Method, system and equipment for determining liquid production capacity of breaking joint body, medium and product

Abstract

The invention discloses a method, a system, equipment, a medium and a product for determining the liquid production capacity of a breaking joint body, and relates to the field of geophysical exploration and logging, and the method comprises the steps: obtaining three-dimensional seismic data, well location data, logging and logging data, horizon interpretation data, well layering data and well trajectory data of a target work area; according to the obtained data, the fractured zone seepage capacity, the fractured zone seepage capacity and the sandstone thickness of the horizontal section of the target well in the target work area are extracted; determining a fault-fracture-sand comprehensive index according to the seepage capacity of the fracture zone, the seepage capacity of the fracture zone and the sandstone thickness; according to the fault-fracture-sand comprehensive index, the liquid production capacity of a target well in the target work area is determined through a liquid production capacity prediction model; wherein the liquid production capacity prediction model is obtained by fitting the fault-fracture-sand comprehensive index and the corresponding liquid production capacity of each well in the research work area. According to the method, the actual productivity benefit of the breaking joint body can be accurately represented.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration and well logging, and in particular to a method, system, equipment, medium and product for determining the fluid production of a fracture body. Background Art

[0002] Fractures are generated under various geological activities. Their development is controlled by the brittleness of rocks and has an important impact on oil and gas migration and seepage. Faults occur during tectonic movement and are a type of structure with significant relative displacement along both sides of the fracture surface. Faults vary in size, with large ones extending hundreds of kilometers along the strike and small ones only tens of centimeters. A system composed of many faults can be called a fault zone. Faults play a dual role in the formation of oil and gas reservoirs. They serve as the main channel for oil and gas migration and promote the accumulation of oil and gas through their sealing effect. The fault body is a system composed of faults, associated brittle fracture zones and the surrounding transformed dense low-density sandstones. Its upper and side parts contain impermeable mudstone layers and other obstructions. The accumulation of oil and gas in the fault body is called a fault body reservoir, which is a type of reservoir with great potential. At present, the U-ResUNet deep learning model is used to identify faults in all strata in the Zhenjing block of the Ordos Basin. In addition, based on the analysis of seismic, core, imaging logging and other data, the fracture response characteristics and fault reservoir development patterns are described in detail from different scales. The fault identification method has been verified through the analysis of drilling data and fracturing data. In addition, a large number of seismic and logging interpretation results are used to describe the characteristics of fault bodies in detail from the perspective of fault body evolution mechanism, and then systematically explore the control of fault bodies on oil and gas.

[0003] In summary, the identification of fault bodies and the prediction of their actual production capacity are particularly important for oil and gas exploration deployment decisions. However, in the past, predictions and evaluations were mostly carried out on single factors. For example, for faults, a variety of technical means, such as coherence bodies and curvatures, can be used to characterize their geometric shapes, but there is a lack of prediction of their seepage capacity; for fractures, core observation methods, geophysical prediction methods, etc. can be used to describe and predict their morphological characteristics and density, but their contribution to production capacity cannot be quantitatively evaluated. The fault body is composed of multiple factors such as faults, fractures, and lithology. The production capacity of a single well drilling into the fault body is also the result of the combined action of these multiple factors. Therefore, it is necessary to build a system for comprehensive evaluation. Summary of the invention

[0004] The purpose of this application is to provide a method, system, equipment, medium and product for determining the liquid production of a fracture body, which can accurately characterize the actual production capacity and efficiency of the fracture body.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a method for determining the amount of fluid produced in a fracture body, comprising: Obtain 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data in the target work area; Based on 3D seismic data, well location data, logging and mud recording data, layer interpretation data, well stratification data and well trajectory data, the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area are extracted; Determine the fault-fracture-sand comprehensive index based on the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone; According to the comprehensive indicators of faults, fractures and sands, the liquid production of the target wells in the target work area is determined using the liquid production prediction model; among them, the liquid production prediction model is obtained by fitting the comprehensive indicators of faults, fractures and sands and the corresponding liquid production of each well in the study work area.

[0006] Optionally, the fault-fracture-sand comprehensive index is determined according to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone, including: The seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone are normalized respectively to obtain the treated seepage capacity of the broken zone, the treated seepage capacity of the fracture zone and the treated thickness of the sandstone; Using the formula Determine the fault-fracture-sand comprehensive index; where a is the seepage capacity weight of the fracture zone; is the seepage capacity of the fracture zone after treatment; b is the weight of the seepage capacity of the fracture zone; is the seepage capacity of the treated fracture zone; c is the weight of sandstone thickness; is the thickness of sandstone after treatment; FFS is the comprehensive index of fault-fracture-sand.

[0007] Optionally, the liquid production prediction model is: Y=d×FFS+e; Among them, FFS is the comprehensive index of fault-fracture-sand; Y is the liquid production of the target well in the target work area; d and e are unknown coefficients.

