Anisotropic field quality control method and apparatus

Abstract

The present application relates to the technical field of oil exploration, and particularly relates to an anisotropic field quality control method and device. The present application performs quality control on an anisotropic field based on well-seismic combination of three-component induction logging and partial azimuth seismic data, combines micro and macro, calibrates seismic velocity and logging velocity, uses OVT domain azimuth processing technology and three-component induction logging technology, and cooperatively completes quality control on an initial anisotropic field. On the basis of quality control, abnormal wells reducing the precision of an anisotropic model in a development area are identified and removed, and then an anisotropic model is re-established and iteratively controlled, so that the fidelity and precision of the controlled anisotropic field are comprehensively improved, the anisotropic field in the development research area is more in line with regulations and has higher precision, and is better related to seismic imaging scale and better consistent with anisotropic rules obtained by measuring reservoir sand body scale.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration technology, and in particular to an anisotropic field quality control method and apparatus. Background Technology

[0002] Currently, in the discovered large and medium-sized oil and gas fields, thin interbedded sandstone and mudstone reservoirs and fractured reservoirs account for approximately 30% according to incomplete statistics. These reservoirs represent an important area for effectively supplementing and replacing conventionally developed oil-bearing reservoir types. However, these reservoirs often exhibit strong anisotropy on a macroscopic scale. Accurate measurement and description of this anisotropy is crucial for improving development efficiency. Similarly, accurately describing formation anisotropy can improve the accuracy of seismic data anisotropic depth migration and enhance the overall exploration success rate. With the continuous development of oil and gas fields, especially the increasing demand for efficient development of unconventional reservoirs, thin interbedded sandstone and mudstone reservoirs and fractured reservoirs with complex geological structures often exhibit significant anisotropy due to their unique structural characteristics. This anisotropy is not only observed at the microscopic scale but also at the macroscopic scale, where longitudinal and transverse velocity anisotropy and longitudinal and transverse resistivity anisotropy can be observed. In developing unconventional reservoirs with poor connectivity, accurate selection of enrichment targets, precise seismic imaging, accurate directional drilling, and effective fracturing all determine whether the controlled area of ​​horizontal wells / well groups can be developed efficiently. Anisotropic fields are a crucial foundational data model, directly determining the accuracy of anisotropic depth migration results from seismic data. They also serve as important reference data for integrated geological and engineering modeling and the formulation of various engineering schemes. However, quality control methods for anisotropic fields are very limited, hindering the accurate tapping of the data potential of anisotropic reservoir development areas. There is an urgent need for a multi-method collaborative quality control approach to improve the accuracy of anisotropic fields and ensure their physical conformity. Summary of the Invention

[0003] To address the above problems, the present invention provides an anisotropic field quality control method and apparatus.

[0004] In a first aspect, the present invention provides a method for quality control of anisotropic fields, the method comprising:

[0005] Quality control data were collected for the target layer of the area to be studied;

[0006] The seismic data in the quality control data is compared with the anisotropic field M. anisotropy1 Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth;

[0007] A resistivity anisotropic field was established using three-component induction logging.

[0008] When the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold, the first quality control is passed;

[0009] Core samples were collected from the target layer, and the anisotropy of the core samples was measured in the laboratory. The anisotropy parameter data obtained from the laboratory measurements were used to analyze the quality-controlled anisotropic field M. anisotropy1 M is obtained by calibration update anisotropy2 ;

[0010] The updated anisotropic field M was calibrated using the maximum velocity difference field quality control in each orientation. anisotropy2 And its correlation; when the correlation is greater than the second correlation threshold, the second quality control is passed.

[0011] Quality control of the anisotropic field M is achieved by calibrating the resistivity anisotropic field. anisotropy2 When the correlation is greater than the third correlation threshold, the third quality control is passed;

[0012] When the first, second, and third quality controls pass simultaneously, the final anisotropic field is output.

[0013] Furthermore, quality control data is collected, including:

[0014] Determine the coordinates of the four points in the quality control study area, collect all the target layer drilling and complete logging curve data in the study area, collect all the seismic data of different times and different observation systems in the four coordinates of the study area, collect the velocity model and stratigraphic interpretation results corresponding to each set of seismic data, and collect the core data of the target layer of all exploration and evaluation wells in the study area, especially in the horizontal well platform area.

[0015] Furthermore, the seismic data in the quality control data is compared with the anisotropic field M. anisotropy1 Matching, including:

[0016] Based on the criteria of minimum area, latest acquisition, maximum offset, maximum coverage times, and maximum aspect ratio of the target layer, three-dimensional seismic data are selected from the quality control data. The velocity model is used to complete the time-depth conversion, so that the seismic processing results and pre-stack trace collections are converted to the depth domain.

