Method, system and device for identifying fracture network form after reservoir flowback and medium

Abstract

The invention discloses a method, a system and a device for identifying a fracture network form after reservoir flowback and a medium. The method comprises the following steps: acquiring first apparent resistivity data before fracturing of a target reservoir and second apparent resistivity data after flowback; performing small-layer equal-thickness division on the target reservoir to obtain a plurality of target small layers; extracting a plurality of first resistivity plane distribution diagrams from the first apparent resistivity data, and extracting a plurality of second resistivity plane distribution diagrams from the second apparent resistivity data; calculating a plurality of apparent resistivity drop amplitude plane distribution diagrams before and after flowback; calculating a decreasing amplitude boundary value according to the resistivity decreasing amplitude, the lithology weighting parameters, the target thickness and the flattening thickness; if not, the amplitude decreasing boundary value is a first boundary value, and if so, the amplitude decreasing boundary value is a second boundary value; and determining a part enclosed by the decreasing amplitude boundary value as an apparent resistivity decreasing amplitude change main body, and determining a part enclosed by the decreasing amplitude boundary value and a zero value of the resistivity decreasing amplitude as a predicted crack zone. According to the invention, the accuracy of seam net form identification can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field related to oil and gas exploration and development, and in particular, to a method, system, device and medium for identifying the fracture network morphology after reservoir flowback. Background Art

[0002] In the field of unconventional oil and gas resource exploration and development, due to the complex mineral composition and pore structure of continental shale oil reservoirs, well-developed bedding, strong heterogeneity, and extremely poor physical properties, the productivity of shale reservoirs under natural conditions is extremely low. Traditional methods and technologies are no longer sufficient to achieve the goal of economic exploitation. It is necessary to adopt methods such as increasing the fracturing intensity to break through the formation principal stress difference, guiding fractures to change direction and connect with natural fractures, and opening natural weak planes to maximize the reservoir exploitation efficiency. Although practical applications have proved that volume fracturing with close cutting of reservoirs using multi-clusters in horizontal wells has certain effects, however, when facing continental shale oil reservoirs with widely developed natural fractures, engineering problems such as low complexity of the fracture network and difficult prediction of the fracture network morphology after fracturing still exist. It is difficult to accurately describe the extension law of multiple fractures during the hydraulic fracturing process and the geometric morphology of the fracture network formed by intersecting with natural fractures. Therefore, it is necessary to carry out research on new methods and technologies for characterizing the fracture network morphology of shale oil reservoirs, provide theoretical support for improving the reservoir transformation volume in on-site fracturing operations, and provide a basis for adjusting the development plan of shale oil. Summary of the Invention

[0003] The present invention aims to at least solve one of the technical problems existing in the prior art. For this purpose, the present invention proposes a method for identifying the fracture network morphology after reservoir flowback, which can improve the accuracy of fracture network morphology identification.

[0004] The present invention also provides a system for identifying the fracture network morphology after reservoir flowback, a control device for executing the above method for identifying the fracture network morphology after reservoir flowback, and a computer-readable storage medium.

[0005] According to the method for identifying the fracture network morphology after reservoir flowback according to the first aspect embodiment of the present invention, the method includes: Obtaining first apparent resistivity data of a target reservoir in a study area before fracturing, second apparent resistivity data after flowback, and elevation data of the target reservoir; Performing isopachous division of sub-layers on the target reservoir based on the elevation data to obtain G target sub-layers with a target thickness; Extracting corresponding data of G + 1 planes corresponding to the G target sub-layers from the first apparent resistivity data to obtain G + 1 first resistivity plane distribution maps, and extracting corresponding data of G + 1 planes corresponding to the G target sub-layers from the second apparent resistivity data to obtain G + 1 second resistivity plane distribution maps; Calculate the reduction amplitude of the resistivity after flowback based on the G + 1 first resistivity plane distribution maps and the G + 1 second resistivity plane distribution maps to obtain G + 1 apparent resistivity reduction value plane distribution maps before and after flowback; Calculate the reduction boundary value corresponding to each apparent resistivity reduction value plane distribution map according to the resistivity reduction amplitude, a preset lithology weighting parameter, the target thickness, and the flattened thickness; wherein, the flattened thickness is the thickness value after removing the ineffective lithology interlayer thickness corresponding to the target sub-layer. If not in the dominant transformation area in the apparent resistivity reduction value plane distribution map, the reduction boundary value is the first boundary value. If in the dominant transformation area, the reduction boundary value is the second boundary value, and the dominant transformation area represents the shale oil enrichment area; Determine the part enclosed by the reduction boundary value as the main body of the change in the apparent resistivity reduction, and determine the part enclosed by the reduction boundary value and the zero value of the resistivity reduction amplitude as the predicted fracture zone. Based on the predicted fracture zone, complete the identification of the fracture network morphology after flowback of the target reservoir.