[0008] Optionally, the fault-fracture-sand comprehensive index and the corresponding liquid production of each well in the study area are fitted to obtain a liquid production prediction model, specifically including: Obtain 3D seismic data, well location data, logging and well data, stratigraphic interpretation data, well stratification data and well trajectory data in the study area; Based on the 3D seismic data, well location data, logging and mud logging data, stratigraphic interpretation data, well stratification data and well trajectory data of the research area, the fracture zone seepage capacity, fracture zone seepage capacity, sandstone thickness and daily average liquid production of the horizontal sections of a set number of horizontal wells in the research area are extracted; According to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone, the fault-fracture-sand comprehensive index expression is established; The broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal sections of a set number of horizontal wells in the research area were normalized to obtain the treated broken zone seepage capacity, treated fracture zone seepage capacity and treated sandstone thickness. Determine the seepage capacity weight of the fracture zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness; Using the fault-fracture-sand comprehensive index expression Determine the fault-fracture-sand comprehensive index of the horizontal section of a set number of horizontal wells in the study area; where a is the seepage capacity weight of the fracture zone; is the seepage capacity of the fracture zone after treatment; b is the weight of the seepage capacity of the fracture zone; is the seepage capacity of the treated fracture zone; c is the weight of sandstone thickness; is the thickness of the sandstone after treatment; FFS is the comprehensive index of fault-fracture-sand; The fault-fracture-sand comprehensive indicators and the corresponding daily average liquid production of the horizontal sections of a set number of horizontal wells in the study area were fitted to obtain a liquid production prediction model.

[0009] Optionally, the process of determining the fracture zone seepage capacity weight, the fracture zone seepage capacity weight and the sandstone thickness weight specifically includes: The first correlation between the seepage capacity of the fracture zone and the average daily liquid production, the second correlation between the seepage capacity of the fracture zone and the average daily liquid production, and the third correlation between the thickness of the sandstone and the average daily liquid production were determined respectively; According to the first correlation, the second correlation and the third correlation, the seepage capacity weight of the broken zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness are determined respectively.

[0010] Optionally, according to the first correlation, the second correlation and the third correlation, the broken zone seepage capacity weight, the fracture zone seepage capacity weight and the sandstone thickness weight are determined respectively, specifically including: Using the formula Determine the seepage capacity weight of the fracture zone; Using the formula Determine the weight of fracture zone seepage capacity; Using the formula Determine the sandstone thickness weight; Among them, A is the first correlation; B is the second correlation; C is the third correlation.

[0011] In a second aspect, the present application provides a system for determining the amount of liquid produced by a fracture body, comprising: Data acquisition module, used to obtain 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data of the target work area; The parameter extraction module is used to extract the fracture zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area based on 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data; A comprehensive index determination module is used to determine the fault-fracture-sand comprehensive index based on the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone; The liquid production determination module is used to determine the liquid production of the target well in the target work area based on the comprehensive indicators of faults, fractures and sands and use the liquid production prediction model; wherein the liquid production prediction model is obtained by fitting the comprehensive indicators of faults, fractures and sands of each well in the study area and the corresponding liquid production.

[0012] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-described methods for determining the amount of fluid produced in a fracture body.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for determining the amount of liquid produced in a fracture body.

[0014] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for determining the amount of liquid produced in a fracture body.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects: The present application provides a method, system, equipment, medium and product for determining the liquid production of a fracture body, which obtains three-dimensional seismic data, well location data, logging and mud logging data, stratigraphic interpretation data, well stratification data and well trajectory data of a target work area; extracts the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of a horizontal section of a target well in the target work area based on the three-dimensional seismic data, well location data, logging and mud logging data, stratigraphic interpretation data, well stratification data and well trajectory data; determines the fault-fault-sand comprehensive index based on the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness; determines the liquid production of a target well in the target work area based on the fault-fault-sand comprehensive index using a liquid production prediction model; wherein the liquid production prediction model is obtained by fitting the fault-fault-sand comprehensive index and the corresponding liquid production of each well in the study work area. This application is based on the formation process of the fault body, fully combines the main controlling factors that affect its development, and calculates the correlation between the three and the liquid production by statistically analyzing the seepage capacity of the horizontal section of the horizontal well of the fault body, the seepage capacity of the fracture zone, and the sandstone thickness data information, combined with the actual liquid production information of the horizontal well, and using this to obtain the weights represented by each category. In this way, the fault-fracture-sand comprehensive index FFS is constructed to characterize the liquid production information of the fault body, so as to accurately characterize the actual production capacity benefits of the fault body. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A schematic flow chart of a method for determining the amount of liquid produced by a fracture body provided in one embodiment of the present application; Figure 2 A system flow chart in an example of the present application; Figure 3 This is a statistical diagram of the seepage capacity data of the broken zone in an example of this application; Figure 4 This is a statistical diagram of fracture zone seepage capacity data in an example of the present application; Figure 5 A correlation heat map in an example of the present application; Figure 6 It is a fitting diagram of the comprehensive index FFS and liquid production in an example of this application; Figure 7 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0020] The present application can make up for the problems in the background technology very well. It is based on the formation process of the fracture body and fully combines the main controlling factors affecting its development. By statistically analyzing the seepage capacity of the horizontal section of the fracture zone, the seepage capacity of the fracture zone, and the sandstone thickness data information of the horizontal well with the actual liquid production information of the horizontal well, the correlation between the three and the liquid production is calculated and the weights represented by each category are obtained. In this way, the comprehensive evaluation index FFS of the fracture body is constructed to characterize the liquid production information of the fracture body, which effectively depicts the production capacity efficiency of the fracture body and has important practical significance for the oil and gas exploration industry.