[0017] Using four-point coordinates, the selected seismic data and anisotropic field M are combined. anisotropy1 Match the data, set them to the same grid, and remove the extended data outside the study area after extending them by a maximum offset in four directions.

[0018] Furthermore, the time-depth conversion objects include processed seismic data, pre-stack gathers, and stratigraphic interpretation results.

[0019] Furthermore, the pre-stack gather OVT five-dimensional data is regularized and divided into several groups of azimuth sectors, including:

[0020] Seismic data and anisotropic field M anisotropy1 Five-dimensional data regularization is performed on the pre-stack CMP gathers after matching and mesh filtering;

[0021] The pre-stack CMP gathers after five-dimensional data regularization are sorted in the OVT domain, and the sorted trace heads are azimuth and offset.

[0022] The initial azimuth was determined according to the structural distribution pattern. The 360-degree azimuth seismic data was divided into several azimuth sectors on an average basis, and the pre-stack seismic data within the azimuth range of each sector were selected.

[0023] Furthermore, the maximum velocity difference field in each azimuth is established, including:

[0024] Multiple wave suppression processes are applied to gathers within several azimuth sectors.

[0025] The CMP gather obtained by wave suppression is used to generate a gather for velocity analysis and an autocorrelation energy spectrum while retaining all offset information.

[0026] Automatic velocity analysis is performed by grouping velocity gathers and energy spectra in different azimuths to form several azimuths. The azimuths are sorted to determine the maximum and minimum velocities of each azimuth. The absolute value of the difference between the maximum and minimum velocities at the same depth in the target layer is calculated to form the maximum velocity difference field of each azimuth.

[0027] Furthermore, a resistivity anisotropic field is established through three-component induction logging, including:

[0028] Three-component induction logging was carried out on wells in the study area that met the open-hole logging conditions.

[0029] For three-component induction logging data, nine magnetic components are measured in vertical, inclined, or horizontal sections through three transmitting coils and three receiving coils. Anisotropic forward modeling is completed by applying electromagnetic excitation to anisotropic formations and solving the three-dimensional response of the formations using Maxwell's equations. The formation response is then solved using the forward modeling results and the staggered grid finite difference method or finite element method. The residuals between the calculated results and the actual measurement results are calculated, and the parameters are adjusted and updated until the residuals are minimized or the a priori criteria are met. Nine conductivity components are obtained through inversion, and finally, the different resistivities in three directions at a certain observation point are determined.

[0030] Using the results, a target layer resistivity anisotropic field is established in the same anisotropic parameter direction as the controlled anisotropic field.

[0031] Furthermore, it also includes:

[0032] If the first, second, or third quality control fails, M will be... anisotropy1 Wells that failed quality control were removed from the well information set used in the modeling process and were no longer included in the anisotropic modeling. The remaining wells were used to rebuild the initial anisotropic model M. anisotropy1 And re-perform quality control.

[0033] In a second aspect, the present invention provides an anisotropic field quality control device, comprising: a first quality control unit, a second quality control unit, a third quality control unit, and an output unit;

[0034] The first quality control unit is used to collect quality control data for the target layer of the area to be studied.

[0035] The first quality control unit is also used to combine the seismic data in the quality control data with the anisotropic field M. anisotropy1 Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth;

[0036] The first quality control unit is also used to establish a resistivity anisotropic field through three-component induction logging;

[0037] The first quality control unit is also used to ensure that the first quality control passes when the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold.

[0038] The second quality control unit is used to collect core samples from the target layer and measure the anisotropy of the core samples in the laboratory; the anisotropy parameter data obtained from the laboratory measurements are used to control the anisotropic field M. anisotropy1 M is obtained by calibration update anisotropy2 ;

[0039] The second quality control unit is also used to calibrate the updated anisotropic field M using the maximum velocity difference field in each azimuth. anisotropy2 And its correlation; when the correlation is greater than the second correlation threshold, the second quality control is passed.

[0040] The third quality control unit is used to calibrate the quality control anisotropic field M using a resistivity anisotropic field. anisotropy2 When the correlation is greater than the third correlation threshold, the third quality control is passed;

[0041] The output unit is used to output the final anisotropic field after the first, second, and third quality controls have passed simultaneously.

[0042] Thirdly, the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0043] Memory, which stores computer programs;

[0044] When a processor executes a computer program stored in memory, it implements the anisotropic field quality control method described above.

[0045] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described anisotropic field quality control method.

[0046] The present invention has at least the following beneficial effects:

[0047] This invention utilizes a combination of three-component induction logging and partial azimuth seismic data for quality control of anisotropic fields. By combining microscopic and macroscopic data and cross-calibrating seismic and logging velocities, and employing OVT domain azimuth processing technology and three-component induction logging technology, the initial anisotropic field is collaboratively controlled. Based on this quality control, abnormal wells that reduce the accuracy of the anisotropic model in the development area are identified, removed, and then re-established and iteratively quality controlled. This comprehensively improves the fidelity and accuracy of the controlled anisotropic field, making the anisotropic field physics in the development and research area more compliant and accurate. It also shows better correlation with the seismic imaging scale and better agreement with the anisotropic laws obtained from well logging reservoir sand body scale measurements.

