A geosteering method and device

Abstract

This specification relates to the technical field of oil exploration and development, and provides a geosteering method and device. The method includes: establishing a three-dimensional geological model based on the logging data and seismic data of the target block; optimizing the seismic data based on the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model based on the optimized seismic data; adjusting the reconstructed three-dimensional geological model using the logging while drilling curve to obtain a three-dimensional geosteering model; judging whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation results corresponding to the optimized seismic data, if not, repeating the above steps to adjust the seismic data to update the three-dimensional geosteering model; determining the geosteering of the target block based on the three-dimensional geosteering model. Through the embodiments of this specification, the accuracy of the geosteering model can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum exploration and development, and in particular to a geosteering method and device. Background Art

[0002] In the rolling exploration and development stage of oil and gas fields, the lateral development scale of oil and gas reservoirs and the oil and gas reserves have been clearly demonstrated on a macro scale. In order to improve the oil and gas recovery efficiency and the oil leakage area, horizontal wells or high-angle wells are often deployed. Before drilling horizontal wells, the reservoir spatial distribution morphology predicted by seismic prediction is usually used to optimize the wellbore trajectory, determine the seismic response characteristics corresponding to the wellbore trajectory, establish a three-dimensional geosteering model, and forward-model the while-drilling curve. During the horizontal well drilling process, the while-drilling measurement data is usually compared with the forward-modeled logging curve, combined with the seismic response characteristics of high-quality reservoirs, and the geosteering model is updated to determine the formation position of the current trajectory, and optimize the trajectory to be drilled and the drilling decision according to the needs of the drilling project.

[0003] However, during the horizontal well drilling process, the measurement while drilling data can only measure the data of the drilled formation, and the geosteering model adjusted while drilling can only reflect the stratigraphic structure and attribute information of the current formation being drilled. For unknown formations, the current measurement while drilling instruments cannot detect the changes in the formation before drilling. Therefore, there is a large uncertainty in the geosteering model. Using such a geosteering model to adjust the wellbore trajectory may often cause the wellbore trajectory to drill out of the reservoir and lose the drilling rate. In order to make up for the defects of the pre-drilling formation of the existing geosteering model, it is necessary to use seismic data to predict and update the pre-drilling geosteering model. However, for ultra-deep formations, due to energy attenuation during the seismic data acquisition process, the high-frequency components are attenuated more, and the formation resolution is low, which cannot meet the needs of updating the geosteering model and adjusting the trajectory. Therefore, a geosteering method is urgently needed to establish an accurate geosteering model and provide effective geosteering decisions. Summary of the invention

[0004] In view of the current ultra-deep formations, due to energy attenuation during seismic data acquisition, the high-frequency components are attenuated more, the formation resolution is low, and the needs of geosteering model updating and trajectory adjustment cannot be met, resulting in the low accuracy of the geosteering model. This solution is proposed to overcome the above problems or at least partially solve the above problems.

[0005] In one aspect, some embodiments of the present specification provide a geosteering method, the method comprising:

[0006] Establish a three-dimensional geological model based on the well logging data and seismic data of the target block;

[0007] Optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model according to the optimized seismic data;

[0008] The reconstructed 3D geological model is adjusted using the logging while drilling curve to obtain a 3D geosteering model;

[0009] Determine whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data, and if not, repeat the above steps to adjust the seismic data to update the three-dimensional geosteering model;

[0010] The geosteering of the target block is determined according to the three-dimensional geosteering model.

[0011] Furthermore, the three-dimensional geological model is established based on the well logging data and seismic data of the target block, including:

[0012] Determine rock physical information and lithology combination information according to the well logging data;

[0013] Using the well logging data and seismic data to construct a synthetic seismic record of the target block, and performing well-seismic calibration processing on the synthetic seismic record;

[0014] Extract the seismic phase position and seismic response characteristics of the target layer in the adjacent wells based on the well-seismic calibration results;

[0015] The seismic horizon interpretation results of the target layer of the target well are obtained through the seismic phase position and seismic response characteristics of the target layer of the adjacent well;

[0016] A three-dimensional geological model is established based on the seismic horizon interpretation results, the rock physics information and the lithology combination information.

[0017] Furthermore, the step of constructing a synthetic seismic record of the target block using the well logging data and seismic data includes:

[0018] Using standard Ricker wavelet to adjust the time-depth relationship of the logging data;

[0019] Determine the logging reflection coefficient corresponding to the logging data after adjusting the time-depth relationship;

[0020] extracting seismic wavelets from the seismic data;

[0021] The synthetic seismic record is constructed using the seismic wavelet and the well logging reflection coefficient.

[0022] Furthermore, the space-varying wavelet in the three-dimensional geological model is obtained by interpolating the seismic wavelet.

[0023] Further, the optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model includes:

[0024] The space-varying wavelet is used to perform deconvolution processing on the seismic data to obtain optimized seismic data.

[0025] Furthermore, before establishing the three-dimensional geological model based on the well logging data and seismic data of the target block, the following steps are further included:

[0026] Preprocessing the well logging data to eliminate abnormal values ​​in the well logging data;

[0027] A well logging response characteristic prediction model is established using the well logging data to predict the well logging response characteristic data of the target well.

