CN111561266A - Stratum crack identification method and system - Google Patents
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Abstract
A formation crack identification method and system are provided, wherein the method comprises the following steps: acquiring imaging resistivity data of each sampling point along the circumferential direction and the depth direction of a well under the well to obtain an imaging resistivity array of an area to be analyzed; separating according to the imaging resistivity array to obtain a plurality of characteristic data groups, wherein different characteristic data groups correspond to different cracks which may exist; and respectively determining the area and the maximum length of each characteristic data group, calculating the ratio of the area to the maximum length, and respectively determining whether a crack or a hole exists in the corresponding region of each characteristic data group according to the ratio. The method identifies the cracks in the well and transmits the characteristic information of the cracks to the ground under the condition of identifying the cracks, so that the existing data transmission technology can be utilized to quickly and completely transmit the information to the ground, and the method has important significance on the safety, efficiency and safety of drilling.
Description
Technical Field
The invention relates to the technical field of oil and gas exploration and development, in particular to a stratum crack identification method and system.
Background
The drilling processes of horizontal wells, highly deviated wells and the like are generally as follows: a predetermined well plan is first designed to run, then under drilling conditions according to Measurement While Drilling (MWD) and Logging While Drilling (LWD) systems, and then downhole conditions are sent to the surface. And then the ground engineer carries out analysis processing according to the data returned to the ground so as to calculate the information such as the current position of the drill bit, the underground stratum condition and the like, and sends an instruction to adjust or keep the advancing direction of the drill bit or carry out tripping to adjust according to the calculation processing results.
That is, in prior art geosteering operations, data collected downhole must be sent to the surface, interpreted and analyzed by a surface pilot engineer, and instructions for further drilling made.
Various types of MWD and LWD have been able to perform various types of downhole data acquisition, essentially detailing the downhole conditions, but limited by the transmission while drilling techniques, such data cannot be efficiently transmitted to the surface.
The existing transmission while drilling modes comprise a mud pulser mode and an electromagnetic mode, the transmission rates of the two modes are only about 1bit/s, the transmission bandwidth is very limited, and the real-time uploading of all underground acquired data, particularly the uploading of imaging data, can not be met far. And the identification of the stratum fractures can be processed and identified only by clear stratum imaging data.
Therefore, in practical applications, only a small portion of the data is transmitted to the surface. And according to the data, a ground engineer cannot effectively judge whether the formation fracture exists or not and the trend of the formation fracture and other key information. Therefore, the ground engineer can only analyze and process very limited data and then make decisions according to the processed results. Such decision correctness is very limited.
Disclosure of Invention
In order to solve the above problems, the present invention provides a formation crack identification method, including:
acquiring imaging resistivity data of each sampling point along the circumferential direction and the depth direction of a well under the well to obtain an imaging resistivity array of an area to be analyzed;
separating according to the imaging resistivity array to obtain a plurality of characteristic data groups, wherein different characteristic data groups correspond to different cracks which may exist;
and step three, respectively determining the area and the maximum length of each characteristic data group, calculating the ratio of the area to the maximum length, and respectively determining whether cracks or holes exist in the corresponding area of each characteristic data group according to the ratio.
According to an embodiment of the present invention, the second step includes:
step a, calculating an imaging resistivity average value of the imaging resistivity array;
b, extracting a characteristic array from the imaging resistivity array according to the imaging resistivity average value;
and c, separating the characteristic array to obtain a plurality of characteristic data groups.
According to an embodiment of the present invention, in the step b, for any element in the imaging resistivity array, it is determined whether an imaging resistivity value corresponding to the element is smaller than a ratio of the imaging resistivity average value to a preset calculation coefficient, and if so, the element is extracted and used as a constituent element in the feature array, where a value of the preset calculation coefficient is greater than 1.
According to an embodiment of the present invention, the step c includes:
c1, selecting an element from the characteristic array and placing the element into a first characteristic data group;
c2, selecting elements adjacent to a first characteristic data group in the imaging resistivity array from the characteristic array and merging the elements into the first characteristic data group;
and c3, traversing all elements in the feature array based on the step c2 to obtain a final first feature data group.