[0006] According to the method for identifying the fracture network morphology after flowback of the reservoir according to the embodiments of the present invention, at least the following beneficial effects are achieved: By equally dividing the target reservoir into sub-layers of equal thickness, and then analyzing the reduction amplitude of the resistivity before and after flowback of the G + 1 resistivity plane distribution maps corresponding to the G target sub-layers one by one, it can intuitively show the change of the resistivity of the target reservoir along the formation trend direction, and can improve the accuracy of fracture network morphology identification in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity. By dividing the fracturing fluid distribution area with the reduction boundary value that conforms to the actual physical properties of the reservoir and is related to the actual lithology distribution state of the reservoir as the boundary line, relevant parameters that can effectively characterize the actual lithology of the formation in the study area can be used to reduce the adverse impact of rock physical properties on the resistivity, and more accurate results closer to the actual situation can be obtained, making the fracture network morphology identification more accurate. Among them, the rock physical property parameters in the dominant transformation area and the non-dominant transformation area have a large gap, and the calculation of the reduction boundary value conducts a classification discussion on whether it is in the dominant transformation area, which is more in line with the actual situation of the study area, and the final fracture network morphology identification has higher accuracy.

[0007] According to some embodiments of the present invention, the dominant transformation area is determined through the following steps: Obtain the resistivity data of multiple production wells and the corresponding multiple production well logging data in the study area, and the production well logging data includes multiple logging parameters; Perform correlation fitting according to the resistivity data of multiple production wells and the corresponding multiple production well logging data to obtain a fitting relationship between the resistivity and multiple logging parameters; Obtain the critical values of multiple well logging parameters of the formation in the shale oil enrichment area in the study area based on the fitting relationship formula to determine the lower resistivity limit of the shale oil enrichment area in the study area; Determine the dominant transformation area in the G + 1 resistivity plane distribution maps according to the lower resistivity limit, where the dominant transformation area is the area in the resistivity plane distribution map where the resistivity is greater than the lower resistivity limit.

[0008] According to some embodiments of the present invention, the multiple well logging parameters are respectively effective porosity, water saturation, free hydrocarbon content, and organic carbon content, and the constraint formula of the fitting relationship formula is: ; Wherein, is the resistivity, and are preset calculation parameters, e is the mathematical natural constant, is the effective porosity, is the water saturation, is the free hydrocarbon content, TOC is the organic carbon content, is the determination coefficient of the free hydrocarbon content, is the determination coefficient of the organic carbon content, m is the preset porosity index, k is the preset saturation index.

[0009] According to some embodiments of the present invention, the obtaining the critical values of multiple well logging parameters of the formation in the shale oil enrichment area in the study area based on the fitting relationship formula to determine the lower resistivity limit of the shale oil enrichment area in the study area includes: Obtain the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content of the formation in the shale oil enrichment area in the study area; Determine the lower resistivity limit according to the fitting relationship formula, the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content.

[0010] According to some embodiments of the present invention, the constraint formula of the first boundary value is: ; = ; The constraint formula of the second boundary value is: ; Wherein, is the resistivity reduction amplitude, n is the target thickness, is the flattened thickness, E is a preset lithology weighting parameter, is the average interbed thickness of shale, is the average interbed thickness of mudstone, is the average interbed thickness of sandstone, is the sum of the average interbed thicknesses of carbonate rocks, is the weight coefficient of shale, is the weight coefficient of mudstone, is the weight coefficient of sandstone, is the weight coefficient of carbonate rocks.

[0011] According to some embodiments of the present invention, the constraint formula for the target thickness is: ; wherein, n is the target thickness, N is the thickness of the target reservoir, is the effective porosity, m is a preset porosity index, k is a preset saturation index, a and b are both preset lithology coefficients.

[0012] According to some embodiments of the present invention, the identification of the fracture network morphology after the backflow of the target reservoir based on the predicted fracture zone includes: Subdivide the grid for each planar distribution map of the apparent resistivity drop value; Determine the spatial position, fracture width and fracture length of the predicted fracture zone according to the number of grid points and the grid point positions of the predicted fracture zone in each planar distribution map of the apparent resistivity drop value; Complete the identification of the fracture network morphology after the backflow of the target reservoir according to the spatial positions, fracture widths and fracture lengths of all the predicted fracture zones in G + 1 planar distribution maps of the apparent resistivity drop value.