[0028] Furthermore, the three-dimensional geological model reconstructed by adjusting the logging while drilling curve includes:

[0029] Real-time acquisition of logging while drilling data;

[0030] Establishing a logging while drilling curve corresponding to the logging while drilling data;

[0031] The reconstructed three-dimensional geological model is forward modeled using a well logging response characteristic prediction model to obtain a forward modeled well logging curve;

[0032] The inclination angle and thickness parameters in the reconstructed three-dimensional geological model are adjusted so that the adaptability between the forward logging curve and the logging while drilling curve reaches a first threshold.

[0033] Further, judging whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation results corresponding to the optimized seismic data includes:

[0034] Extracting reservoir data from the seismic horizon interpretation result;

[0035] Calculating the matching degree between the target layer data and the reservoir data;

[0036] If the matching degree is greater than the second threshold, the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data, otherwise they do not match.

[0037] Furthermore, determining the geosteering of the target block according to the three-dimensional geosteering model further includes:

[0038] According to the three-dimensional geosteering model, a sweet spot prediction position of the target layer is obtained;

[0039] If the predicted sweet spot position does not match the actual drilling situation, the three-dimensional geosteering model is updated using the method described in any one of the aforementioned embodiments, and the phase spectrum of the space-variant wavelet is adjusted during the updating process.

[0040] On the other hand, some embodiments of the present specification further provide a geosteering device, the device comprising:

[0041] Establish a module for building a three-dimensional geological model based on well logging data and seismic data of the target block;

[0042] An optimization module, used for optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model according to the optimized seismic data;

[0043] An adjustment module is used to adjust the reconstructed three-dimensional geological model using the logging while drilling curve to obtain a three-dimensional geosteering model;

[0044] An updating module is used to determine whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data. If not, repeat the above steps to adjust the seismic data to update the three-dimensional geosteering model;

[0045] The guidance module is used to determine the geo-steering of the target block according to the three-dimensional geo-steering model.

[0046] On the other hand, some embodiments of the present specification further provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein when the computer program is executed by the processor, the instructions of the above method are executed.

[0047] On the other hand, some embodiments of the present specification further provide a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor of a computer device, the instructions of the above method are executed.

[0048] On the other hand, some embodiments of the present specification further provide a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor of a computer device, the instructions of the above method are executed.

[0049] One or more technical solutions provided by some embodiments of this specification have at least the following technical effects:

[0050] The embodiments of the present specification can establish a spatially varying wavelet at a target stratum according to seismic data when establishing a three-dimensional geological model, and optimize the seismic data according to the spatially varying wavelet in the three-dimensional geological model to improve the resolution of ultra-deep strata, and reconstruct the three-dimensional geological model. Thereafter, the reconstructed three-dimensional geological model is adjusted using the logging while drilling curve to make the three-dimensional geological model fit the real stratum data obtained by the logging while drilling as much as possible, thereby obtaining a three-dimensional geological steering model, and judging whether the current three-dimensional geological steering model needs to be iteratively updated according to whether the seismic layer interpretation corresponding to the optimized seismic data matches, thereby obtaining a three-dimensional geological steering model that matches both the optimized seismic data and the logging while drilling curve, thereby improving the accuracy of the three-dimensional geological steering model and facilitating geological decision-making.

[0051] The above description is only an overview of the technical solutions of some embodiments of this specification. In order to more clearly understand the technical means of some embodiments of this specification, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of some embodiments of this specification more obvious and easy to understand, the specific implementation methods of some embodiments of this specification are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate some embodiments of this specification or technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or prior art descriptions. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0053] Figure 1 A schematic diagram of an implementation system of a geosteering method in some embodiments of this specification is shown;

[0054] Figure 2 A flow chart of a geosteering method in some embodiments of this specification is shown;

[0055] Figure 3 A schematic diagram of the steps of establishing a three-dimensional geological model in some embodiments of this specification;

[0056] Figure 4 A schematic diagram of the steps of constructing synthetic seismic records in some embodiments of this specification;

[0057] Figure 5 A schematic diagram of the steps of adjusting the reconstructed three-dimensional geological model in some embodiments of this specification;

[0058] Figure 6 A schematic diagram of the steps of matching seismic horizon interpretation results in some embodiments of this specification;

[0059] Figure 7 A schematic diagram of reservoir development characteristics of adjacent wells in some embodiments of this specification;

[0060] Figure 8 A schematic diagram of seismic response characteristics corresponding to a target layer in some embodiments of this specification;

[0061] Fig. 9 A schematic cross-sectional view of original seismic data in some embodiments of this specification;

[0062] Fig.10 A schematic cross-sectional view of optimized seismic data in some embodiments of this specification;

[0063] Fig.11 A first schematic diagram of a three-dimensional geosteering model in some embodiments of this specification;

[0064] Fig.12 A second schematic diagram of a three-dimensional geosteering model in some embodiments of this specification;

[0065] Fig.13 A third schematic diagram of a three-dimensional geosteering model in some embodiments of this specification;

[0066] Fig.14 This is a schematic diagram of the structure of a geosteering device in some embodiments of this specification;

[0067] Fig.15 This is a schematic diagram of the computer device structure provided in some embodiments of this specification.