According to an embodiment of the present invention, the step c further comprises:
c4, removing elements contained in the obtained k characteristic data groups from the characteristic array, and selecting an element from the characteristic array after the corresponding element is removed again to be placed in the (k + 1) th characteristic data group;
c5, selecting elements adjacent to the (k + 1) th characteristic data group in the imaging resistivity array from the characteristic array after the corresponding elements are removed, and merging the elements into the (k + 1) th characteristic data group;
step c6, based on the step c5, traversing all elements in the feature data group after the corresponding elements are removed, and separating to obtain a final (k + 1) th feature data group;
and c7, removing elements contained in the obtained k +1 feature data groups from the feature array U, judging whether the elements which are not removed still exist in the feature array, if so, adding 1 to the value of k, and executing the steps c4 to c7 again.
According to an embodiment of the present invention, in the third step, for any feature data group, the area of the feature data group is determined by counting the number of elements included in the feature data group.
According to an embodiment of the present invention, in the third step, for any feature data group, if the ratio of the area to the maximum length is smaller than a preset ratio threshold, it is determined that a crack exists in the region corresponding to the feature data group.
According to an embodiment of the invention, the method further comprises:
extracting extreme value coordinate points of each characteristic data group for each characteristic data group with cracks in the corresponding region under the well;
and fifthly, transmitting the extreme value coordinate point to a ground end, and determining the crack angle of the crack corresponding to the characteristic data group at the ground end according to the extreme value coordinate point of the corresponding characteristic data group.
According to one embodiment of the invention, the fracture angle is determined according to the following expression:
θ＝arctan[(Ymax-Ymin)×v/(Xmax-Xmin)]
wherein θ represents a crack angle, YmaxAnd YminA maximum value and a minimum value of coordinates in a depth direction of the characteristic data group, v represents a drilling speed, and XmaxAnd XminThe maximum value and the minimum value of the coordinates perpendicular to the depth direction of the feature data group are respectively represented.
The invention also provides a formation crack identification system, which comprises:
the imaging resistivity acquisition device is used for acquiring imaging resistivity data of each sampling point along the circumferential direction and the depth direction of the well under the well to obtain an imaging resistivity array of an area to be analyzed;
and the underground data processing device is connected with the imaging resistivity acquisition device and is used for separating and obtaining a plurality of characteristic data groups according to the imaging resistivity array, wherein different characteristic data groups correspond to different cracks which may exist, the underground data processing device is also used for respectively determining the area and the maximum length of each characteristic data group, calculating the ratio of the area to the maximum length, and respectively determining whether cracks or holes exist in the corresponding area of each characteristic data group according to the ratio.
According to one embodiment of the invention, the downhole data processing device is configured to first calculate an average imaging resistivity value of the imaging resistivity array, extract a feature array from the imaging resistivity array according to the average imaging resistivity value, and then separate the feature array to obtain a plurality of feature data groups.
According to one embodiment of the invention, the downhole data processing device is configured to first select an element from the feature array to be placed in a first feature data group, then select an element from the feature array that is adjacent to the first feature data group in the imaging resistivity array and merge into the first feature data group, and then traverse all elements in the feature array based on the same principle to obtain a final first feature data group.
According to an embodiment of the invention, the downhole data processing device is further configured to:
removing elements contained in the obtained k characteristic data groups from the characteristic data, and selecting an element from the characteristic data from which the corresponding element is removed again to place the element in a (k + 1) th characteristic data group;
selecting elements adjacent to the (k + 1) th characteristic data group in the imaging resistivity array from the characteristic array without the corresponding elements and merging the elements into the (k + 1) th characteristic data group;
based on the same principle, traversing all elements in the feature data group after the corresponding elements are removed, and separating to obtain a final (k + 1) th feature data group.
According to an embodiment of the invention, for each feature data group having a fracture in the corresponding region, the downhole data processing apparatus is further configured to extract an extreme value coordinate point of each feature data group.