[0048] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and the drawings. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart of the quality control method according to an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the quality control device structure according to an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of the electronic device structure;

[0053] Figure 4 This is a flowchart illustrating the quality control methods. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] This invention utilizes a combination of three-component induction logging and partial azimuth seismic data for quality control of anisotropic fields. Through implementation and development, this invention enables microscopic calibration and macroscopic quality control of anisotropic parameter fields. By combining microscopic and macroscopic methods, and cross-calibrating seismic and logging velocities, this invention leverages OVT domain azimuth processing technology and three-component induction logging technology to collaboratively complete quality control of the initial anisotropic field. Based on this quality control, abnormal wells that reduce the accuracy of the anisotropic model in the development area are identified, removed, and then the anisotropic model is re-established and iteratively quality controlled. This results in a more compliant and accurate anisotropic field physics within the development and research area, exhibiting better correlation with seismic imaging scales and a better match with the anisotropic patterns obtained from well logging reservoir sand body scale measurements.

[0056] like Figure 1 As shown, the present invention provides a method for quality control of anisotropic fields, the method comprising:

[0057] S101, Collect quality control data for the target layer of the area to be studied;

[0058] S102, combining the seismic data in the quality control data with the anisotropic field M anisotropy1 Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth;

[0059] S103, a resistivity anisotropic field is established through three-component induction logging;

[0060] S104, when the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold, the first quality control is passed;

[0061] S105, core samples were collected from the target layer, and the anisotropy of the core samples was measured in the laboratory; the anisotropy parameter data obtained from the laboratory measurements were used to analyze the quality-controlled anisotropic field M. anisotropy1 M is obtained by calibration update anisotropy2 ;

[0062] S106, using the maximum velocity difference field quality control of each orientation to calibrate and update the anisotropic field M. anisotropy2 And its correlation; when the correlation is greater than the second correlation threshold, the second quality control is passed.

[0063] S107, quality control of anisotropic field M by resistivity anisotropic field calibration anisotropy2 When the correlation is greater than the third correlation threshold, the third quality control is passed;

[0064] S108 outputs the final anisotropic field after the first, second, and third quality controls pass simultaneously.

[0065] The specific implementation details are as follows:

[0066] Step 1: Collect and organize all basic data required for quality control processing, including determining the coordinates of the four points in the quality control study area, collecting all accurate and complete well logging curves of the target layer encountered in the study area, collecting all seismic data from different times and different observation systems within the four-point coordinates of the study area, collecting the velocity model and stratigraphic interpretation results (time domain) corresponding to each set of seismic data, and collecting core data of the target layer from all exploration and appraisal wells in the study area, especially in the horizontal well platform area. If there is no core of the target layer in the entire study area, core sampling will be carried out during the drilling of the latest target layer encountered in the area. The top and bottom depths of the core sampling should fully cover the target layer.

[0067] Step 2: Conduct three-component induction logging operations on wells within the study area that meet the open-hole logging conditions, and complete logging operations on as many vertical, deviated, and horizontal wells as possible in the target formation.

[0068] Step 3: Optimize the seismic data volume collected in Step 1. Based on criteria such as minimum area, latest acquisition, maximum offset, maximum coverage count, and maximum aspect ratio of the target layer, select a set of 3D seismic data. Perform time-depth conversion using a velocity model. This conversion includes processed seismic data, pre-stack gathers, and layer interpretation results, transforming the processed seismic data and pre-stack gathers into the depth domain. Collect the initial anisotropic parameter field M for subsequent quality control. anisotropy1 Using four-point coordinates, the selected seismic data and anisotropic field (M) are combined. anisotropy1 Matching, setting the same grid, and then discarding the extended study area outside the data after extending by a maximum offset in four directions.

[0069] Step 4: Perform five-dimensional data regularization on the pre-stack CMP gather after mesh filtering in Step 3, ensuring that the minimum number of coverage times at the shallowest depth of the target layer is no less than 360.

[0070] Step 5: Perform OVT domain data sorting on the pre-stack CMP gather after the five-dimensional data regularization in Step 4, and sort the gather heads by azimuth and offset.

[0071] Step 6: Under the guidance of geological understanding, the starting azimuth of the CMP gathers extracted from the OVT domain obtained in Step 5 is determined according to the structural distribution pattern. The 360-degree azimuth seismic data is divided into 12 azimuth sectors on average. The pre-stack seismic data within the azimuth range of each sector is selected, and each sector has no less than 30 effective coverages.

[0072] Step 7: Perform multiple wave suppression processing on the gathers in the 12 azimuth sectors divided in Step 6.