[0013] According to the fracture network morphology identification system of the second aspect embodiment of the present invention, the system includes: A data acquisition unit for acquiring the first apparent resistivity data of the target reservoir in the study area before fracturing and the second apparent resistivity data after backflow, as well as the elevation data of the target reservoir; A small layer division unit for performing isopachous division of the target reservoir based on the elevation data to obtain G target small layers with a thickness value of the target thickness; The small layer resistivity extraction unit is used to extract the corresponding data of G + 1 planes corresponding to G target small layers from the first apparent resistivity data to obtain G + 1 first resistivity plane distribution maps, and extract the corresponding data of G + 1 planes corresponding to G target small layers from the second apparent resistivity data to obtain G + 1 second resistivity plane distribution maps; The resistivity reduction amplitude determination unit is used to calculate the resistivity reduction amplitude after flowback according to the G + 1 first resistivity plane distribution maps and the G + 1 second resistivity plane distribution maps to obtain G + 1 apparent resistivity drop value plane distribution maps before and after flowback; The drop boundary value calculation unit is used to calculate the drop boundary value corresponding to each apparent resistivity drop value plane distribution map according to the resistivity reduction amplitude, a preset lithology weighting parameter, the target thickness, and the flattened thickness; wherein, the flattened thickness is the thickness value after removing the ineffective lithology interlayer thickness corresponding to the target small layer. If it is not in the dominant transformation area in the apparent resistivity drop value plane distribution map, the drop boundary value is the first boundary value. If it is in the dominant transformation area, the drop boundary value is the second boundary value, and the dominant transformation area represents the shale oil enrichment area; The fracture network identification unit is used to determine the part surrounded by the drop boundary value as the main body of the change in apparent resistivity drop, and determine the part surrounded by the drop boundary value and the zero value of the resistivity reduction amplitude as the predicted fracture zone, and complete the identification of the fracture network morphology after flowback of the target reservoir based on the predicted fracture zone.

[0014] The fracture network morphology identification system after flowback of the reservoir according to the embodiment of the present invention has at least the following beneficial effects: By equally dividing the target reservoir into small layers of equal thickness, and then analyzing the resistivity reduction amplitude before and after flowback of the G + 1 resistivity plane distribution maps corresponding to G target small layers one by one, it can intuitively show the change of the resistivity of the target reservoir along the formation trend direction, and can improve the accuracy of fracture network morphology identification in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity. By dividing the fracturing fluid distribution area with the drop boundary value that conforms to the actual physical properties of the reservoir and is related to the actual lithology distribution state of the reservoir as the boundary line, it can effectively characterize the relevant parameters of the actual lithology of the formation in the study area to reduce the adverse impact of rock physical properties on resistivity, and can obtain results closer to the actual situation, making the fracture network morphology identification more accurate. Among them, the rock physical property parameters in the dominant transformation area and the non-dominant transformation area have a large gap, and the calculation of the drop boundary value conducts a classification discussion on whether it is in the dominant transformation area, which is more in line with the actual situation of the study area, and the final fracture network morphology identification accuracy is higher.

[0015] The control device according to the embodiment of the third aspect of the present invention includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the method for identifying the fracture network morphology after reservoir backflow as described in the embodiment of the first aspect above. Since the control device adopts all the technical solutions of the method for identifying the fracture network morphology after reservoir backflow in the above embodiment, it has at least all the beneficial effects brought by the technical solutions of the above embodiment.

[0016] The computer-readable storage medium according to the embodiment of the fourth aspect of the present invention stores computer-executable instructions, and the computer-executable instructions are used to execute the method for identifying the fracture network morphology after reservoir backflow as described in the embodiment of the first aspect above. Since the computer-readable storage medium adopts all the technical solutions of the method for identifying the fracture network morphology after reservoir backflow in the above embodiment, it has at least all the beneficial effects brought by the technical solutions of the above embodiment.

[0017] Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification or be understood by implementing the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present invention will become obvious and easy to understand from the description of the embodiments in conjunction with the following drawings, where: Figure 1 is a flowchart of the method for identifying the fracture network morphology after reservoir backflow according to an embodiment of the present invention; Figure 2 is a schematic diagram of a resistivity profile according to an embodiment of the present invention; Figure 3 is a schematic diagram of a resistivity plan according to an embodiment of the present invention; Figure 4 is a schematic diagram of a fitting curve of the resistivity and the power-law parameters of the effective porosity and water saturation in the fitting relationship according to an embodiment of the present invention; Figure 5 is a schematic diagram of the advantageous transformation area according to an embodiment of the present invention; Figure 6 is a schematic diagram of fracture network identification according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0020] In the description of the present invention, if the first, second, etc. are described only for the purpose of distinguishing technical features, they should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features or implicitly specifying the sequence relationship of the indicated technical features.