[0021] In an exemplary embodiment, Figure 1 As shown, a method for determining the amount of liquid produced by a fracture body is provided, comprising the following steps: S1: Obtain 3D seismic data, well location data, logging and mud recording data, layer interpretation data, well stratification data and well trajectory data of the target work area.

[0022] S2: Based on 3D seismic data, well location data, logging and mud recording data, stratigraphic interpretation data, well stratification data and well trajectory data, the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area are extracted.

[0023] S3: Determine the fault-fracture-sand comprehensive index based on the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone.

[0024] As an optional implementation, S3 specifically includes: The seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone are normalized respectively to obtain the treated seepage capacity of the broken zone, the treated seepage capacity of the fracture zone and the treated thickness of the sandstone.

[0025] Using the formula Determine the fault-fracture-sand comprehensive index; where a is the seepage capacity weight of the fracture zone; is the seepage capacity of the fracture zone after treatment; b is the weight of the seepage capacity of the fracture zone; is the seepage capacity of the treated fracture zone; c is the weight of sandstone thickness; is the thickness of sandstone after treatment; FFS is the comprehensive index of fault-fracture-sand.

[0026] S4: According to the comprehensive index of fault-fracture-sand, the liquid production prediction model is used to determine the liquid production of the target well in the target work area; wherein, the liquid production prediction model is obtained by fitting the comprehensive index of fault-fracture-sand and the corresponding liquid production of each well in the study work area.

[0027] As an optional implementation, the liquid production prediction model is: Y=d×FFS+e.

[0028] Among them, FFS is the comprehensive index of fault-fracture-sand; Y is the liquid production of the target well in the target work area; d and e are unknown coefficients.

[0029] As an optional implementation method, the fault-fracture-sand comprehensive index and the corresponding liquid production of each well in the study area are fitted to obtain a liquid production prediction model, which specifically includes: Step 1: Obtain 3D seismic data, well location data, logging and mud logging data, stratigraphic interpretation data, well stratification data, and well trajectory data for the study area.

[0030] In practical applications, such as Figure 2 As shown, the geological software - SMI software was used to establish the research area, import 3D seismic data, well location data, logging and well recording data, stratigraphic interpretation data, well stratification data, well trajectory data, and produce synthetic seismic records of the wells in the work area.

[0031] SMI software, the full name of which is Seismic Waveform Indication Inversion Software, is a high-precision phase-controlled reservoir prediction platform that can carry out seismic intelligent interpretation, rock physics modeling, pre-stack and post-stack inversion, etc.

[0032] Three-dimensional seismic data is obtained through seismic exploration technology. Seismic exploration is a geophysical exploration method that mainly uses the elasticity and density differences of underground media to infer the properties and morphology of underground rock formations by observing and analyzing the response of the earth to artificially excited seismic waves.

[0033] Three-dimensional seismic data refers to: explosives are placed on the ground or in the soil, and the vibrations generated by detonating the explosives are transmitted to the deep underground. This vibration is recorded in the form of waveforms, and the reflected waves are received by the detector. The received waveform data can be used to know the real situation of the underground rock formation. The technicians process the received data, such as noise reduction and smoothing, to obtain a three-dimensional seismic data body. The data format is a data file with the ".sgy" suffix commonly used in the field of petroleum geology. Sgy files usually contain data such as line number iline, channel number xline, depth Time (ms), and are three-dimensional volume data.

[0034] Well location data refers to the well location coordinate data of actual wells drilled during the actual well deployment process.

[0035] Well logging and mud recording data are data collected during the drilling process in the field of petroleum engineering. They are important information used to describe the properties of underground rock formations, geological structures, and storage conditions.

[0036] The logging data used in this embodiment include three logging curves: acoustic time difference logging curve, density logging curve, and deep induction resistivity logging curve. Among them, the acoustic time difference and density logging curves are used to make synthetic seismic records.

[0037] Then, the characteristics of the broken zone in the logging are calibrated by the abnormal response of the three logging curves when the drilling encounters the broken zone. The logging data used is the leakage and overflow data, because the simple definition of the broken zone is the location where the rock breaks during the fracture formation process. At this time, during the logging process, the drilling fluid will undergo abnormal changes, which is the so-called leakage and overflow data. For example, t tons are lost.

