oil zone recovery with a preset threshold value, and obtaining safe oil zone recovery according to a threshold processing result;

The quantitative characterization module is used for generating an oil zone potential index through mathematical analysis of the thickness of the reservoir, the saturation of oil gas, the API gravity and the sulfur content, constructing an oil zone benefit model according to the oil zone reserve, the oil zone potential index and the safety oil zone availability, generating an oil zone benefit index, and quantitatively evaluating the oil zone exploitation benefit through the oil zone benefit index.