[0021] In the description of the present invention, it should be understood that for the orientation description, such as up, down, etc., the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the indicated device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0022] In the description of the present invention, it should be noted that unless otherwise clearly defined, words such as setting, installation, connection, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0023] The following will combine Figures 1 to 6 to clearly and completely describe the method for identifying the fracture network morphology after reservoir flowback in the embodiments of the present invention. Obviously, the following described embodiments are part of the embodiments of the present invention, not all embodiments.

[0024] Refer to Figures 1 to 6 , Figure 1 which is a flowchart of the method for identifying the fracture network morphology after reservoir flowback in an embodiment of the present invention; Figure 2 which is a schematic diagram of a resistivity profile in an embodiment of the present invention; Figure 3 which is a schematic diagram of a resistivity plan in an embodiment of the present invention; Figure 4 which is a schematic diagram of a fitting curve of the resistivity and the power parameters of effective porosity and water saturation in the fitting relationship in an embodiment of the present invention; Figure 5 which is a schematic diagram of the superior transformation area in an embodiment of the present invention; Figure 6 which is a schematic diagram of fracture network identification in an embodiment of the present invention.

[0025] According to the method for identifying the fracture network morphology after reservoir flowback in the first aspect embodiment of the present invention, the method includes: Obtain the first apparent resistivity data before fracturing and the second apparent resistivity data after flowback of the target reservoir in the study area, as well as the elevation data of the target reservoir; Based on the elevation data, perform isopachous division of the target reservoir into small layers to obtain G target small layers with a thickness value of the target thickness; Extract the corresponding data of G + 1 planes corresponding to G target small layers from the first apparent resistivity data to obtain G + 1 first resistivity plane distribution maps, and extract the corresponding data of G + 1 planes corresponding to G target small layers from the second apparent resistivity data to obtain G + 1 second resistivity plane distribution maps; Calculate the reduction amplitude of resistivity after flowback according to the G + 1 first resistivity plane distribution maps and the G + 1 second resistivity plane distribution maps to obtain G + 1 apparent resistivity reduction value plane distribution maps before and after flowback; Calculate the reduction boundary value corresponding to each apparent resistivity reduction value plane distribution map according to the resistivity reduction amplitude, the preset lithology weighting parameter, the target thickness, and the flattened thickness; among them, the flattened thickness is the thickness value after removing the ineffective lithology interlayer thickness of the corresponding target small layer. If it is not in the dominant transformation area in the apparent resistivity reduction value plane distribution map, the reduction boundary value is the first boundary value. If it is in the dominant transformation area, the reduction boundary value is the second boundary value, and the dominant transformation area represents the shale oil enrichment area; Determine the part enclosed by the reduction boundary value as the main body of the change in apparent resistivity reduction, and determine the part enclosed by the reduction boundary value and the zero value of the resistivity reduction amplitude as the predicted fracture zone. Based on the predicted fracture zone, complete the identification of the fracture network morphology after flowback of the target reservoir.

[0026] The apparent resistivity data is obtained through the following steps: Obtain the electromagnetic field information, seismic data, and geological data of the study area; Establish an initial geoelectric model according to the electromagnetic field information, seismic data, and geological data, and perform high-precision wide-area electromagnetic method inversion on the initial geoelectric model to obtain the inversion apparent resistivity distribution profile of the study area, so as to obtain the apparent resistivity data of the target reservoir in the study area.

[0027] The altitude data is obtained through the following steps: Obtain the seismic data and logging data of the study area; Determine the altitude range where the target reservoir is located according to the seismic data and logging data, and record the altitude range as altitude data.

[0028] It should be noted that the altitude range refers to the altitude data that can describe the top and bottom interfaces of the target reservoir at any position within the study area. The altitudes of the top and bottom boundaries of the target reservoir change continuously with the geographical location and the stratigraphic trend, rather than being constant. The altitude data of the target reservoir can be represented in the form of coordinate points (x, y, z), where x and y are the x and y values of the geodetic coordinate system at this position, and z is the corresponding altitude depth.

[0029] The constraint formula for the target thickness is: ; Formula (1) Among them, n is the target thickness,N is the thickness of the target reservoir, is the effective porosity, m is the preset porosity index, k is the preset saturation index, a and b are both preset lithology coefficients. The thickness of the target reservoir is obtained from elevation data, and the effective porosity, porosity index, saturation index, and lithology coefficient can all be obtained from the existing geological data and seismic data in the study area. G is equal to N / n .