According to one embodiment of the invention, the system further comprises:
a surface data processing device disposed at a surface end and communicatively coupled to the downhole data processing device, wherein,
if a crack exists in the corresponding area of a characteristic data group, the ground data processing device is configured to transmit the extreme value coordinate point of the characteristic data group to the ground data processing device, and the ground data processing device is configured to determine the crack angle of the crack corresponding to the characteristic data group according to the extreme value coordinate point.
In the prior art, part of data is directly selected from collected data and transmitted to the surface, so that downhole equipment needs to transmit a large amount of data to the surface. Due to the limitations of transmission-while-drilling systems such as mud pulsers, it is difficult for surface systems to process and analyze information such as fractures from data transmitted to the surface. The stratum fracture identification method and the stratum fracture identification system provided by the invention identify the fractures underground, and transmit the characteristic information of the fractures to the ground under the condition of identifying the fractures (in practical application, the characteristic of a certain fracture can be transmitted to the ground by about 4 bytes of data), so that the information can be quickly and completely transmitted to the ground by utilizing the existing data transmission technology, which has important significance on the drilling safety and efficiency safety.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required in the description of the embodiments or the prior art:
FIG. 1 is a schematic flow chart of an implementation of a method for identifying formation fractures according to one embodiment of the present invention;
FIG. 2 is a flow diagram illustrating an implementation of generating a feature data group according to one embodiment of the invention;
FIGS. 3 and 4 are schematic diagrams of a flow chart of implementation of separating several feature data groups according to an embodiment of the present invention;
FIG. 5 is a graph of high resolution imaging resistivity data acquired in accordance with one embodiment of the invention;
FIG. 6 is a schematic representation of an image generated from various feature data populations according to one embodiment of the present invention;
FIG. 7 is a schematic representation of the imaging of the boundaries of various feature data clusters in accordance with one embodiment of the present invention;
FIG. 8 is a schematic diagram of the configuration of a formation fracture identification system according to one embodiment of the present invention;
FIG. 9 is a schematic diagram of an exemplary embodiment of a drilling system according to an embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details or with other methods described herein.
Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.
Aiming at the defects in the prior art, the invention provides a novel stratum fracture identification method and a novel stratum fracture identification system.
Fig. 1 shows a schematic implementation flow diagram of the formation fracture identification method provided by the embodiment.
As shown in fig. 1, in the formation fracture identification method provided in this embodiment, in step S101, imaging resistivity data of each sampling point is acquired along the circumferential direction and the depth direction of the well in the downhole, so as to obtain an imaging resistivity array of the region to be analyzed.
In particular, in the embodiment, the method preferably acquires the well-circumference data at preset fixed time intervals by using a high-resolution imaging resistivity measurement while drilling system. For example, the weekly well data may contain n sample points.
By selecting the depth well-circumference resistivity imaging data contained in the stratum to be analyzed, a two-dimensional array R (namely an imaging resistivity array) can be obtained. Wherein the imaging resistivity array R may be represented as:
wherein R isij(where i 1, 2.. times, m, j 1, 2.. times, n) represents imaging resistivity data at the ith depth coordinate and the jth periwell coordinate
After obtaining the imaging resistivity array of the region to be analyzed, the method separates a plurality of feature data groups according to the imaging resistivity array obtained in step S101 in step S102. Wherein different characteristic data groups preferably correspond to different possible cracks.
Specifically, fig. 2 shows a schematic flow chart of an implementation of generating a feature data group in the present embodiment.
As shown in fig. 2, in the present embodiment, the method preferably calculates an average value of the imaging resistivities of the imaging resistivity array R in step S201. For example, the method may calculate an average value of the imaging resistivities of the imaging resistivity array R in step S201 according to the following expression:
wherein R isAVGRepresenting the average imaging resistivity.