[0073] Step 8: Generate velocity analysis gathers and autocorrelation energy spectra from the 12 sets of CMP gathers obtained in Step 7. All offset information must be retained in this step.

[0074] Step 9: Using the velocity analysis gathers and energy spectra obtained in Step 8, complete 12 sets of automatic velocity analyses to form Velocity data. 方位1 To Vel 方位12 First, for Vel 方位1 To Vel 方位12 Sort the data to determine the velocity values ​​Vel at the locations with the highest and lowest velocities. max方位m To Vel min方位n Calculate the same depth Vel of the target layer max方位m To Vel min方位n The absolute value of the difference forms the maximum velocity difference field in each direction.

[0075] Step 10: Using the cored sample from Step 1, measure the anisotropy parameters of the target layer rock sample in an acoustic laboratory. Use the anisotropy parameter data measured in the laboratory to analyze the quality-controlled anisotropy field M. anisotropy1 M is obtained by calibration update anisotropy2 .

[0076] Step 11: Using the depth domain layer interpretation results obtained in Step 3, select a segment of the target layer to draw M. anisotropy2 The planar property map is used to determine the correlation between the updated anisotropic field and the velocity difference field in different orientations obtained in step 9. The cross-correlation is calculated within the same physical range. If the cross-correlation is less than 0.8, the quality control fails and the process cannot proceed to the next step. If the cross-correlation is greater than or equal to 80%, the quality control passes and the process proceeds to the next step.

[0077] Step 12: The three-component induction logging data obtained in Step 2 contains nine magnetic components measured by three transmitting coils and three receiving coils in vertical, inclined, or horizontal sections. Anisotropic forward modeling is completed by applying electromagnetic excitation to the anisotropic formation and solving the three-dimensional response of the formation using Maxwell's equations. The formation response is then solved using the forward modeling results and algorithms such as staggered grid finite difference method and finite element method. The residuals between the calculated results and the actual measurement results are calculated, and the parameters are adjusted and updated until the residuals are minimized or the a priori criteria are met. This allows the nine conductivity components to be inverted, and the different resistivities in three directions at a certain observation point are finally determined. The results are used to establish an anisotropic resistivity field of the target layer in the same anisotropic parameter directions as the controlled anisotropic field.

[0078] Step 13: Use the resistivity anisotropy field obtained in Step 12 to calibrate the quality control anisotropy field M. anisotropy2 If the correlation is greater than 90% (multiple wells), the quality control is passed; if the correlation is less than or equal to 90%, the quality control is failed. In this case, it is necessary to analyze and record the well information that does not meet the requirements in the low correlation area.

[0079] Step 14: If the correlation between the maximum velocity difference field obtained in step 9 and the anisotropic field of the three-component induced resistivity obtained in step 12 is greater than 75%, the quality control is passed; if it is less than or equal to 75%, the quality control is failed. At this time, it is necessary to analyze and record the well information that does not conform to the low correlation area.

[0080] Step 15: Compare the areas that failed quality control in Steps 13 and 14. If there are wells that failed all quality control checks, then M... anisotropy1 Wells removed from the well information set used in the modeling process will no longer participate in the anisotropic modeling. The remaining wells will be used to re-establish the initial anisotropic model M. anisotropy1 .

[0081] Step 16: Re-establish the anisotropic model M using the information from the abnormal wells identified in Step 15. anisotropy1 Repeat steps 9 to 14 to complete all quality control processes until the quality control requirements are met, and output the final anisotropic model.

[0082] like Figure 2 As shown, the present invention provides an anisotropic field quality control device, comprising: a first quality control unit 201, a second quality control unit 202, a third quality control unit 203, and an output unit 204;

[0083] The first quality control unit 201 is used to collect quality control data for the target layer of the area to be studied.

[0084] The first quality control unit 201 is also used to combine the seismic data in the quality control data with the anisotropic field M. anisotropy1Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth;

[0085] The first quality control unit 201 is also used to establish a resistivity anisotropic field through three-component induction logging;

[0086] The first quality control unit 201 is also used to ensure that the first quality control passes when the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold.

[0087] The second quality control unit 202 is used to collect core samples from the target layer and measure the anisotropy of the core samples in the laboratory; the anisotropy parameter data obtained from the laboratory measurement are used to control the anisotropic field M. anisotropy1 M is obtained by calibration update anisotropy2 ;

[0088] The second quality control unit 202 is also used to calibrate the updated anisotropic field M using the maximum velocity difference field in each azimuth. anisotropy2 And its correlation; when the correlation is greater than the second correlation threshold, the second quality control is passed.

[0089] The third quality control unit 203 is used to calibrate the quality control anisotropic field M through the resistivity anisotropic field. anisotropy2 When the correlation is greater than the third correlation threshold, the third quality control is passed;

[0090] The output unit 204 is used to output the final anisotropic field after the first quality control, the second quality control and the third quality control have passed simultaneously.