[0030] It can be understood that the target sub-layer is a virtual sub-layer obtained by equally dividing the target reservoir according to a certain thickness and does not exist in the actual formation environment. It can be seen from the empirical formula for dividing virtual sub-layers that the thickness of virtual sub-layers is only related to the thickness, porosity, and lithology of the actual reservoir. There are mainly two reasons for such processing: First, anisotropy is one of the main characteristics of shale oil reservoirs. Due to the influence of the reservoir system, natural fractures, and dual organic-inorganic origins, the pore and fracture development degrees of shale reservoirs in the vertical and horizontal directions vary greatly. The bedding fractures are highly developed in the horizontal direction, and even high-porosity and high-permeability zones can be formed in relatively shallow formations (the elevation depth represented by the relatively shallow formations depends on the actual geological situation. For example, in a pure shale-type shale oil reservoir in a certain basin in China, it usually represents the area shallower than -2000m above sea level). The pore and permeability in the horizontal direction may reach hundreds of times that in the vertical direction, resulting in extremely strong vertical heterogeneity of shale reservoirs. A difference of several meters in elevation may lead to significant differences in physical properties. Therefore, when analyzing the lithology, physical properties, and oil-bearing characteristics of a certain shale oil reservoir, it is not very reasonable to study the reservoir with a thickness of more than ten meters or even dozens of meters as a whole. Instead, it is beneficial to the refined evaluation of the oil and gas content of the reservoir to conduct smaller sub-layer division and classification research according to the actual lithology and physical properties of the reservoir. Second, with the continuous deepening of the development and research of unconventional oil and gas resources in China, the refinement degree of the evaluation of the oil and gas content of the reservoir is also getting higher and higher. Making the resolution of reservoir information in the vertical direction smaller and the positioning more accurate is one of the main research directions of domestic scholars at present. Virtual sub-layers do not exist in reality. The significance of dividing virtual sub-layers is to combine the microscopic analysis results of sub-layers with the macroscopic analysis results of the entire reservoir, achieve a more scientific and reasonable evaluation result of the oil and gas content of the reservoir, and can be understood as a means of classification analysis. After studying each virtual sub-layer one by one and then combining them into a whole to form a comprehensive understanding of the reservoir, such a means is particularly suitable for shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity.

[0031] For the understanding of G target sub-layers and G + 1 resistivity plane distribution maps, refer to Figure 3 . Figure 3It is a schematic diagram of the resistivity plan view of an embodiment of the present invention. If the number of target sub-layers is 2 and they are divided into upper and lower sub-layers, then there are three resistivity plan distribution maps, namely the top boundary of the upper sub-layer, the boundary between the upper and lower sub-layers, and the bottom boundary of the lower sub-layer.

[0032] By equally dividing the target reservoir into sub-layers with equal thickness and then analyzing the resistivity reduction amplitude before and after flowback for each of the G + 1 resistivity plan distribution maps corresponding to the G target sub-layers one by one, it is possible to intuitively show the change of the resistivity of the target reservoir along the formation trend direction, and it can improve the accuracy of fracture network morphology recognition in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity.

[0033] It can be understood that flowback refers to the situation where after the fracturing fluid is injected underground and the fracturing purpose is completed, when the fracturing operation stops, the formation pressure drops, some fractures close, and a large amount of formation water, drilling cuttings, and the remaining fracturing fluid flow back to the ground, which is collectively called fracturing flowback fluid. The flowback process usually lasts for several months. In addition, the flowback efficiency is an important parameter for evaluating the fracturing effect. The higher the flowback rate of the fracturing fluid, that is, the less fracturing fluid remains in the formation, the less damage to the formation, and the greater the oil and gas production. Generally speaking, engineering technicians can obtain better placement of proppants in the fractures by controlling the flowback velocity. Generally, the purpose of fracturing fluid flowback and fracturing construction operations is the same, which is to obtain fractures with high conductivity.

[0034] In some embodiments, one or several production wells with logging data in the study area are selected for fracturing work, and the resistivity reduction amplitude after flowback is calculated according to the G + 1 first resistivity plan distribution maps and the G + 1 second resistivity plan distribution maps to obtain the G + 1 apparent resistivity reduction value plan distribution maps before and after flowback.

[0035] The constraint formula for the resistivity reduction amplitude is: ; Formula (2) Among them, is the resistivity reduction amplitude, is the resistivity before fracturing, is the resistivity after flowback.

[0036] In some embodiments of the present invention, referring to Figure 2 、 Figure 4 and Figure 5 , the advantageous transformation area is determined through the following steps: Obtain the resistivity data of multiple production wells and the corresponding logging data of multiple production wells in the study area. The logging data of production wells includes multiple logging parameters; Perform correlation fitting based on resistivity data of multiple production wells and corresponding logging data of multiple production wells to obtain a fitting relationship between resistivity and multiple logging parameters; Based on the fitting relationship, obtain the critical values of multiple logging parameters of the formation in the shale oil enrichment area in the study area to determine the lower limit of resistivity in the shale oil enrichment area in the study area; Determine the dominant transformation area in the G + 1 resistivity plane distribution maps according to the lower limit of resistivity. The dominant transformation area is the area where the resistivity in the resistivity plane distribution map is greater than the lower limit of resistivity.