[0038] The necessity of synthetic seismic records: It has been explained above that most earthquakes use time domain depth (ms), which means that the travel time of the reflected wave from a certain depth is n milliseconds, but the well depth is the real depth (m). The two have different units and cannot be directly compared. Therefore, synthetic seismic records are needed to convert the time depth ms on the earthquake with the depth m on the well logging, that is, time-to-depth conversion. After the conversion, the well logging depth can correspond to the depth on the earthquake.

[0039] The stratigraphic interpretation data is the time-depth data of the interface positions of different underground rock layers determined through the analysis and interpretation of seismic data.

[0040] Because different rock formations have different properties, including resistivity, density, porosity, etc., the responses in seismic and well logging will also be different. The final well stratification data, for example: Well name: P1, layer: Chang 8 top, depth: 2200m.

[0041] Well name: P1, layer: Chang 8 low, depth: 2400m.

[0042] The stratigraphic interpretation data and well stratification data are actually stratigraphic names divided from the perspective of seismic and well respectively. For example, t6c corresponds to seismic, and Chang 8 top corresponds to well. Both actually refer to the same stratigraphic position.

[0043] Well stratification data is the depth data about the interface positions of different rock formations in the well, which is divided through well core analysis and logging data characteristics during the oil and gas exploration and development process.

[0044] The principle of synthetic seismic recording is to artificially convert acoustic logging or vertical seismic profile data into seismic records. It is a very widely used type of seismic model technology and is also the basis for work such as layer calibration and reservoir description.

[0045] In this embodiment, the post-stack seismic data of the boundary range of the Yongzheng and Yulinzi fault zones in the Binchang block of the Ordos Basin are imported into the work area, and the well location data, logging and well recording data, target layer segment interpretation data, well stratification data, and well trajectory data are loaded together. Based on the loaded actual drilled fracture body horizontal well data, "well-seismic" calibration is performed to complete the production of synthetic seismic records. This embodiment is based on the data of 19 typical horizontal wells in the study area and conducts subsequent research.

[0046] Step 2: Based on the 3D seismic data, well location data, logging and mud recording data, stratigraphic interpretation data, well stratification data and well trajectory data of the study area, extract the broken zone seepage capacity, fracture zone seepage capacity, sandstone thickness and average daily liquid production of the horizontal sections of a set number of horizontal wells in the study area.

[0047] In practical applications, based on the research area established in step 1, combined with the logging, mud logging and seismic information of the horizontal wells with actual fracture bodies at the location where the fracture zone is developed, the seepage capacity of the fracture zone of the horizontal wells is statistically analyzed through leakage, overflow, abnormal response of the logging curve and whether there is obvious phase axis misalignment on the actual seismic profile.

[0048] Loss and overflow data refer to the phenomenon that the drilling fluid changes when encountering fractures. It is an important parameter used to reflect the characteristics of formation fluids. It is of great significance for accurately evaluating reservoir properties, designing reasonable drilling process plans, and ensuring safe production.

[0049] The fracture zone refers to a structural unit within the fracture system. When the rock layer is subjected to tectonic stress, the weak part will break and form fissures. As the number of fissures increases and they combine to form a fracture surface, the rock layer will be pulled apart along the fracture surface under the action of stress to form a cavity, and the surrounding broken rocks will fill in to form a fracture zone. The fracture zone has an important impact on the transportation and accumulation of oil and gas.

[0050] In practical applications, based on the research area established in step 1, combined with the seismic response of the horizontal wells of the fractured body drilled, and the data of logging and mud logging data at the location of the fractured zone development, firstly, observe whether there is an obvious phase axis misalignment phenomenon at the location of the fractured zone on the seismic profile. If there is an obvious misalignment, it is preliminarily marked as the location of the fractured zone development; if there is no obvious misalignment, only flexural deformation is present, which is considered to be an abnormal seismic response caused by cracks, which does not conform to the actual definition of the fractured zone; secondly, through the abnormal response of the logging curve in the fractured zone, the acoustic time difference logging data value greater than 235, the deep induction resistivity logging data value between 10-20, and the density logging data value between 2.4-2.55 are statistically analyzed to further determine the development mode of the fractured zone in the logging; finally, by combining the first two fractured zone laws and the leakage and overflow locations that occurred in the mud logging, the seepage capacity of the horizontal section of the fractured zone is comprehensively statistically analyzed. The seepage capacity of the fractured zone in the horizontal section of the actual drilling well is as follows: Figure 3 shown.

[0051] Based on step 1, the three-dimensional seismic data of the study area are filtered to improve the seismic quality. On the basis of filtering, the fracture density along-layer slice extraction near the target layer is carried out to characterize the development and distribution of fractures on the plane, and the fracture density limit threshold is limited to statistically analyze the seepage capacity data of the horizontal fracture zone under this along-layer slice.