[0068] [Description of Reference Numerals]

[0069] 101. Terminal;

[0070] 102. Server;

[0071] 1401. Establish module;

[0072] 1402. Optimization module;

[0073] 1403. Adjustment module;

[0074] 1404. Update module;

[0075] 1405, guidance module;

[0076] 1502. Computer equipment;

[0077] 1504. Processor;

[0078] 1506. Memory;

[0079] 1508, driving mechanism;

[0080] 1510, input / output interface;

[0081] 1512. Input devices;

[0082] 1514. Output device;

[0083] 1516. Presentation equipment;

[0084] 1518. Graphical user interface;

[0085] 1520, network interface;

[0086] 1522. Communication link;

[0087] 1524. Communication bus. DETAILED DESCRIPTION

[0088] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in some embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on some embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0089] It should be noted that the terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment. It should be noted that the acquisition, storage, use, processing, etc. of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations.

[0090] like Figure 1The diagram is a schematic diagram of an implementation system of a geosteering method according to an embodiment of the present invention, which may include: a terminal 101 and a server 102. The terminal 101 and the server 102 communicate with each other through a network, which may include a local area network (LAN), a wide area network (WAN), the Internet or a combination thereof, and is connected to a website, a user device (such as a computing device) and a back-end system. A staff member may send a geosteering request to the server 102 through the terminal 101. After receiving the geosteering request, the server 102 calls the logging data and seismic data of the target block in the database and the real-time logging while drilling data for calculation and processing to obtain a geosteering result, and sends the geosteering result to the terminal 101, so that the staff member can make a drilling decision based on the geosteering result.

[0091] In the embodiments of this specification, the server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks (CDN, Content Delivery Network), and big data and artificial intelligence platforms.

[0092] In an optional embodiment, the terminal 101 may include but is not limited to electronic devices such as self-service terminal devices, desktop computers, tablet computers, laptop computers, smart wearable devices, etc. Optionally, the operating system running on the electronic device may include but is not limited to Android system, IOS system, Linux, Windows, etc. Of course, the terminal 101 is not limited to the above-mentioned electronic devices with a certain entity, and it can also be software running in the above-mentioned electronic devices.

[0093] In addition, it should be noted that Figure 1 What is shown is only an application environment provided by the present disclosure. In actual application, multiple terminals 101 may be included, and this specification does not limit this.

[0094] Figure 2 It is a flow chart of a geological guidance method provided by an embodiment of the present invention. This specification provides the method operation steps described in the embodiment or flow chart, but may include more or fewer operation steps based on conventional or non-creative labor. The order of steps listed in the embodiment is only one way of executing the steps among many orders, and does not represent the only order of execution. When the actual system or device product is executed, it can be executed in the order of the method shown in the embodiment or the drawings or in parallel. Specifically, Figure 2As shown, applied to the above-mentioned server side, the method may include:

[0095] S201: Establish a three-dimensional geological model based on the well logging data and seismic data of the target block;

[0096] S202: optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model according to the optimized seismic data;

[0097] S203: adjusting the reconstructed three-dimensional geological model using the logging while drilling curve to obtain a three-dimensional geosteering model;

[0098] S204: determining whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data; if not, repeating the above steps to adjust the seismic data to update the three-dimensional geosteering model;

[0099] S205: Determine the geosteering of the target block according to the three-dimensional geosteering model.

[0100] The embodiments of the present specification can establish a spatially varying wavelet at a target stratum according to seismic data when establishing a three-dimensional geological model, and optimize the seismic data according to the spatially varying wavelet in the three-dimensional geological model to improve the resolution of ultra-deep strata, and reconstruct the three-dimensional geological model. Thereafter, the reconstructed three-dimensional geological model is adjusted using the logging while drilling curve to make the three-dimensional geological model fit the real stratum data obtained by the logging while drilling as much as possible, thereby obtaining a three-dimensional geological steering model, and judging whether the current three-dimensional geological steering model needs to be iteratively updated according to whether the seismic layer interpretation corresponding to the optimized seismic data matches, thereby obtaining a three-dimensional geological steering model that matches both the optimized seismic data and the logging while drilling curve, thereby improving the accuracy of the three-dimensional geological steering model and facilitating geological decision-making.

[0101] Specifically, in some embodiments, well logging is a method of measuring geophysical parameters by using geophysical properties such as electrochemical properties, conductive properties, acoustic properties, and radioactivity of rock formations. Well logging data refers to geophysical parameter data of the target formation obtained by the well logging method. Seismic data refers to seismic signal data obtained by seismic exploration. In some embodiments, logging data, target block geological data, etc. can also be introduced to establish a three-dimensional geological model. This is not limited herein. The well logging response, reservoir position, and lithology combination model of the target reservoir can be analyzed by seismic data, well logging data, etc., so as to obtain the stratigraphic distribution of the formation where the target block is located and establish a three-dimensional geological model. However, since the target well is in a state to be drilled, the complete stratigraphic data of the target well cannot be obtained. Therefore, it is necessary to predict the stratigraphic data of the formation where the target well is located. In some embodiments, the stratigraphic data of the formation where the target well is located can be obtained by interpolation fitting prediction through adjacent well data. The stratigraphic data can include logging response characteristic data such as natural gamma data, and can also include seismic signal data such as seismic data. It can be understood that the data corresponding to each formation in the three-dimensional geological model can be multi-dimensional, such as logging response characteristic dimension, seismic data dimension, etc.