[0091] like Figure 3 As shown, the present invention provides an electronic device, including a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302 and the memory 303 communicate with each other through the communication bus 304;

[0092] Memory 303 stores computer programs;

[0093] The processor 301 implements the above method when executing a computer program stored in the memory 303.

[0094] The present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0095] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0096] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0097] To enable those skilled in the art to better understand the present invention, the principles of the present invention are explained below in conjunction with the accompanying drawings:

[0098] Extensive measurements and experience have shown that there is a certain statistical correlation between longitudinal wave velocity and resistivity, V p Let ρ be the longitudinal wave velocity, ρ be the resistivity of the propagation medium, and H be the burial depth. Then, the following relationship exists between resistivity and longitudinal wave velocity:

[0099]

[0100] or

[0101] V p =2×10 3 H a ρ b (2)

[0102] In equations (1) and (2): the unit of resistivity ρ is Ω·m; the unit of burial depth is m; the unit of velocity is m / s; and a and b are empirical constants.

[0103] In anisotropic pre-stack depth migration of seismic data, the anisotropic parameter field is an important fundamental data, usually obtained using well-controlled constrained modeling techniques. Currently, there is limited research on quality control of the anisotropic field used for development and research. However, the key to correct and feasible quality control processing lies in determining the reference standard of the controlled object (data), whether the reference standard is physically compliant, and how to correct the controlled data to improve accuracy after quality control feedback. The core idea of ​​this invention is to use the seismic anisotropic field as the initial model and the object of quality control. First, calibration is performed using microscale reference samples guided by core laboratory measurements. After this preprocessing, the quality control process begins. Azimuth velocity analysis is used to examine whether there are strong azimuth velocity differences in the target layer. Correspondences are established and compared. In this quality control step, anomaly zones and anomaly well information are also identified. Using three-component induction logging data, nine magnetic components are measured in vertical, inclined, or horizontal sections through three transmitting and three receiving coils. Anisotropic forward modeling is completed by applying electromagnetic excitation to the anisotropic formation and solving for the three-dimensional response of the formation using Maxwell's equations. Then, the formation response is solved using the forward modeling results and algorithms (staggered mesh finite difference method, finite element method, etc.). The calculated results are then compared with the actual measurement results. If the error is found, the parameters are adjusted and updated until the residual is minimized or the prior standard is met. This allows for the inversion of the nine conductivity components, ultimately determining the different resistivities in three directions at a given observation point. In highly anisotropic formations, velocity anisotropy is quality controlled using resistivity anisotropy. Similarly, in this quality control step, abnormal areas and abnormal well information must be identified. Finally, through comparative analysis, if the same abnormal wells exist in each quality control step, these wells must have inherent problems or not conform to the actual underground structural trend. At this point, we return to the initial anisotropic field establishment process, remove the abnormal wells from the well control field establishment data, and complete the anisotropic field establishment. If the quality control passes, the anisotropic field established after removing the abnormal wells is output. The purpose and significance of quality control are not only monitoring and discrimination but also improving the fidelity and accuracy of the quality control object to support the efficient development of anisotropic reservoirs.

[0104] The anisotropic field quality control method based on well-seismic combination of three-component induction logging and partial azimuth seismic data, with the improved and updated anisotropic model of this invention, can be widely applied to anisotropic depth migration, geomechanical analysis, and precise geological steering of development wells. It provides a higher fidelity anisotropic field for research on selecting enrichment targets, accurate seismic imaging, accurate steering target entry, and effective fracturing engineering in anisotropic reservoir development, supporting the efficient development of horizontal well / group control areas in anisotropic reservoirs, and has good application and promotion prospects.

[0105] like Figure 4As shown, taking the western region of a certain oilfield as an example, the study area belongs to a typical "three-low" oil reservoir. A certain undeveloped section has strong anisotropic characteristics. In terms of seismic imaging, well-controlled anisotropic modeling and anisotropic depth migration processing have been completed. A total of 3D seismic data can be collected in the study area, with the acquisition years spanning ten years. The most recent result is the high-density 3D seismic data of work area B acquired in early 2016.

[0106] Step 1: Collection and organization of all basic data required for quality control processing. This includes determining the coordinates of four points in the quality control study area; collecting complete and accurate logging curves of all wells within the study area that encountered the target layer; collecting all seismic data from different times and observation systems within the four-point coordinates of the study area; collecting the velocity model and stratigraphic interpretation results (time domain) corresponding to each set of seismic data; and collecting core data from all exploration and appraisal wells in the study area, especially in the horizontal well platform area. If there is no core sample of the target layer in the entire study area, core sampling will be carried out during the drilling of the most recently encountered target layer in the area. The top and bottom depths of the core samples must fully cover the target layer. Through collection, three sets of seismic data and corresponding velocity models were found. At the same time, core sampling of the target layer was completed in multiple wells in the study area, and the core data was preserved intact and can be used for subsequent research steps of this invention.