[0052] The target layer section is the main stratigraphic interpretation position in the actual study area.

[0053] Along-layer slicing refers to the slice attributes extracted along a certain interpretation layer, which is used to reflect the attribute changes along the layer.

[0054] The fracture zone is a structural unit inside the fault body. It means that during tectonic activities, in addition to the geological forces that are mostly consumed at the location of the fracture zone, the forces will continue to transform the rock strata on both sides of the fracture zone, causing them to fold and deform, thus generating cracks. Such areas with densely developed fractures are called fracture zones.

[0055] In practical applications, based on step 1, due to the poor seismic quality of the Binchang block on the southern edge of the Ordos Basin, the seismic signal-to-noise ratio is relatively low, and the block as a whole is in a strike-slip background, a large number of hidden faults are developed, and the actual fault distance is small, which is difficult to effectively identify on the seismic profile, which will have a great impact on the interpretation of faults and cracks. Therefore, this application enhances the continuity of seismic synclines by constructing guided filtering technology to improve the quality of seismic data. Based on the seismic body processed by filtering technology, its multi-channel coherence attributes are calculated to complete the characterization of small and medium-scale faults in the work area. Among them, the multi-channel coherence attribute is an upgraded version of the coherence attribute, which is better for identifying small-scale faults. Then, the fracture simulation slice function module in the SMI software was used to extract the interlayer fracture simulation slice of the target layer t6c based on the multi-channel coherent attributes, and further fine-detailed characterization of the microfractures in the work area was completed. The horizontal well was projected on the horizontal segment of the interlayer fracture simulation slice, and a certain threshold limit was imposed on the fracture density. After research and experiments, it was found that when the threshold value was greater than or equal to 0.4, it was consistent with the actual drilling fracture zone analysis. Therefore, this embodiment was limited based on the threshold value of 0.4, and the seepage capacity of the fracture zone with a fracture density greater than 0.4 was counted, realizing the acquisition of the seepage capacity data of the horizontal fracture zone. The seepage capacity of the horizontal fracture zone in a part of the study area is as follows: Figure 4 shown.

[0056] Based on step 1, according to the interpreted sand body planar development results in the study area, the average sandstone thickness along the horizontal section is counted through the different layer sections encountered by the actual horizontal wells, and the sandstone thickness statistics of the horizontal section under the main drilling target layer section are completed.

[0057] Sandstone thickness refers to the actual thickness of sandstone developed inside the fault body.

[0058] The planar development results of sand bodies refer to the relevant data and analysis results used to describe and explain the formation, evolution and spatial distribution of a sedimentary layer containing sandstone (i.e., sand body) in sedimentary geology.

[0059] Based on the research area established in step 1, the main controlling factors affecting the fluid production of the fault body are comprehensively analyzed. The relevant data of the main controlling factors on the horizontal section of the horizontal wells in the actual drilled fault body are statistically analyzed: the seepage capacity of the broken zone, the seepage capacity of the fracture zone, and the sandstone thickness data. Based on this data, the fault-fracture-sand comprehensive index FFS is established to characterize the actual fluid production information.

[0060] Step 3: According to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone, a comprehensive index expression of fault-fracture-sand is established.

[0061] The productivity study of the wells drilled in the fault body this time comprehensively considers the three influencing factors: the seepage capacity of the broken zone, the seepage capacity of the fracture zone, and the thickness of the sand body. The actual data of each item is multiplied by the corresponding weight, and the weighted multiplication results are accumulated along the well trajectory to obtain the comprehensive FFS result of the actual drilling well. That is, the larger the cumulative sum of the three data multiplied by the weight, the better the actual productivity benefit. Therefore, the final constructed FFS index is: .

[0062] Among them, the seepage capacity of the broken zone is based on the research area established in step 1, combined with the seismic response of the horizontal well of the actual drilled fracture body and the data of logging and mud logging data at the location where the broken zone is developed. First, observe on the seismic profile whether there is an obvious phase axis misalignment phenomenon at the location of the broken zone. If there is an obvious misalignment, it is preliminarily marked as the location where the broken zone is developed; secondly, through the abnormal response of the actual drilling well logging curve in the broken zone, the acoustic time difference logging data value is greater than 235, the deep induction resistivity logging data value is between 10-20, and the density logging data value is between 2.4-2.55 to further determine the development information of the broken zone in the logging; finally, by combining the first two broken zone laws and the leakage and overflow locations that occurred in the mud logging, the horizontal section of the broken zone with strong seepage capacity development information is finally comprehensively marked. Figure 3 The figure shows a statistical diagram of the strong seepage capacity data of the broken zone in the horizontal section of the actual drilling. At the same time, by using the SMI software to extract structural seismic attributes in the geological work area, this embodiment uses a total of five types of seismic attribute data, namely variance, frequency attenuation, similarity, maximum positive curvature, and minimum negative curvature. On this basis, the seismic attributes beside the well are extracted, and the position of the statistical data points of the strong seepage capacity of the broken zone is combined with the idea of ​​'well-seismic' to make a supervised learning model sample set. Based on the Pytorch deep learning framework, a neural network model is constructed to carry out model training for this sample. Based on the trained model, the five seismic attribute bodies extracted in the geological software are sent to the network to carry out the prediction of the development degree of the strong seepage capacity of the broken zone in the actual work area without the interpretation conclusion of the broken zone. The model prediction accuracy is shown in Table 1. It can be seen from Table 1 that the final weighted average accuracy of the model can reach about 90%, and the prediction effect of the actual broken zone seepage capacity is good.