[0102] Furthermore, in some embodiments, after the three-dimensional geological model is constructed by well logging data, mud logging data, seismic data (i.e., seismic data), etc., the space-varying wavelet of the target layer is obtained by interpolation fitting based on the seismic data of adjacent wells. The space-varying wavelet can be used to optimize the seismic data of the ultra-deep formation in the current seismic data, which can be understood as further updating the seismic data and improving the stratigraphic resolution of the ultra-deep formation. The three-dimensional geological model can be updated on the basis of the updated seismic data, and during the drilling of the target well, the logging while drilling tool can be used to measure the logging while drilling data, and then generate a logging while drilling curve. Since the logging while drilling curve and the logging while drilling data reflect the real stratigraphic data of the formation where the target well is located, it is necessary to use the logging while drilling curve as a reference to adjust the parameters in the updated and reconstructed three-dimensional geological model to obtain a three-dimensional geosteering model with higher accuracy. In addition, it is also necessary to ensure that the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation results corresponding to the optimized seismic data, thereby improving the accuracy of the three-dimensional geosteering model.

[0103] See attached Figure 3 In some embodiments, establishing a three-dimensional geological model based on the well logging data and seismic data of the target block may include:

[0104] S301: Determine rock physical information and lithology combination information according to the well logging data;

[0105] S302: constructing a synthetic seismic record of the target block using the well logging data and seismic data, and performing well-seismic calibration processing on the synthetic seismic record;

[0106] S303: extracting the seismic phase position and seismic response characteristics of the target layer in the adjacent well according to the well-seismic calibration results;

[0107] S304: Obtaining the seismic horizon interpretation result of the target layer of the target well through the seismic phase position and seismic response characteristics of the target layer of the adjacent well;

[0108] S305: Establishing a three-dimensional geological model according to the seismic horizon interpretation results, the rock physics information and the lithology combination information.

[0109] It can be understood that, in some embodiments, rock physical information is information reflecting various physical properties of rocks, and lithology refers to some attributes reflecting rock characteristics, such as color, composition, structure, cement, cementation type, special minerals, etc. Lithology usually includes two types: one is rock and the other is soil. Lithology combination information is information reflecting the lithology of the formation. The comprehensive use of logging data and seismic data is an effective method to predict the lithology, physical properties and reserves of the target layer. The logging data is in the depth domain, and the seismic data is in the time domain (it can also be converted into the frequency domain or other domains using digital signal processing methods). Synthetic seismic records can achieve fine calibration of the target layer segment. Well-seismic calibration is an effective means to establish the association between logging data and seismic data, so as to give full play to the advantages of logging data and seismic data. Effectively perform seismic inversion and reflect accurate formation information. Specifically, in some embodiments, logging curves can be generated based on logging data to obtain synthetic theoretical seismic traces. At the same time, actual seismic data from the wellside (adjacent wells) of the target well can be used for comparison and calibration, thereby completing the well seismic calibration process and obtaining the well seismic calibration results. Thereafter, the seismic phase position and seismic response characteristics of the target layer of the adjacent well are identified and extracted from the well seismic calibration results. The distribution of various formations in the formation where the target well is located, including the reservoir, is determined through the seismic phase position and seismic response characteristics of the target layer of the adjacent well and the seismic forward modeling results, thereby obtaining the fine seismic layer interpretation results of the target layer of the target well, and realizing the establishment of an effective three-dimensional geological model that accurately reflects the true situation of the target formation, providing an accurate model basis for the subsequent optimization of the three-dimensional geological model.

[0110] See attached Figure 4 In some embodiments, constructing a synthetic seismic record of the target block using the well logging data and seismic data may include:

[0111] S401: using standard Ricker wavelet to adjust the time-depth relationship of the logging data;

[0112] S402: Determine the logging reflection coefficient corresponding to the logging data after adjusting the time-depth relationship;

[0113] S403: extracting seismic wavelets from the seismic data;

[0114] S404: Construct the synthetic seismic record using the seismic wavelet and the logging reflection coefficient.

[0115] It can be understood that, in some embodiments, the standard Ricker wavelet is a type of seismic wavelet, which is a seismic wave excited by a seismic source, propagated underground and received by people on the ground or in a well. It is usually a short pulse vibration, which is called a vibration wavelet. The standard Ricker wavelet can be used to convert the logging data in the depth domain into the logging data in the time domain, so as to obtain the logging reflection coefficient. The statistical algorithms that can be used to extract the seismic wavelet from the seismic data include methods based on high-order statistics, second-order statistics methods (collectively referred to as statistical methods) and nonlinear inversion, etc., which are not limited in this article. Then, the logging reflection coefficient is convolved with the extracted seismic wavelet to obtain an initial synthetic seismic record, and then the initial synthetic seismic record is corrected under a more accurate velocity field according to the seismic data of the neighboring wells in the target block. Then, the initial synthetic seismic record is matched and adjusted with the seismic traces near the well to obtain the final synthetic seismic record, and the well-seismic calibration processing is completed, so that the seismic phase position and seismic response characteristics corresponding to the target reservoir of the neighboring wells in the target block can be accurately determined.

[0116] Furthermore, in some embodiments, the space-varying wavelet in the three-dimensional geological model is obtained by interpolating the seismic wavelet.