[0107] Step 2: Locate the drilling schedule in the study area. For wells that have been drilled and logged but have not yet been casingd, coordinate to perform as many three-component induction logging operations as possible. For wells in the area that meet the conditions for open-hole logging but have not yet undergone logging operations, perform three-component induction logging operations. Complete logging operations for as many vertical, deviated, and horizontal wells as possible in the target formation.

[0108] Step 3: Optimize the seismic data volume collected in Step 1. Based on criteria such as minimum area, latest acquisition, maximum offset, maximum coverage count, and maximum aspect ratio of the target layer, select a set of 3D seismic data. Perform time-depth conversion using a velocity model. This conversion includes processed seismic data, pre-stack gathers, and layer interpretation results, transforming the processed seismic data and pre-stack gathers into the depth domain. Collect the initial anisotropic parameter field M for subsequent quality control. anisotropy1 Using four-point coordinates, the selected seismic data and anisotropic field (M) are combined. anisotropy1 The data was matched, and the same grid was set. After extending the data by a maximum offset in four directions, the data outside the extended study area was discarded. The best data was selected from three sets of seismic data acquired in different years. The latest data had a pixel size of 10m*10m, a maximum offset greater than 3000m, a target layer aspect ratio greater than 0.8, a maximum coverage count of 192, and all acquisition system parameters were the best among the three sets. Therefore, it was selected as the preferred source of basic seismic data for this invention.

[0109] Step 4: Perform five-dimensional data regularization on the pre-stack CMP gathers after mesh filtering in Step 3, ensuring that the minimum coverage number at the shallowest depth of the target layer is no less than 360 times. Through radial five-dimensional data regularization, the coverage number of the target layer in the pre-stack seismic data of Area B increased from 192 to 720 times.

[0110] Step 5: Perform OVT domain data sorting on the pre-stack CMP gather after the five-dimensional data regularization in Step 4, and sort the gather heads by azimuth and offset.

[0111] Step 6: Under the guidance of geological understanding, the CMP gathers extracted from the OVT domain obtained in Step 5 are used to determine the starting azimuth according to the structural distribution pattern. The 360-degree azimuth seismic data are divided into 12 azimuth sectors on average. Prestack seismic data within the azimuth range of each sector are selected, with each sector having no less than 30 effective covers. The seismic data from the 12 groups of different azimuth sectors divided from the prestack data of Area B processed in Step 5 have an average of 60 covers per group, which meets the technical requirements of this invention.

[0112] Step 7: Perform multiple suppression processing on the gathers within the 12 azimuth sectors defined in Step 6. This step uses weighted least squares Radon transform to suppress interlayer multiples and long-range multiples.

[0113] Step 8: Generate velocity analysis gathers and autocorrelation energy spectra from the 12 sets of CMP gathers obtained in Step 7. All offset information must be retained in this step. Seismic data with offsets greater than 3000m are also retained in this step without data cut-off for far offsets.

[0114] Step 9: Using the velocity analysis gathers and energy spectra obtained in Step 8, complete 12 sets of automatic velocity analyses to form Velocity data. 方位1 To Vel 方位12 First, for Vel 方位1 To Vel 方位12 Sort the data to determine the velocity values ​​Vel at the locations with the highest and lowest velocities. max方位m To Vel min方位n Calculate the same depth Vel of the target layer max方位m To Vel min方位n The absolute value of the difference forms a velocity difference field in different directions.

[0115] Step 10: Using the cored sample from Step 1, measure the anisotropy parameters of the target layer rock sample in an acoustic laboratory. Use the anisotropy parameter data measured in the laboratory to analyze the quality-controlled anisotropy field M. anisotropy1 M is obtained by calibration update anisotropy2 .

[0116] Step 11: Using the depth domain layer interpretation results obtained in Step 3, select a segment of the target layer to draw M. anisotropy2 The planar property map is used to determine the correlation between the updated anisotropic field and the velocity difference field in different orientations obtained in step 9. The cross-correlation is calculated within the same physical range. If the cross-correlation is less than 0.8, the quality control fails and the process cannot proceed to the next step. If the cross-correlation is greater than or equal to 80%, the quality control passes and the process proceeds to the next step.

[0117] Step 12: The three-component induction logging data obtained in Step 2 contains nine magnetic components measured by three transmitting coils and three receiving coils in vertical, inclined, or horizontal sections. Anisotropic forward modeling is completed by applying electromagnetic excitation to the anisotropic formation and solving the three-dimensional response of the formation using Maxwell's equations. The formation response is then solved using the forward modeling results and algorithms such as staggered grid finite difference method and finite element method. The residuals between the calculated results and the actual measurement results are calculated, and the parameters are adjusted and updated until the residuals are minimized or the a priori criteria are met. This allows the nine conductivity components to be inverted, and the different resistivities in three directions at a certain observation point are finally determined. The results are used to establish an anisotropic resistivity field of the target layer in the same anisotropic parameter directions as the controlled anisotropic field.