Is obtained byAverage value of imaging resistivity RAVGThe method then proceeds to step S202 where the resistivity average R is determined based on the imaging resistivity averageAVGAnd extracting a characteristic array from the imaging resistivity array R. For example, in this embodiment, for any element in the resistivity array, the method preferably determines the imaging resistivity value R corresponding to the elementijWhether or not it is less than the average value R of the imaging resistivityAVGRatio to a predetermined calculation coefficient e (e > 1) (i.e. R)AVGE). If the value is less than the threshold value, the method extracts the element and uses the element as a constituent element in the feature array U. By traversing all elements in the imaging resistivity array R, the method can also obtain a complete characteristic array U.
It should be noted that, in different embodiments of the present invention, the preset calculation coefficient e may be configured to be different reasonable values greater than 1 according to actual needs, so that the average value R of the imaging resistivity isAVGThe ratio of the imaging resistivity to a preset calculation coefficient e (e is more than 1) is less than or far less than the imaging resistivity average value RAVG。
After obtaining the feature array U, the method separates a plurality of feature data groups from the feature array U in step S203.
Specifically, as shown in fig. 3, in the present embodiment, the method preferably first selects an element from the feature array U to be placed in the first feature data group in step S301. The method may select an element from the feature array U by a random selection, and the initial state of the first feature data group is null.
Of course, in other embodiments of the present invention, the method may also select elements in other reasonable manners according to practical situations, and the present invention is not limited thereto. For example, in one embodiment of the present invention, the method may also select the first element or the last element of the feature array U.
After obtaining the temporary first feature data group, the method selects an element adjacent to the current first feature data group in the imaging resistivity array R from the feature data U and incorporates the element into the first feature data group in step S302, thereby updating the first feature data group. That is, the number of elements of the first feature data group is increased.
Based on the same principle as step S302, the method traverses all elements in the feature array U in step S303, and thus completes the update of the first feature data group, thereby obtaining the final first feature data group U1。
In this embodiment, the elements in the first feature data group obtained in the above steps S301 to S303 are successively adjacent in the imaging resistivity array R, and therefore, these elements are also in the same crack region.
If a plurality of cracks are contained in the region to be analyzed, the first feature data group does not contain all the elements in the feature array U. At this time, the method determines the feature data groups corresponding to other fractures in the manner shown in fig. 4.
Specifically, as shown in fig. 4, assuming that k feature data groups (corresponding to k cracks, where k is a natural number) are determined, the method will remove elements included in the k feature data groups from the feature array U in step S401.
After the elements included in the k feature data groups are removed, in step S402, an element is selected from the feature arrays from which the corresponding elements are removed and is placed in the (k + 1) th feature data group. The initial state of the (k + 1) th feature data group is null, and after the selected element is placed, the (k + 1) th feature data group also includes an element.
Subsequently, in step S403, the method selects an element adjacent to the (k + 1) th feature data group in the imaging resistivity array R from the feature array from which the corresponding element is removed, and incorporates the element into the (k + 1) th feature data group, so as to update the (k + 1) th feature data group. Based on the same principle of step S403, the method traverses all elements in the feature array U from which corresponding elements are removed in step S404, thereby completing the update of the (k + 1) th feature data group and obtaining the final (k + 1) th feature data group Uk+1。
In this embodiment, the specific implementation principle and implementation process of the steps S402 to S404 are similar to those of the steps S301 to S303, and therefore specific details of the steps S402 to S404 are not described herein again.
Obtaining the k +1 th characteristic data group Uk+1Then, in step S405, the method removes elements included in the obtained k +1 feature data groups from the feature array U, and in step S406, determines whether there are still unremoved elements in the feature array at this time.
If there are still unremoved elements in the feature array at this time, in step S407, the method adds 1 to the value k in step S401, and returns to step S401 and re-executes step S401 until the obtained feature data group includes all the elements in the feature array U.
For example, assuming that the first feature data group is determined (i.e. k takes a value of 1), the method may remove elements included in the first feature data group from the feature array U in step S401. Subsequently, in step S402, an element is selected from the feature array without the corresponding element and placed in a second feature array, where the second feature array only includes the element selected in step S402.