[0063] Table 1 Model accuracy data table

[0064] Since there is no seismic attribute that can effectively characterize the seepage capacity of fractures, the fracture density in the extracted t6c fracture slice along the layer is used to reflect the fracture seepage capacity. The greater the fracture density, the more fractures are developed at this location, and the easier it is to form a cross-fracture network, and its seepage capacity will be enhanced. Therefore, this paper uses fracture density data to reflect the strength of fracture seepage capacity. Based on the seismic data input in step 1, the continuity of the seismic phase axis is first enhanced through structural guidance filtering, and then multi-channel coherent attributes are extracted on this basis. Then, the fracture simulation slice function module in the SMI software is used to extract the simulated slice of the fracture along the layer of the target layer segment t6c based on the multi-channel coherent attributes, so as to obtain the fracture density development plan of the target layer. The statistical diagram of the seepage capacity of the specific fracture zone is shown in the figure. Figure 4 As shown, P8, P27, and P31-36 are the names of some horizontal wells. Combined with the information presented on the fracture density plane map of the horizontal wells in the actual drilling fault body, it is determined that the position where the normalized fracture density in the software is greater than 0.4 is determined as a fracture-intensive area, that is, the fracture zone seepage capacity development area.

[0065] Sandstone thickness, based on step 1, according to the interpreted sand body plane development results in the study area, through the different layers encountered by the actual horizontal wells, the average sandstone thickness along the horizontal section is counted, and the average sand body thickness statistics of the horizontal section under the main drilling target layer are completed.

[0066] Step 4: Normalize the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal sections of a set number of horizontal wells in the study area to obtain the treated broken zone seepage capacity, treated fracture zone seepage capacity and treated sandstone thickness.

[0067] Step 5: Determine the seepage capacity weight of the broken zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness.

[0068] As an optional implementation method, the process of determining the fracture zone seepage capacity weight, the fracture zone seepage capacity weight and the sandstone thickness weight specifically includes: Step 51: respectively determine the first correlation between the seepage capacity of the broken zone and the average daily liquid production, the second correlation between the seepage capacity of the fracture zone and the average daily liquid production, and the third correlation between the sandstone thickness and the average daily liquid production.

[0069] Step 52: According to the first correlation, the second correlation and the third correlation, respectively determine the seepage capacity weight of the broken zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness, specifically including: Using the formula Determine the seepage capacity weight of the fracture zone.

[0070] Using the formula Determine the permeability weight of the fracture zone.

[0071] Using the formula Determines the sandstone thickness weight.

[0072] Among them, A is the first correlation; B is the second correlation; C is the third correlation.

[0073] In practical applications, based on the comprehensive index FFS of fracture body fluid production initially established in step 2, the main controlling factor data of fluid production of actually drilled fracture body wells and the actual fluid production information of each well are statistically analyzed. Based on this data, the correlation value between the main controlling factor and the target variable (fluid production) is calculated, and the actual weight of each data in the FFS comprehensive index is further calculated using the correlation value.

[0074] Based on step 2, combined with the cumulative number of data points of seepage capacity in the horizontal section of the broken zone, the cumulative number of data points of seepage capacity in the fracture zone, the sand body thickness data and the daily average liquid production data of each horizontal well of the 19 typical horizontal wells in the research area, the first three data of the first 16 horizontal wells were selected as independent variables, and the liquid production data was selected as the dependent variable. The correlation between each variable and the dependent variable was calculated. The thermal coefficient of the correlation between each variable and the dependent variable is shown in the figure below: Figure 5 As shown. Figure 5 It can be seen that the correlation between the seepage capacity of the broken zone and the liquid production is the largest, with a specific value of 0.59, and the seepage capacity of the fracture zone and the sandstone thickness are the second, 0.36 and 0.47 respectively, which is consistent with the geological understanding of the actual work area. This shows that under the condition of the same sand body development, the seepage capacity of the broken zone is the main contributing unit to the production capacity of the fault body, and the effect of the fracture on the seepage and conduction of oil and gas is smaller than the actual impact of the broken zone.