[0118] Step 13: Use the resistivity anisotropy field obtained in Step 12 to calibrate the quality control anisotropy field M. anisotropy2 If the correlation is greater than 90% (multiple wells), the quality control is passed; if the correlation is less than or equal to 90%, the quality control is failed. In this case, it is necessary to analyze and record the well information that does not meet the requirements in the low correlation area.

[0119] Step 14: If the correlation between the azimuth velocity difference field obtained in Step 9 and the three-component induced resistivity anisotropy field obtained in Step 12 is greater than 75%, the quality control is passed; if it is less than or equal to 75%, the quality control is failed. At this time, it is necessary to analyze and record the well information that does not conform to the low correlation area.

[0120] Step 15: Compare the areas that failed quality control in Steps 13 and 14. If there are wells that failed all quality control checks, then M... anisotropy1 Wells removed from the well information set used in the modeling process will no longer participate in the anisotropic modeling. The remaining wells will be used to re-establish the initial anisotropic model M. anisotropy1 .

[0121] Step 16: Re-establish the anisotropic model M using the information from the abnormal wells identified in Step 15. anisotropy1 Repeat steps 9 to 14 to complete all quality control processes until the quality control requirements are met, and output the final anisotropic model.

[0122] This invention combines microscopic and macroscopic perspectives, cross-calibrates seismic velocity and logging velocity, and utilizes OVT domain azimuth processing technology and three-component induction logging technology to collaboratively complete the quality control of the initial anisotropic field. Based on the quality control, abnormal wells that reduce the accuracy of the anisotropic model in the development area are identified, removed, and then the anisotropic model is re-established and iteratively quality controlled. This makes the anisotropic field physics in the development and research area more compliant and more accurate, with better correlation with the seismic imaging scale and better agreement with the anisotropic laws obtained from well logging reservoir sand body scale measurements.

[0123] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for quality control of anisotropic fields, characterized in that, The method includes: Quality control data were collected for the target layer of the area to be studied; The seismic data in the quality control data is compared with the anisotropic field M. anisotropy1 Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth; A resistivity anisotropic field was established using three-component induction logging. When the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold, the first quality control is passed; Core samples were collected from the target layer, and the anisotropy of the core samples was measured in the laboratory. The anisotropy parameter data obtained from the laboratory measurements were used to analyze the quality-controlled anisotropy field M. anisotropy1 M is obtained by calibration update anisotropy2 ; The anisotropic field M is calibrated using the maximum velocity difference field in each azimuth. anisotropy2 When the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropy field is greater than the second correlation threshold, the second quality control is passed. Quality control of the anisotropic field M is achieved by calibrating the resistivity anisotropic field. anisotropy2 When the correlation between the maximum velocity difference field in each orientation and the resistivity anisotropy field is greater than the third correlation threshold, the third quality control is passed. When the first, second, and third quality controls pass simultaneously, the final anisotropic field is output. A resistivity anisotropic field is established using three-component induction logging, including: Three-component induction logging was carried out on wells in the study area that met the open-hole logging conditions. For three-component induction logging data, nine magnetic components are obtained by measuring the vertical, inclined, or horizontal sections through three transmitting coils and three receiving coils. Anisotropic forward modeling is completed by applying electromagnetic excitation to anisotropic formations and solving the three-dimensional response of the formation using Maxwell's equations. The formation response is then solved using the forward modeling results and the staggered grid finite difference method or finite element method. The residuals are calculated by comparing the calculation results with the actual measurement results. The parameters are then adjusted and updated until the residuals are minimized or the a priori criteria are met. Nine conductivity components are obtained by inversion, and finally, the different resistivities in three directions at a certain observation point are determined. Using the results, a target layer resistivity anisotropic field is established in the same anisotropic parameter direction as the controlled anisotropic field.

2. The anisotropic field quality control method according to claim 1, characterized in that, Collect quality control data, including: Determine the coordinates of four points in the quality control study area, collect all drilling and target layer logging curves that are correct and complete within the study area, collect all seismic data from different times and different observation systems within the four coordinates of the study area, collect the velocity model and stratigraphic interpretation results corresponding to each set of seismic data, and collect coring data of all exploration wells in the target layer of the horizontal well platform area within the study area.