In step S403, the method selects elements adjacent to the second feature data group in the imaging resistivity array R from the feature array from which the corresponding elements are removed, and merges the elements into the second feature data group, so as to update the second feature data group.
Based on the same principle of step S403, the method traverses all elements in the feature array U from which corresponding elements are removed in step S404, thereby completing updating of the second feature data group and obtaining the final second feature data group U2。
Therefore, the method realizes the separation of the characteristic arrays according to the cracks, thereby obtaining the characteristic data groups corresponding to different cracks.
Of course, in other embodiments of the present invention, the method may also use other association methods to separate the feature data groups corresponding to different cracks from the feature data group according to actual needs, and the present invention is not limited thereto.
As shown in fig. 1 again, in this embodiment, after obtaining the feature data groups, the method determines the area and the maximum length of each obtained feature data group in step S103.
Specifically, in this embodiment, for any obtained feature data group, the method may preferably determine the area of the feature data group by counting the number of elements included in the feature data group. Meanwhile, the method can respectively calculate the interval length between any two elements in the elements contained in the characteristic data group, and the maximum value of all the obtained interval lengths is taken as the maximum length of the characteristic data group.
Of course, in other embodiments of the present invention, the method may also determine the area and/or the maximum length of each feature data group in other reasonable manners according to actual needs, and the present invention is not limited thereto.
In this embodiment, for any feature data group, after obtaining the area and the maximum length of the feature data group, the method calculates a ratio of the area to the maximum length of the feature data group in step S104, and determines whether there is a crack in a corresponding region of the feature data group according to the ratio in step S105. If the ratio is smaller than the preset ratio threshold, the method judges that the region corresponding to the characteristic data group has cracks. If the ratio is greater than the predetermined ratio threshold, the method determines that holes exist in the region corresponding to the feature data group.
It should be noted that the specific value of the preset proportion threshold may be configured to be different reasonable values according to actual needs, and the specific value of the preset proportion threshold is not limited in the present invention.
For example, FIG. 5 shows a high resolution imaging resistivity data map with information on cracks, holes, etc. stored in memory in a two dimensional array (i.e., imaging resistivity array). In this data, the data of two dimensions of each element respectively represents the peri-well coordinate and the depth coordinate thereof, and the size of the data of each element itself is preferably represented by gray scale. Wherein, the larger the resistivity is, the lighter the gray scale of the element is; the smaller the resistivity, the deeper the grey scale of the element. Dark black thin bands generally indicate the presence of cracks and dark black patches generally indicate the presence of holes.
With respect to the imaging resistivity data map shown in fig. 5, through the steps S101 to S105, the method can determine that the imaging schematic map generated according to each feature data group is shown in fig. 6. As can be seen from fig. 6, crack and hole information can already be characterized from the individual characteristic data groups. Fig. 7 is a schematic imaging diagram showing the boundaries of the feature data groups, and it can be seen from fig. 7 that the boundary information of the crack and the hole can be extracted according to the feature data groups.
As shown in fig. 1, in this embodiment, after determining whether the region to be analyzed is cracked, optionally, in step S106, for each feature data group in which a crack exists in the corresponding region, the method extracts an extreme value coordinate point of each feature data group. The above-mentioned extreme value coordinate points preferably include a total of 4 extreme value point coordinate points in the depth direction and perpendicular to the depth direction.
In this embodiment, optionally, the method further determines, at the ground end in step S107, a crack angle of the crack corresponding to the corresponding characteristic data group according to the extreme value coordinate point obtained in step S106. Specifically, the method may determine the fracture angle in step S107 according to the following expression:
θ＝arctan[(Ymax-Ymin)×v/(Xmax-Xmin)](3)
wherein θ represents a crack angle, YmaxAnd YminA maximum value and a minimum value of coordinates in a depth direction of the characteristic data group, v represents a drilling speed, and XmaxAnd XminThe maximum value and the minimum value of the coordinates perpendicular to the depth direction of the feature data group are respectively represented.