[0075] In order to eliminate the differences in the numerical dimensions of the three, this embodiment normalizes the data of the three and linearly scales them to the range of [0-1]. Then, the calculated correlation data of the three items is divided by the cumulative sum of the correlations of the three items to obtain the weight occupied by each category. The specific weight calculation principle is shown in formulas (1)-(3), and the normalization calculation principle is shown in formula (4): (1) (2) (3) (4) Among them: x' is the normalized data; x is the data to be normalized. min With x max Respectively represent the minimum and maximum values ​​in the data column to be normalized.

[0076] Step 6: Use the fault-fracture-sand comprehensive index expression Determine the comprehensive fault-fracture-sand indices of the horizontal sections of a set number of horizontal wells in the study area.

[0077] Step 7: Fit the fault-fracture-sand comprehensive indicators and the corresponding daily average liquid production of the horizontal sections of a set number of horizontal wells in the study area to obtain a liquid production prediction model.

[0078] Based on the weight data obtained in step 6, the liquid production information of the horizontal wells in the fractured body of the actual drilling is combined with the FFS comprehensive index to calculate and fit the calculated FFS index results to obtain the final formula for quantitatively predicting liquid production using the FFS comprehensive index, and then bring it into the posterior well for calculation to evaluate the generalization performance of the FFS comprehensive index on the prediction accuracy of liquid production.

[0079] The FFS data were fitted with the actual liquid production to characterize the liquid production information of the fracture body. The fitting coefficients d=0.03426 and e=0.56878 were obtained, and the fitting formula was Y=0.03426×FFS+0.56878.

[0080] Liquid production data refers to the total amount of fluid that can be stably extracted from a wellhead (i.e., a well) every day after a period of production during the drilling process. These fluids usually include oil, natural gas, and water.

[0081] The fault-fracture-sand comprehensive index FFS established in this application combines the broken zone "Fault", fracture density "Fracture", sand body "Sand" and liquid production data, and comprehensively characterizes the liquid production information of the fault body through these three main factors affecting the liquid production of the fault body.

[0082] The final fitting relationship is obtained by fitting the calculated 16 FFS index data with the corresponding liquid production data, and the data of 3 wells that do not participate in the actual weight calculation are used for verification to characterize the information of the fracture body liquid production. The final fitting relationship between the comprehensive index FFS and the liquid production is shown in the figure below: Figure 6 As shown, from Figure 6 It can be seen that the fitting degree of 16 wells can reach 0.82, which is significantly improved compared with the correlation between the three factors and the liquid production separately. Figure 6It can also be seen from the verification wells in that the verification wells that did not actually participate in the correlation calculation also showed good generalization in the end, and their data were all near the fitting line. This fully demonstrates that the production efficiency of the fault body is jointly restricted by multiple factors and is difficult to be effectively characterized by a single variable. The FFS index constructed in this application based on the genetic mechanism and controlled factors of the fault body and fully combining the geological and mathematical perspectives can solve this problem well, and the characterization accuracy of the liquid production can reach 82%, providing effective data support for actual oilfield exploration and development.

[0083] Based on the same inventive concept, the embodiment of the present application also provides a system for implementing the above-mentioned fracture body liquid production determination system. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in the fracture body liquid production determination system embodiment provided below can refer to the limitations of the fracture body liquid production determination method above, and will not be repeated here.

[0084] In an exemplary embodiment, a system for determining the amount of fluid produced in a fracture body is provided, comprising: The data acquisition module is used to obtain three-dimensional seismic data, well location data, logging and mud logging data, layer interpretation data, well stratification data and well trajectory data of the target work area.

[0085] The parameter extraction module is used to extract the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area based on three-dimensional seismic data, well location data, logging and mud recording data, layer interpretation data, well stratification data and well trajectory data.

[0086] The comprehensive index determination module is used to determine the fault-fracture-sand comprehensive index according to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone.

[0087] The liquid production determination module is used to determine the liquid production of the target well in the target work area based on the comprehensive indicators of faults, fractures and sands and use the liquid production prediction model; wherein the liquid production prediction model is obtained by fitting the comprehensive indicators of faults, fractures and sands of each well in the study area and the corresponding liquid production.

[0088] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above-mentioned method for determining the amount of fluid produced in a fracture body when executing the computer program.

[0089] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the method for determining the amount of liquid produced in a fracture body described above is implemented.

[0090] In an exemplary embodiment, a computer program product is provided, including a computer program, which implements the above-mentioned method for determining the amount of fluid produced in a fracture body when executed by a processor.

[0091] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining the amount of liquid produced in a fracture body is implemented.

[0092] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0093] It should be noted that 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 in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0094] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0095] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0096] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0097] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining the amount of liquid produced in a fracture body, characterized in that: include: Obtain 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data in the target work area; Based on 3D seismic data, well location data, logging and mud recording data, layer interpretation data, well stratification data and well trajectory data, the broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area are extracted; Determine the fault-fracture-sand comprehensive index based on the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone; According to the comprehensive indicators of faults, fractures and sands, the liquid production of the target wells in the target work area is determined using the liquid production prediction model; among them, the liquid production prediction model is obtained by fitting the comprehensive indicators of faults, fractures and sands and the corresponding liquid production of each well in the study work area.