[0117] It can be understood that, in some embodiments, the space-varying wavelet, which can also be called the space-varying seismic wavelet, and the seismic record (seismic data) can be regarded as the convolution of the formation reflection coefficient and the seismic wavelet. Therefore, in order to invert accurate formation information from the seismic record, it is necessary to first have an accurate seismic wavelet. The seismic wavelet prediction value of the formation where the target well is located obtained by interpolating the seismic wavelets of adjacent wells in the three-dimensional geological model as the space-varying wavelet can further improve the resolution of the seismic data of ultra-deep formations. In some embodiments, the seismic wavelet prediction value of the formation where the target well is located obtained by interpolating the seismic wavelets of adjacent wells in the reconstructed three-dimensional geological model (after well-seismic calibration processing) is used as the space-varying wavelet. On the basis of the refined three-dimensional geological model, the accuracy of the space-varying wavelet is further optimized. In some embodiments, the interpolation method can be a Kriging interpolation algorithm, which is not limited in this article.

[0118] Furthermore, in some embodiments, optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model may include: performing deconvolution processing on the seismic data using the space-varying wavelet to obtain optimized seismic data.

[0119] It can be understood that in some embodiments, the seismic data of ultra-deep formations have a large attenuation of high-frequency components and a low formation resolution due to the energy attenuation in seismic acquisition. Therefore, the seismic data can be deconvolved using space-varying wavelets to obtain high-resolution seismic data, and the three-dimensional geological model can be re-established using the optimized high-resolution seismic data to recalibrate the location of the target reservoir.

[0120] In some embodiments, before establishing a three-dimensional geological model based on the well logging data and seismic data of the target block, the following steps may be further included:

[0121] Preprocessing the well logging data to eliminate abnormal values ​​in the well logging data;

[0122] A well logging response characteristic prediction model is established using the well logging data to predict the well logging response characteristic data of the target well.

[0123] It can be understood that, in some embodiments, preprocessing the logging data can also be understood as standardizing the logging data, the purpose of which is to eliminate outliers, allow the logging curve to truly reflect the formation information, and ensure the accuracy of the subsequent three-dimensional geological model establishment. At the same time, the logging data can be used to establish a logging response feature prediction model through a regression algorithm. The logging response features may include resistivity, acoustic waves, natural gamma, etc. It should be noted that the logging response feature prediction model corresponds one-to-one to the formation where the target block is located, thereby realizing the prediction of the logging response feature data of the target well through the logging data of the adjacent wells.

[0124] See attached Figure 5 In some embodiments, adjusting the reconstructed three-dimensional geological model using the logging while drilling curve may include:

[0125] S501: Acquire logging while drilling data in real time;

[0126] S502: Establishing a logging while drilling curve corresponding to the logging while drilling data;

[0127] S503: forward modeling the reconstructed three-dimensional geological model using a well logging response characteristic prediction model to obtain a forward modeling well logging curve;

[0128] S504: adjusting the inclination and thickness parameters in the reconstructed three-dimensional geological model so that the adaptability between the forward logging curve and the logging while drilling curve reaches a first threshold.

[0129] It can be understood that, in some embodiments, the logging while drilling curve is a logging curve reflected by the real formation data obtained from the logging while drilling data. The logging while drilling data includes comprehensive logging data, MWD logging while drilling data and LWD logging while drilling data. The logging response characteristic data of the target well can be predicted according to the logging response characteristic prediction model. Then, the forward logging curve can be obtained by forward modeling based on the reconstructed three-dimensional geological model. The forward logging curve is the curve data predicted by the reconstructed three-dimensional geological model, not the logging curve reflected by the real formation data. Therefore, the accuracy of the reconstructed three-dimensional geological model can be judged by comparing the difference between the logging while drilling curve reflected by the real formation data and the predicted forward logging curve. Specifically, in some embodiments, the fitness of the forward logging curve and the logging while drilling curve can be calculated to judge whether the reconstructed three-dimensional geological model conforms to the real formation data. The fitness can be understood as the degree of fit or matching. The larger the fitness, the more accurate the reconstructed three-dimensional geological model is. When the fitness is Reaching the first threshold value indicates that the reconstructed three-dimensional geological model is sufficiently accurate. The specific calculation method of the fitness can be to sample sample points of the forward logging curve and the logging while drilling curve, calculate the proximity of each sample point, and thus obtain the fitness. The specific calculation method is not limited herein. In some embodiments, the error value between the forward logging curve and the logging while drilling curve can also be calculated, and whether the reconstructed three-dimensional geological model conforms to the real formation data can be judged according to the size of the error value. The smaller the error value, the more accurate the reconstructed three-dimensional geological model is. If the reconstructed three-dimensional geological model is not accurate enough, it is necessary to adjust the inclination and thickness parameters in the reconstructed three-dimensional geological model. Specifically, the adjustment method can be to reconstruct the three-dimensional geological model using the method described in the aforementioned embodiment to obtain a three-dimensional geological steering model. This is because the inclination and thickness parameters in the three-dimensional geological model cannot be adjusted at will. The three-dimensional geological model and all parameters therein are obtained based on seismic data, logging data, etc., thereby ensuring the accuracy and effectiveness of the three-dimensional geological steering model.

[0130] See attached Figure 6 In some embodiments, the step of determining whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data may include:

[0131] S601: extracting reservoir data from the seismic horizon interpretation result;

[0132] S602: Calculate the matching degree between the target layer data and the reservoir data;

[0133] S603: If the matching degree is greater than a second threshold, the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data, otherwise they do not match.

[0134] It can be understood that, in some embodiments, although the establishment of the three-dimensional geosteering model is based on optimized high-resolution seismic data, it cannot be guaranteed that the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation results corresponding to the optimized seismic data. Therefore, it is necessary to calculate the matching degree between the reservoir data in the seismic layer interpretation results and the target layer data. The matching degree can be calculated using the root mean square error between the target layer data and the reservoir data. According to the matching degree, it is determined whether the three-dimensional geosteering model needs to be updated again, thereby ensuring that the three-dimensional geosteering model can reflect the real stratigraphic information and reservoir distribution to the greatest extent.