In this embodiment, after the crack is determined, according to actual needs, the crack depth of the crack may also be determined by the method. Specifically, in this embodiment, the method preferably extracts a sampling time at which imaging resistivity data included in the feature data group corresponding to the fracture is acquired, and determines the fracture depth of the fracture according to the sampling time based on known well depths corresponding to different times.
In this embodiment, the above steps S101 to S106 may be preferably configured in corresponding downhole equipment to be implemented by the downhole equipment, and the above step S107 may be preferably configured in surface equipment to be implemented by the surface equipment. Because the downhole equipment transmits fracture characteristic data (such as a characteristic data group corresponding to a fracture and an extreme value coordinate point of the characteristic data group), the data volume of the data is obviously much smaller than that of original data (such as an imaging resistivity array), so that the data can be transmitted by using the existing data transmission mode, and the data processing efficiency is improved.
The invention also provides a stratum crack identification system, wherein fig. 8 shows a structural schematic diagram of the system in the embodiment.
As shown in FIG. 8, in this embodiment, the formation fracture identification system preferably includes an imaging resistivity acquisition device 801 and a downhole data processing device 802. The imaging resistivity acquisition device 801 is used for acquiring imaging resistivity data of each sampling point along the well circumferential direction and the depth direction, so that an imaging resistivity array of an area to be analyzed is obtained.
The downhole data processing device 802 is connected to the imaging resistivity acquisition device 801, and can separate a plurality of characteristic data groups according to the imaging resistivity array transmitted by the imaging resistivity acquisition device 801. Wherein different characteristic data groups correspond to different possible cracks. For each feature data group, the downhole data processing device 802 further determines the area and the maximum length thereof, calculates a ratio of the area to the maximum length, and determines whether a crack or a karst cave exists in a corresponding region of each feature data group according to the ratio.
Optionally, in this embodiment, the formation fracture identification system may further include a surface data processing device 803 according to actual needs. A surface data processing device 803 is disposed at the surface end and is communicatively coupled to the downhole data processing device 802. If there is a crack in the area corresponding to a feature data group, the ground data processing apparatus will transmit the extreme value coordinate point of the feature data group to the ground data processing apparatus, and the ground data processing apparatus 803 will determine the crack angle of the crack corresponding to the feature data group according to the received extreme value coordinate point.
In this embodiment, after determining the crack, the ground data processing device 803 may also determine the crack depth of the crack according to actual needs. Specifically, in this embodiment, the surface data processing device 803 preferably extracts a sampling time at which imaging resistivity data included in the feature data group corresponding to the fracture is collected, and determines the fracture depth of the fracture according to the sampling time based on known well depths corresponding to different times.
In this embodiment, the principle and process of the imaging resistivity acquisition device 801, the downhole data processing device 802, and the surface data processing device 803 for realizing their respective functions are similar to those disclosed in the above steps S101 to S107, and therefore detailed descriptions of the imaging resistivity acquisition device 801, the downhole data processing device 802, and the surface data processing device 803 are omitted here.
The downhole data processing device 802 may preferably include: the device comprises an underground data processing module and an underground data storage module. The downhole data processing module is connected with the imaging resistivity acquisition device 801 to receive the imaging resistivity array transmitted by the imaging resistivity acquisition device 801 and store the data into the downhole data storage module. For example, the downhole data processing module and the imaging resistivity acquisition device 801 may be in data communication using a serial bus interface. Of course, in other embodiments of the invention, the data communication between the downhole data processing module and the imaging resistivity acquisition device 801 may be in other reasonable manners.
The underground data processing module can extract a section of imaging data from the underground data storage module according to a preset flow and analyze and process the imaging data, so that whether the stratum corresponding to the section of imaging data contains cracks or holes or not is identified.