[0037] It should be noted that referring to Figure 2 , the resistivity data of multiple production wells are resistivity data extracted by selecting several apparent resistivity profiles, and all apparent resistivity profiles must pass through one or several production wells with logging data in the study area.

[0038] In some embodiments of the present invention, the multiple logging parameters are respectively effective porosity, water saturation, free hydrocarbon content, and organic carbon content. The constraint formula of the fitting relationship is: ; Formula (3) Among them, is the resistivity, and are preset calculation parameters, e is the mathematical natural constant, is the effective porosity, is the water saturation, is the free hydrocarbon content, TOC is the organic carbon content, is the determination coefficient of the free hydrocarbon content, is the determination coefficient of the organic carbon content, m is the preset porosity index, k is the preset saturation index.

[0039] Perform correlation fitting based on resistivity data of multiple production wells and corresponding logging data of multiple production wells, and obtain the determination coefficient of the fitting curve according to the fitting result. The determination coefficient is That is, the square of the correlation coefficient R .

[0040] Denote the power parameter of the effective porosity and the water saturation as x . Refer to Figure 4 , and perform calculation fitting with reference to Formula (3) until the determination coefficient between the resistivity x and the power parameter Above 0.9. It should be noted that when the free hydrocarbon content , and the organic carbon content TOC When their respective determination coefficients are lower than 0.5, they will be judged as not having a correlation. At this time, in the formula , TOC Is assigned a value of 0.

[0041] In some embodiments of the present invention, based on the fitting relationship, critical values of multiple logging parameters of the formation in the shale oil enrichment area of the study area are obtained to determine the lower limit of resistivity in the shale oil enrichment area of the study area, including: Obtain the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content of the formation in the shale oil enrichment area of the study area; Determine the lower limit of resistivity according to the fitting relationship, the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content.

[0042] It can be understood that the higher the upper limits of effective porosity and water saturation of the formation in the shale oil enrichment area of the study area, and the lower the lower limits of free hydrocarbon content and organic carbon content, the larger the defined range of the preferential transformation area, and the more oil content in the shale reservoir may be. From the fitting relationship, when the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content are determined, and the determination coefficient is a known value, the lower limit of resistivity can be determined. Then, the preferential transformation area can be determined in the G + 1 resistivity plane distribution maps according to the lower limit of resistivity. The preferential transformation area is the area in the resistivity plane distribution map where the resistivity is greater than the lower limit of resistivity. Among them, the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content can be obtained from the geological data, logging data, drilling data, and oil testing data of the study area.

[0043] It should be noted that the advantageous transformation area is the possible shale oil enrichment area inferred from the resistivity distribution. The reason for dividing the advantageous transformation area is as follows: The oil occurrence state and oil content in the shale reservoir are closely related to the lithology distribution. Usually, the shale oil accumulation is relatively large in the positions where mud shale is the main body, bedding fissures are highly developed, and clay minerals are developed. However, the amount of oil spillage is small in the positions where brittle lithologies such as felsic particles, dolomite laminations, and shell limestone laminations are developed. In these positions, carbonate cementation is dense, the reservoir space is not developed, and the oil content is relatively low. Different lithologies result in different physical properties of the rock. Strata with a larger brittleness index may have better fracturability during fracturing operations (the brittleness index is an important parameter used to characterize the brittle characteristics of rocks and is a comprehensive parameter that quantifies the ability of rocks to resist plastic deformation and undergo sudden fracture under external forces), generating more fracturing cracks. In addition, according to the fitting relationship, it can also be known that the lower resistivity limit of the shale oil enrichment area is related to well logging parameters such as the free hydrocarbon content and organic carbon content in the reservoir of the actual research area. In fact, these two parameters are inseparable from the lithology contained in the oil accumulation environment of the crude oil. Therefore, the present invention delimits the "advantageous transformation area" based on the obtained plan view and the lower resistivity limit of the shale oil enrichment area, aiming to carry out classification research and analysis to achieve a more detailed and accurate evaluation of the fracture network morphology after reservoir fracturing. The lower resistivity limit marks the difference in the physical properties of the rocks inside and outside the advantageous transformation area. In subsequent fracturing operations, different artificial fracture morphologies will be obtained in different lithology areas. If only a unified resistivity reduction standard is used to delineate the fracture range in the subsequent steps, it will lead to a result that deviates from the actual situation of the formation in the work area and the reliability of the results is not high. Generally speaking, the purpose of dividing the advantageous transformation area is to achieve the classification discussion and research of areas with obvious differences in reservoir lithology.