[0135] Furthermore, in some embodiments, if it is determined that the target layer data in the three-dimensional geosteering model does not match the seismic layer interpretation results corresponding to the optimized seismic data, and the three-dimensional geosteering model needs to be updated, the phase spectrum or frequency in the seismic data is adjusted, such as appropriately scaling the frequency or moving the phase spectrum, and the method described in any of the aforementioned embodiments is repeated to reconstruct and update the three-dimensional geosteering model.

[0136] Furthermore, in some embodiments, determining the geosteering of the target block according to the three-dimensional geosteering model may further include:

[0137] According to the three-dimensional geosteering model, a sweet spot prediction position of the target layer is obtained;

[0138] If the predicted sweet spot position does not match the actual drilling situation, the three-dimensional geosteering model is updated using the method described in any of the above embodiments, and the phase spectrum of the space-varying wavelet is adjusted during the updating process.

[0139] It can be understood that, in some embodiments, the geosteering process is an interactive drilling method, which utilizes logging while drilling, measurement while drilling, directional tools and steering model software to continuously perform comparative analysis and adjust the well trajectory during the drilling of the horizontal well, direct the drilling direction, and adjust the well trajectory to the expected layer or the best position of the reservoir to achieve the best oil (gas) production or water injection effect. After the three-dimensional geosteering model is established, the sweet spot prediction position of the target layer can be determined according to the formation distribution and the current target wellbore trajectory. For example, in the early well-seismic comparison and calibration process, the sweet spot prediction position of the target layer of the target well is determined by the logging response characteristics and seismic characteristics corresponding to the sweet spot position indicated by the adjacent well. For example, if the natural gamma curve corresponding to the sweet spot position of the adjacent well is a low value and the seismic characteristic is a bright spot of wave crest reflection, then the natural gamma curve at the target well is a low value and the seismic characteristic is a bright spot of wave crest reflection. The position of the point is used as the sweet spot prediction position so that the target well can be drilled towards the target layer. In the process of oil and gas exploration and development, a large area of ​​oil and gas bearing areas and a large section of oil and gas bearing layers will be revealed. The sweet spot prediction position is often the part with good development benefits under current economic and technical conditions. Drilling is carried out at the sweet spot prediction position guided by the three-dimensional geological steering model, and combined with the actual drilling situation, it is judged whether the current sweet spot prediction position is accurate. If the drilling rate is lower than the preset threshold, the accuracy of the current sweet spot prediction position is low. If the drilling rate is high, it means that the current sweet spot prediction position is more accurate. When the accuracy of the current sweet spot prediction position is low, the three-dimensional geological steering model is updated by the method described in any of the aforementioned embodiments, and the phase spectrum of the space-variant wavelet is adjusted during the updating process, so that the seismic phase of the deconvolved seismic data responds and further matches the actual reservoir position.

[0140] Furthermore, the geosteering method is described in conjunction with a specific embodiment. However, it should be noted that this embodiment is only for better illustrating the present invention and does not constitute an improper limitation to the present invention.

[0141] Take a horizontal well in Block X of the Southwest Oil and Gas Field as an example. The target layer of this horizontal well is the fourth section of the Deng River, which is buried about 5,000 meters deep and belongs to the high-temperature and high-pressure formation. The directional screw tool is used, the drilling cycle is long, the drilling is frequent, and the drilling cost is high. In terms of geology, the formation drilled by this horizontal well is a carbonate formation, and the reservoir lithology is mainly dolomite. The high-quality reservoir is located at the paleo-geomorphic high point of the platform margin beach. Because the paleo-geomorphic high point was uplifted in the Tongwan Movement, it received leaching and overlapped with the hill beach to form a high-quality reservoir, which is located within 100 meters of the top of the reservoir. However, because the fourth section of the Deng River is buried deep, the seismic resolution is low and there is multi-solution, the accuracy of the geological guidance model is not high, which leads to difficult geological guidance decision-making, low reservoir drilling rate, frequent trajectory adjustment, and high drilling risk. The specific geological guidance process is:

[0142] Step 1: Collect and organize the seismic data, logging data and geological data of the target block, and perform standardized processing to study the logging response characteristics and seismic response characteristics of the target reservoir. According to the comparative analysis of adjacent wells, the target reservoir of this well has a top of the lamp, and the reservoir thickness is 30m. Figure 7 As shown, Figure 8 These are the seismic response characteristics of the adjacent wells corresponding to the high-quality reservoir. From the comparison of wells and seismic data, the seismic response of the high-quality reservoir is from the peak with the maximum amplitude at the top of Dengsi to the phase of 0.

[0143] Step 2: Perform linear regression analysis to establish a regression prediction model for the logging response characteristic (such as acoustic wave, gamma or resistivity) curve.

[0144] Step 3: Continue as Figure 8 As shown, synthetic seismic records of the target block wells are constructed, and well-seismic calibration processing is performed to adjust the time-depth relationship of the logging data and extract seismic wavelets from the seismic data.

[0145] Step 4: Use logging data and seismic data (seismic data can obtain seismic interpretation layers) to establish a three-dimensional geological model, which includes the target layer segment. At the same time, based on the Kriging interpolation algorithm, use the seismic data of adjacent wells to reconstruct the spatially varying wavelet of the target layer segment.