Fig. 9 illustrates an exemplary embodiment of a drilling system. As shown in fig. 9, the scheme includes: the system comprises a drilling surface system 901, a surface data receiving and processing system 902, a while-drilling transmission short joint 903, a while-drilling resistivity imaging acquisition short joint 904 and a drill bit 905. The transmission while drilling nipple 903 can select a mud pulse transmission system, an electromagnetic transmission system and the like according to actual needs, and only needs to transmit a bottom hole signal to the ground. In addition, the positions of the transmission while drilling nipple 903 and the resistivity imaging acquisition while drilling nipple 904 can be exchanged and recombined up and down.
In this embodiment, the imaging resistivity acquisition device 801 may be integrated in the logging-while-drilling resistivity imaging acquisition nipple 904, and the downhole data processing device 802 may be integrated in the logging-while-drilling transmission nipple 903. In operation, both the imaging resistivity acquisition device 801 and the downhole data processing device 802 are downhole. The surface data processing device 803 may be integrated into the surface data receiving and processing system 902, and during operation, the surface data processing device 803 is disposed at the surface end.
In the prior art, part of data is directly selected from collected data and transmitted to the surface, so that downhole equipment needs to transmit a large amount of data to the surface. Due to the limitations of transmission-while-drilling systems such as mud pulsers, it is difficult for surface systems to process and analyze information such as fractures from data transmitted to the surface. The stratum fracture identification method and the stratum fracture identification system provided by the invention identify the fractures underground, and transmit the characteristic information of the fractures to the ground under the condition of identifying the fractures (in practical application, the characteristic of a certain fracture can be transmitted to the ground by about 4 bytes of data), so that the information can be quickly and completely transmitted to the ground by utilizing the existing data transmission technology, which has important significance on the drilling safety and efficiency safety.
It is to be understood that the disclosed embodiments of the invention are not limited to the particular structures or process steps disclosed herein, but extend to equivalents thereof as would be understood by those skilled in the relevant art. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.
While the above examples are illustrative of the principles of the present invention in one or more applications, it will be apparent to those of ordinary skill in the art that various changes in form, usage and details of implementation can be made without departing from the principles and concepts of the invention. Accordingly, the invention is defined by the appended claims.
Claims (15)
1. A formation fracture identification method, characterized by comprising:
acquiring imaging resistivity data of each sampling point along the circumferential direction and the depth direction of a well under the well to obtain an imaging resistivity array of an area to be analyzed;
separating according to the imaging resistivity array to obtain a plurality of characteristic data groups, wherein different characteristic data groups correspond to different cracks which may exist;
and step three, respectively determining the area and the maximum length of each characteristic data group, calculating the ratio of the area to the maximum length, and respectively determining whether cracks or holes exist in the corresponding area of each characteristic data group according to the ratio.
2. The method of claim 1, wherein step two comprises:
step a, calculating an imaging resistivity average value of the imaging resistivity array;
b, extracting a characteristic array from the imaging resistivity array according to the imaging resistivity average value;
and c, separating the characteristic array to obtain a plurality of characteristic data groups.
3. The method according to claim 2, wherein in the step b, for any element in the imaging resistivity array, it is determined whether the imaging resistivity value corresponding to the element is smaller than the ratio of the imaging resistivity average value to a preset calculation coefficient, and if so, the element is extracted and used as a constituent element in the feature array, wherein the value of the preset calculation coefficient is greater than 1.
4. A method according to claim 2 or 3, wherein said step c comprises:
c1, selecting an element from the characteristic array and placing the element into a first characteristic data group;
c2, selecting elements adjacent to a first characteristic data group in the imaging resistivity array from the characteristic array and merging the elements into the first characteristic data group;
and c3, traversing all elements in the feature array based on the step c2 to obtain a final first feature data group.
5. The method of claim 4, wherein step c further comprises:
c4, removing elements contained in the obtained k characteristic data groups from the characteristic array, and selecting an element from the characteristic array after the corresponding element is removed again to be placed in the (k + 1) th characteristic data group;
c5, selecting elements adjacent to the (k + 1) th characteristic data group in the imaging resistivity array from the characteristic array after the corresponding elements are removed, and merging the elements into the (k + 1) th characteristic data group;
step c6, based on the step c5, traversing all elements in the feature data group after the corresponding elements are removed, and separating to obtain a final (k + 1) th feature data group;
and c7, removing elements contained in the obtained k +1 feature data groups from the feature array U, judging whether the elements which are not removed still exist in the feature array, if so, adding 1 to the value of k, and executing the steps c4 to c7 again.