[0044] In some embodiments of the present invention, the constraint formula for the first boundary value is: ; Formula (4) = ; Formula (5) The constraint formula for the second boundary value is: ; Formula (6) Wherein, is the resistivity reduction amplitude, n is the target thickness, is the flattened thickness, E is the preset lithology weighting parameter, is the average interlayer thickness of the shale, is the average interlayer thickness of the mudstone, is the average interlayer thickness of the sandstone, is the sum of the average interlayer thicknesses of carbonate rocks is the weight coefficient of shale, is the weight coefficient of mudstone, is the weight coefficient of sandstone, is the weight coefficient of carbonate rocks.

[0045] The sum of the flattened thickness, the average interlayer thickness of shale, the average interlayer thickness of mudstone, the average interlayer thickness of sandstone, and the average interlayer thickness of carbonate rocks can all be obtained from the well logging data in the study area; the weight coefficients of shale, mudstone, sandstone, and carbonate rocks can be obtained from the oil testing data in the study area and through indoor physical property experiments on the core samples of the target reservoirs of multiple production wells in the study area.

[0046] The flattened thickness is the thickness value after removing the ineffective lithologic interlayer thickness of the corresponding target sub-layer, which refers to the total superimposed thickness of mudstone, shale, and sandstone in the target sub-layer. The ineffective lithologic interlayer includes carbonate rocks. The first boundary value and the second boundary value exclude the influence of ineffective reservoirs and are more in line with the actual situation of the study area.

[0047] It should be noted that regarding the correspondence between the relevant parameters of the target sub-layer (the sum of the flattened thickness, the average interlayer thickness of shale, the average interlayer thickness of mudstone, the average interlayer thickness of sandstone, the average interlayer thickness of carbonate rocks, the weight coefficient of shale, the weight coefficient of mudstone, the weight coefficient of sandstone, and the weight coefficient of carbonate rocks) and the planar distribution map of the apparent resistivity drop value, taking the number of target sub-layers as 2 and dividing them into upper and lower two sub-layers, corresponding to three planar distribution maps of the apparent resistivity drop value, namely the top boundary of the upper sub-layer, the boundary between the upper and lower sub-layers, and the bottom boundary of the lower sub-layer. For example, the planar distribution map of the apparent resistivity drop value corresponding to the top boundary of the upper sub-layer can correspond to the relevant parameters of the upper sub-layer; the planar distribution map of the apparent resistivity drop value corresponding to the boundary between the upper and lower sub-layers can correspond to the relevant parameters of the upper sub-layer or the relevant parameters of the lower sub-layer; the planar distribution map of the apparent resistivity drop value corresponding to the bottom boundary of the lower sub-layer can correspond to the relevant parameters of the lower sub-layer.

[0048] Refer to Figure 6 , and a closed irregular polygon can be visually observed. Taking the drop boundary value as the boundary line, the part within the boundary line is determined as the main body of the change in the apparent resistivity drop, and the part outside is the predicted fracture zone. Figure 6 The area enclosed by the dashed line and the coordinate axes in is the dominant transformation area, the area enclosed by the inner solid line is the main body of the change in the apparent resistivity drop, the outer solid line represents the zero value of the resistivity reduction amplitude, indicating that the formation here is hardly affected by the fracturing fluid and the change amplitude of the apparent resistivity is basically zero. The part enclosed by the inner solid line and the outer solid line is the predicted fracture zone, and the part outside the outer solid line belongs to the area not affected by the fracturing operation.

[0049] It should be noted that Figure 5 and Figure 6 are both resistivity plan views, and the horizontal and vertical axes are the earth's coordinate axes.

[0050] It can be understood that the main body of the change in the apparent resistivity drop is the fracturing fluid remaining in the current formation inferred by the present invention based on the resistivity distribution. It should be noted that the plane distribution map of the apparent resistivity drop value of the present invention is obtained based on the difference in apparent resistivity between two periods before and after formation fracturing. The apparent resistivity distribution of the formation before fracturing is the original apparent resistivity distribution of the formation when it has not undergone any transformation construction. It should be understood that the smaller the difference between the apparent resistivity distribution of the formation after flowback and the original apparent resistivity distribution of the formation, the closer the apparent resistivity distribution of the formation after flowback is to the original state, which also means that the retention degree of the fracturing fluid in the formation is lower and the flowback rate of the fracturing fluid is higher. On the contrary, when there is a significant difference between the apparent resistivity distribution of the formation after flowback and the original apparent resistivity distribution of the formation, it means that the fracturing fluid in the formation has a high retention degree. At the same time, due to the presence of a large amount of water and metal ions, the fracturing fluid shows an obvious low resistivity. Therefore, this significant difference will cause an obvious decrease in the apparent resistivity at the same formation position after flowback.