[0146] Step 5: Use space-varying wavelets to perform deconvolution on the seismic data to obtain optimized high-resolution seismic data, such as Fig. 9 and Fig.10 As shown in Figure 3, the resolution of the optimized seismic data is significantly improved.

[0147] The deconvolution process is as follows:

[0148] Assume that the time domain seismic record is represented as:

[0149] x(t)=b(t)*ξ(t) (1)

[0150] Among them, x(t) represents the seismic record collected in the field, b(t) is the seismic wavelet, ξ(t) is the reflection coefficient, t is the duration, and * represents the convolution operator. Taking Fourier transform on both sides of equation (1), we get the seismic record expression in the frequency domain:

[0151] X(w)=B(w)·ξ(w) (2)

[0152] Among them, X(w), B(w), ξ(w) represent the seismic record spectrum, wavelet spectrum and reflection coefficient spectrum respectively, w represents the corresponding frequencies in the frequency domain, and · represents the product operation;

[0153] Apparently:

[0154]

[0155] but:

[0156] ξ(w)=A(w)·X(w) (3)

[0157] Then perform inverse Fourier transform on equation (3) to obtain high-resolution seismic data in the time domain:

[0158] ξ(t)=a(t)*x(t)

[0159] Among them, a(t) is called the anti-wavelet, also known as the anti-filter factor.

[0160] Step 6: Establish a 3D geosteering model based on the adjacent well data and seismic reflection wave characteristics, and forward model the logging while drilling curve, such as Fig.11 As shown in the figure, the high-quality reservoir corresponds to the peak to 0 phase (the bright yellow part is the high-quality reservoir). During the drilling process, the guidance model of the undrilled formation is updated based on the measurement while drilling results and combined with the seismic reflection characteristics, such as Fig.12 As shown in the figure, due to the low seismic resolution and inaccurate 3D geosteering model, the reservoir was drilled out from the top at a well depth of 6500m, but the seismic did not show the layer and the drilling failed.

[0161] Step 7: Use the drilled data to reconstruct the pseudo-acoustic curve and density curve, perform well seismic calibration and deconvolution, and recreate the 3D geosteering model to make drilling steering decisions. In order to maximize the use of this well, the construction party decided to drill the horizontal section from the well depth of 6500m. The design trajectory was optimized with reference to the geosteering model under the constraints of the high-resolution seismic profile. The drilling measurement curve during the drilling process was basically consistent with the seismic prediction results. The drilling trajectory was also fine-tuned according to the steering model. The well was drilled to a depth of 6950m and the drilling rate of the last 450m reached 95%. The final 3D geosteering model is shown below. Fig.13 shown.

[0162] In the above specific embodiment, the target horizontal well is a development well, and the pilot well is not drilled. The horizontal well is directly implemented. The target reservoir is located at the top of the reservoir, and the seismic response is at phase 0. During the drilling process, the seismic data without high-resolution processing is used for prediction, resulting in secondary sidetracking of the horizontal section of the wellbore. During the secondary sidetracking, high-resolution seismic processing is performed to improve the accuracy of the geosteering model, and the sidetracking formation encounter rate reaches 92%.

[0163] It should be noted that, although the operations of the method of the present invention are described in a specific order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0164] Corresponding to the above-mentioned geosteering method, some embodiments of this specification also provide a geosteering device, referring to Fig.14 As shown, in some embodiments, the apparatus may include:

[0165] Establishing module 1401, for establishing a three-dimensional geological model based on the well logging data and seismic data of the target block;

[0166] An optimization module 1402, configured to optimize the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstruct the three-dimensional geological model according to the optimized seismic data;

[0167] An adjustment module 1403 is used to adjust the reconstructed three-dimensional geological model using the logging while drilling curve to obtain a three-dimensional geosteering model;

[0168] An updating module 1404 is used to determine whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data. If not, repeat the above steps to adjust the seismic data to update the three-dimensional geosteering model.

[0169] The steering module 1405 is used to determine the geosteering of the target block according to the three-dimensional geosteering model.

[0170] For the convenience of description, the above device is described by dividing it into various units according to its functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0171] It should be noted that in the embodiments of this specification, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user and fully authorized by all parties.

[0172] The embodiments of this specification also provide a computer device. Fig.15As shown, in some embodiments of the present specification, the computer device 1502 may include one or more processors 1504, such as one or more central processing units (CPUs) or graphics processing units (GPUs), and each processing unit may implement one or more hardware threads. The computer device 1502 may also include any memory 1506, which is used to store any kind of information such as code, settings, data, etc. In a specific embodiment, the computer program on the memory 1506 and can be run on the processor 1504, when the computer program is run by the processor 1504, the instructions of the method described in any of the above embodiments may be executed. Non-limitingly, for example, the memory 1506 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 1502. In one embodiment, when the processor 1504 executes the associated instructions stored in any memory or combination of memories, the computer device 1502 can perform any operation of the associated instructions. The computer device 1502 also includes one or more drive mechanisms 1508 for interacting with any memory, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0173] The computer device 1502 may also include an input / output interface 1510 (I / O) for receiving various inputs (via input devices 1512) and for providing various outputs (via output devices 1514). A specific output mechanism may include a presentation device 1516 and an associated graphical user interface 1518 (GUI). In other embodiments, the input / output interface 1510 (I / O), input device 1512, and output device 1514 may not be included, and the computer device 1502 may be used as a computer device in a network. The computer device 1502 may also include one or more network interfaces 1520 for exchanging data with other devices via one or more communication links 1522. One or more communication buses 1524 couple the components described above together.