6. The method according to any one of claims 1 to 5, wherein in the third step, for any one of the feature data groups, the area of the feature data group is determined by counting the number of elements included in the feature data group.
7. The method according to any one of claims 1 to 6, wherein in the third step, for any feature data group, if the ratio of the area to the maximum length is smaller than a preset ratio threshold, it is determined that a crack exists in the region corresponding to the feature data group.
8. The method of any one of claims 1 to 7, further comprising:
extracting extreme value coordinate points of each characteristic data group for each characteristic data group with cracks in the corresponding region under the well;
and fifthly, transmitting the extreme value coordinate point to a ground end, and determining the crack angle of the crack corresponding to the characteristic data group at the ground end according to the extreme value coordinate point of the corresponding characteristic data group.
9. The method of claim 8, wherein the fracture angle is determined according to the expression:
θ＝arctan[(Ymax-Ymin)×v/(Xmax-Xmin)]
wherein θ represents a crack angle, YmaxAnd YminA maximum value and a minimum value of coordinates in a depth direction of the characteristic data group, v represents a drilling speed, and XmaxAnd XminSit perpendicular to depth direction respectively representing feature data groupsA scalar maximum value and a coordinate minimum value.
10. A formation fracture identification system, the system comprising:
the imaging resistivity acquisition device is used for acquiring imaging resistivity data of each sampling point along the circumferential direction and the depth direction of the well under the well to obtain an imaging resistivity array of an area to be analyzed;
and the underground data processing device is connected with the imaging resistivity acquisition device and is used for separating and obtaining a plurality of characteristic data groups according to the imaging resistivity array, wherein different characteristic data groups correspond to different cracks which may exist, the underground data processing device is also used for respectively determining the area and the maximum length of each characteristic data group, calculating the ratio of the area to the maximum length, and respectively determining whether cracks or holes exist in the corresponding area of each characteristic data group according to the ratio.
11. The system of claim 10, wherein the downhole data processing device is configured to first calculate an average imaging resistivity value for the imaging resistivity array, extract a feature array from the imaging resistivity array based on the average imaging resistivity value, and then separate feature data groups from the feature array.
12. The system of claim 11, wherein the downhole data processing device is configured to first select an element from the feature array to be placed in a first feature data group, then select an element from the feature array that is adjacent to the first feature data group in the imaging resistivity array and merge into the first feature data group, and then traverse all elements in the feature array on the same principle to obtain a final first feature data group.
13. The system of claim 12, wherein the downhole data processing device is further configured to:
removing elements contained in the obtained k characteristic data groups from the characteristic data, and selecting an element from the characteristic data from which the corresponding element is removed again to place the element in a (k + 1) th characteristic data group;
selecting elements adjacent to the (k + 1) th characteristic data group in the imaging resistivity array from the characteristic array without the corresponding elements and merging the elements into the (k + 1) th characteristic data group;
based on the same principle, traversing all elements in the feature data group after the corresponding elements are removed, and separating to obtain a final (k + 1) th feature data group.
14. The system of any one of claims 10 to 13, wherein for each feature data group having a fracture in a corresponding region, the downhole data processing device is further configured to extract an extremum coordinate point for each feature data group.
15. The system of claim 14, wherein the system further comprises:
a surface data processing device disposed at a surface end and communicatively coupled to the downhole data processing device, wherein,
if a crack exists in the corresponding area of a characteristic data group, the ground data processing device is configured to transmit the extreme value coordinate point of the characteristic data group to the ground data processing device, and the ground data processing device is configured to determine the crack angle of the crack corresponding to the characteristic data group according to the extreme value coordinate point.
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