2. The method for determining the amount of liquid produced in a fracture body according to claim 1, characterized in that: According to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone, the fault-fracture-sand comprehensive index is determined, including: The seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone are normalized respectively to obtain the treated seepage capacity of the broken zone, the treated seepage capacity of the fracture zone and the treated thickness of the sandstone; Using the formula Determine the fault-fracture-sand comprehensive index; where a is the seepage capacity weight of the fracture zone; is the seepage capacity of the fracture zone after treatment; b is the weight of the seepage capacity of the fracture zone; is the seepage capacity of the treated fracture zone; c is the weight of sandstone thickness; is the thickness of sandstone after treatment; FFS is the comprehensive index of fault-fracture-sand.

3. The method for determining the amount of liquid produced in a fracture body according to claim 1, characterized in that: The liquid production prediction model is: Y = d × FFS + e; Among them, FFS is the comprehensive index of fault-fracture-sand; Y is the liquid production of the target well in the target work area; d and e are unknown coefficients.

4. The method for determining the amount of liquid produced in a fracture body according to claim 1, characterized in that: The fault-fracture-sand comprehensive indicators and corresponding liquid production of each well in the study area are fitted to obtain a liquid production prediction model, which specifically includes: Obtain 3D seismic data, well location data, logging and well data, stratigraphic interpretation data, well stratification data and well trajectory data in the study area; Based on the 3D seismic data, well location data, logging and mud logging data, stratigraphic interpretation data, well stratification data and well trajectory data of the research area, the fracture zone seepage capacity, fracture zone seepage capacity, sandstone thickness and daily average liquid production of the horizontal sections of a set number of horizontal wells in the research area are extracted; According to the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone, the fault-fracture-sand comprehensive index expression is established; The broken zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal sections of a set number of horizontal wells in the research area were normalized to obtain the treated broken zone seepage capacity, treated fracture zone seepage capacity and treated sandstone thickness. Determine the seepage capacity weight of the fracture zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness; Using the fault-fracture-sand comprehensive index expression Determine the fault-fracture-sand comprehensive index of the horizontal section of a set number of horizontal wells in the study area; where a is the seepage capacity weight of the fracture zone; is the seepage capacity of the fracture zone after treatment; b is the weight of the seepage capacity of the fracture zone; is the seepage capacity of the treated fracture zone; c is the weight of sandstone thickness; is the thickness of the sandstone after treatment; FFS is the comprehensive index of fault-fracture-sand; The fault-fracture-sand comprehensive indicators and the corresponding daily average liquid production of the horizontal sections of a set number of horizontal wells in the study area were fitted to obtain a liquid production prediction model.

5. The method for determining the amount of liquid produced in a fracture body according to claim 4, characterized in that: The determination process of the fracture zone seepage capacity weight, the fracture zone seepage capacity weight and the sandstone thickness weight specifically includes: The first correlation between the seepage capacity of the fracture zone and the average daily liquid production, the second correlation between the seepage capacity of the fracture zone and the average daily liquid production, and the third correlation between the thickness of the sandstone and the average daily liquid production were determined respectively; According to the first correlation, the second correlation and the third correlation, the seepage capacity weight of the broken zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness are determined respectively.

6. The method for determining the amount of liquid produced in a fracture body according to claim 5, characterized in that: According to the first correlation, the second correlation and the third correlation, the seepage capacity weight of the broken zone, the seepage capacity weight of the fracture zone and the weight of the sandstone thickness are determined respectively, specifically including: Using the formula Determine the weight of seepage capacity of the fracture zone; Using the formula Determine the weight of fracture zone seepage capacity; Using the formula Determine the sandstone thickness weight; Among them, A is the first correlation; B is the second correlation; C is the third correlation.

7. A system for determining the amount of liquid produced by a fracture body, characterized in that: include: Data acquisition module, used to obtain 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data of the target work area; The parameter extraction module is used to extract the fracture zone seepage capacity, fracture zone seepage capacity and sandstone thickness of the horizontal section of the target well in the target work area based on 3D seismic data, well location data, well logging and mud logging data, layer interpretation data, well stratification data and well trajectory data; A comprehensive index determination module is used to determine the fault-fracture-sand comprehensive index based on the seepage capacity of the broken zone, the seepage capacity of the fracture zone and the thickness of the sandstone; The liquid production determination module is used to determine the liquid production of the target well in the target work area based on the comprehensive indicators of faults, fractures and sands and use the liquid production prediction model; wherein the liquid production prediction model is obtained by fitting the comprehensive indicators of faults, fractures and sands of each well in the study area and the corresponding liquid production.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the amount of fluid produced in a fracture body according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the amount of fluid produced in a fracture body according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining the amount of fluid produced in a fracture body according to any one of claims 1 to 6 is implemented.

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