[0174] The communication link 1522 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 1522 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0175] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), computer-readable storage media, and computer program products of some embodiments of the present specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processor to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processor generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0176] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processor to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processor so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0178] In a typical configuration, a computer device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0179] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0180] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computer device. As defined in this specification, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0181] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0182] The present specification embodiments may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present specification embodiments may also be practiced in distributed computing environments where tasks are performed by remote processors connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0183] It should also be understood that in the embodiments of this specification, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0184] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0185] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0186] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A geosteering method, characterized in that: The method comprises: Establish a three-dimensional geological model based on the well logging data and seismic data of the target block; Optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model according to the optimized seismic data; wherein the space-varying wavelet in the three-dimensional geological model is obtained by interpolating the seismic wavelet; and the seismic wavelet is extracted from the seismic data; The reconstructed 3D geological model is adjusted using the logging while drilling curve to obtain a 3D geosteering model; Determine whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data, and if not, repeat the above steps to adjust the seismic data to update the three-dimensional geosteering model; The geosteering of the target block is determined according to the three-dimensional geosteering model.

2. The method according to claim 1, characterized in that The three-dimensional geological model is established based on the well logging data and seismic data of the target block, including: Determine rock physical information and lithology combination information according to the well logging data; Using the well logging data and seismic data to construct a synthetic seismic record of the target block, and performing well-seismic calibration processing on the synthetic seismic record; Extract the seismic phase position and seismic response characteristics of the target layer in the adjacent wells based on the well-seismic calibration results; The seismic horizon interpretation results of the target layer of the target well are obtained through the seismic phase position and seismic response characteristics of the target layer of the adjacent well; A three-dimensional geological model is established based on the seismic horizon interpretation results, the rock physics information and the lithology combination information.

3. The method according to claim 2, characterized in that The step of constructing a synthetic seismic record of the target block by using the well logging data and seismic data includes: Using standard Ricker wavelet to adjust the time-depth relationship of the logging data; Determine the logging reflection coefficient corresponding to the logging data after adjusting the time-depth relationship; extracting seismic wavelets from the seismic data; The synthetic seismic record is constructed using the seismic wavelet and the well logging reflection coefficient.

4. The method according to claim 1, characterized in that: The step of optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model comprises: The space-varying wavelet is used to perform deconvolution processing on the seismic data to obtain optimized seismic data.

5. The method according to claim 2, characterized in that: Before establishing the three-dimensional geological model based on the well logging data and seismic data of the target block, the following steps are also included: Preprocessing the well logging data to eliminate abnormal values ​​in the well logging data; A well logging response characteristic prediction model is established using the well logging data to predict the well logging response characteristic data of the target well.

6. The method according to claim 5, characterized in that The three-dimensional geological model reconstructed by adjusting the logging while drilling curve includes: Real-time acquisition of logging while drilling data; Establishing a logging while drilling curve corresponding to the logging while drilling data; The reconstructed three-dimensional geological model is forward modeled using a well logging response characteristic prediction model to obtain a forward modeled well logging curve; The inclination angle and thickness parameters in the reconstructed three-dimensional geological model are adjusted so that the adaptability between the forward logging curve and the logging while drilling curve reaches a first threshold.

7. The method according to claim 1, characterized in that Determine whether the target layer data in the 3D geosteering model matches the seismic layer interpretation results corresponding to the optimized seismic data, including: Extracting reservoir data from the seismic horizon interpretation result; Calculating the matching degree between the target layer data and the reservoir data; If the matching degree is greater than the second threshold, the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data, otherwise they do not match.

8. The method according to claim 1, characterized in that Determining the geosteering of the target block according to the three-dimensional geosteering model further includes: According to the three-dimensional geosteering model, a sweet spot prediction position of the target layer is obtained; If the predicted sweet spot position does not match the actual drilling situation, the three-dimensional geosteering model is updated using the method described in claims 1-7, and the phase spectrum of the space-varying wavelet is adjusted during the updating process.

9. A geosteering device, characterized in that: The device comprises: Establish a module for building a three-dimensional geological model based on well logging data and seismic data of the target block; An optimization module, used for optimizing the seismic data according to the space-varying wavelet in the three-dimensional geological model, and reconstructing the three-dimensional geological model according to the optimized seismic data; wherein the space-varying wavelet in the three-dimensional geological model is obtained by interpolating the seismic wavelet; and the seismic wavelet is extracted from the seismic data; An adjustment module is used to adjust the reconstructed three-dimensional geological model using the logging while drilling curve to obtain a three-dimensional geosteering model; An updating module is used to determine whether the target layer data in the three-dimensional geosteering model matches the seismic layer interpretation result corresponding to the optimized seismic data. If not, repeat the above steps to adjust the seismic data to update the three-dimensional geosteering model; The guidance module is used to determine the geo-steering of the target block according to the three-dimensional geo-steering model.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: When the computer program is executed by the processor, the computer program executes the instructions of the method according to any one of claims 1 to 8.

11. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor of a computer device, the computer program executes the instructions of the method according to any one of claims 1 to 8.

12. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the instructions of the method according to any one of claims 1 to 8 are executed.

Images