3. The anisotropic field quality control method according to claim 1, characterized in that, The seismic data in the quality control data is compared with the anisotropic field M. anisotropy1 Matching, including: Based on the criteria of minimum area, latest acquisition, maximum offset, maximum coverage times, and maximum aspect ratio of the target layer, 3D seismic data are selected from the quality control data. The velocity model is used to complete the time-depth conversion, so that the seismic processing results and pre-stack gathers are converted to the depth domain. Using four-point coordinates, the selected seismic data and anisotropic field M are combined. anisotropy1 Match the data, set them to the same grid, and remove the extended data outside the study area after extending them by a maximum offset in four directions.

4. The anisotropic field quality control method according to claim 3, characterized in that, The time-depth conversion objects include seismic processing results, pre-stack gathers, and stratigraphic interpretation results.

5. The anisotropic field quality control method according to claim 1, characterized in that, The pre-stack gather OVT five-dimensional data is regularized and divided into several groups of azimuth sectors, including: Seismic data and anisotropic field M anisotropy1 Five-dimensional data regularization is performed on the pre-stack CMP gathers after matching and mesh filtering; The pre-stack CMP gathers after five-dimensional data regularization are sorted in the OVT domain, and the sorted trace heads are azimuth and offset. The initial azimuth was determined according to the structural distribution pattern. The 360-degree azimuth seismic data was divided into several azimuth sectors on average, and the pre-stack seismic data within the azimuth range of each sector were selected.

6. The anisotropic field quality control method according to claim 1, characterized in that, Establish the maximum velocity difference field for each azimuth, including: Multiple wave suppression processes are applied to gathers within several azimuth sectors. The CMP gather obtained by wave suppression is used to generate a gather for velocity analysis and an autocorrelation energy spectrum while retaining all offset information. Automatic velocity analysis is performed by grouping velocity gathers and energy spectra in different azimuths to form several azimuths. The azimuths are sorted to determine the maximum and minimum velocities of each azimuth. The absolute value of the difference between the maximum and minimum velocities at the same depth in the target layer is calculated to form the maximum velocity difference field of each azimuth.

7. The anisotropic field quality control method according to claim 1, characterized in that, Also includes: If the first, second, or third quality control fails, M will be... anisotropy1 Wells that failed quality control were removed from the well information set used in the modeling process and were no longer included in the anisotropic modeling. The remaining wells were used to rebuild the initial anisotropic model M. anisotropy1 And re-perform quality control.

8. An anisotropic field quality control device, characterized in that, include: The system comprises a first quality control unit, a second quality control unit, a third quality control unit, and an output unit. The first quality control unit is used to collect quality control data for the target layer of the area to be studied. The first quality control unit is also used to combine the seismic data in the quality control data with the anisotropic field M. anisotropy1 Matching, regularizing the five-dimensional data of the pre-stack OVT gather into several azimuth sectors, and establishing the maximum velocity difference field of each azimuth; The first quality control unit is also used to establish a resistivity anisotropic field through three-component induction logging; The first quality control unit is also used to ensure that the first quality control passes when the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropic field is greater than the first correlation threshold. The second quality control unit is used to collect core samples from the target layer and measure the anisotropy of the core samples in the laboratory; the anisotropy parameter data obtained from the laboratory measurements are used to control the anisotropic field M. anisotropy1 M is obtained by calibration update anisotropy2 ; The second quality control unit is also used to calibrate the quality control anisotropic field M using the maximum velocity difference field in each azimuth. anisotropy2 When the correlation between the maximum velocity difference field in each azimuth and the resistivity anisotropy field is greater than the second correlation threshold, the second quality control is passed. The third quality control unit is used to calibrate the quality control anisotropic field M through the resistivity anisotropic field. anisotropy2 When the correlation between the maximum velocity difference field in each orientation and the resistivity anisotropy field is greater than the third correlation threshold, the third quality control is passed. The output unit is used to output the final anisotropic field after the first, second, and third quality controls have passed simultaneously. A resistivity anisotropic field is established using three-component induction logging, including: Three-component induction logging was carried out on wells in the study area that met the open-hole logging conditions. For three-component induction logging data, nine magnetic components are obtained by measuring the vertical, inclined, or horizontal sections through three transmitting coils and three receiving coils. Anisotropic forward modeling is completed by applying electromagnetic excitation to anisotropic formations and solving the three-dimensional response of the formation using Maxwell's equations. The formation response is then solved using the forward modeling results and the staggered grid finite difference method or finite element method. The residuals are calculated by comparing the calculation results with the actual measurement results. The parameters are then adjusted and updated until the residuals are minimized or the a priori criteria are met. Nine conductivity components are obtained by inversion, and finally, the different resistivities in three directions at a certain observation point are determined. Using the results, a target layer resistivity anisotropic field is established in the same anisotropic parameter direction as the controlled anisotropic field.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, which stores computer programs; A processor, when executing a computer program stored in a memory, implements the anisotropic field quality control method according to any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the anisotropic field quality control method according to any one of claims 1-7.

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