[0051] The standard for the main body dividing line of the change in the apparent resistivity drop is the drop boundary value , and it should be understood that since shale reservoirs usually contain a certain amount of clay minerals, due to the hydrophilicity of clay minerals, even if the fracturing fluid is completely discharged from a certain formation fracture after flowback, it will cause a certain degree of decrease in the resistivity of the formation at that place. This means that whether the fracturing fluid is completely flowback or not will cause a decrease in the resistivity of the shale reservoir, and it also shows that it is impossible to simply judge the distribution of the fracturing fluid in the current formation based on whether the resistivity changes. For this reason, the present invention proposes to use the drop boundary value that conforms to the actual physical properties of the reservoir and is related to the actual lithology distribution state of the reservoir as the boundary line to divide the fracturing fluid distribution area (it can be seen from formula (4), formula (5) and formula (6) that the lithology weighting parameter E is closely related to the actual physical properties and lithology of the reservoir in the study area). By combining relevant parameters that can effectively characterize the actual lithology of the formation in the study area, the adverse effects of rock physical properties on resistivity can be reduced, and a result closer to the actual situation can be obtained. When the resistivity anomaly amplitude is greater than the drop boundary value, that is, the area within the boundary line is judged to still retain some fracturing fluid, resulting in a relatively significant abnormal change amplitude in the resistivity of this area; when the resistivity anomaly amplitude is less than the drop boundary value, that is, the area outside the boundary line is judged to be the fracture distribution area with a low retention degree of fracturing fluid or where there was once fracturing fluid filling but has now been flowback.

[0052] In some embodiments of the present invention, with reference toFigure 6 , based on the predicted fracture zone, the fracture network morphology identification after the target reservoir is completed, including: Subdividing each plane distribution map of apparent resistivity drop amplitude into grids; Determine the spatial position, crack width and crack length of the predicted crack zone according to the number and position of the grid points of the predicted crack zone in each plane distribution map of the apparent resistivity drop amplitude; The fracture network morphology after flowback of the target reservoir is identified based on the spatial position, fracture width and fracture length of all predicted fracture zones in the plane distribution map of G+1 apparent resistivity drop values.

[0053] The method for identifying the fracture network morphology after reservoir backflow proposed in the present invention innovatively proposes a method of organically combining the three technologies of seismic, electromagnetic and well logging, which makes up for some of the shortcomings of the three methods when used separately. The method proposed in the present invention is based on the concept of mutual integration of the three exploration methods of seismic, electromagnetic and well logging. When combining the three technologies, it is not a simple series formula, but the advantages of each data are fully utilized when combining the three types of data: (1) Combining seismic and electromagnetic technology. The geological framework and boundary conditions provided by the seismic model are used to accurately identify the reservoir structure of the study area, which is filled with electromagnetic data, and high-precision wide-area electromagnetic inversion is performed to obtain a wide-area apparent resistivity that is more sensitive to fluids. It combines the characteristics of conventional seismic parameters that are accurate in identifying reservoir structures but inaccurate in identifying fluids, and electromagnetic methods that are not accurate in identifying stratum structures but sensitive to fluids; (2) The organic combination of electromagnetic technology and well logging technology is achieved. The present invention fully considers the complex actual situation of the study area when proposing the discrimination relationship of the advantageous transformation area of ​​the study area. First, the through-well resistivity profile is mainly selected for correlation analysis, so that the data is more consistent with the actual situation of the formation and has higher credibility. Second, several logging parameters closely related to the oil and gas enrichment are selected for fitting, and an empirical formula is established based on the fitting situation. When establishing the empirical formula, it is not a simple linear analysis, but the actual situation of the reservoir is fully considered, and the correlation between various logging parameters and resistivity is substituted, so that the formula parameters are dynamic and have stronger and more extensive applicability; (3) The present invention innovatively divides the target reservoir into several virtual small layers according to equal thickness, and draws the apparent resistivity plane map along the formation trend. Compared with the conventional two-dimensional profile results, the data is more refined and rich, and the multi-dimensional characteristics are significant; (4) When identifying the fracture network morphology, the present invention establishes different formulas according to whether it is in the advantageous transformation area or not. The formula uses the flattening thickness to deduct the influence of the invalid reservoir, which is more in line with the actual situation of the work area.

[0054] The method for identifying the fracture network morphology after reservoir flowback according to the embodiments of the present invention divides the target reservoir into equal-thickness sub-layers, and then analyzes the resistivity reduction amplitudes before and after flowback of the G + 1 resistivity plane distribution maps corresponding to the G target sub-layers one by one, which can intuitively show the change of the resistivity of the target reservoir along the formation trend direction, and can improve the accuracy of fracture network morphology identification in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity. By dividing the fracturing fluid distribution area with the reduction boundary value that conforms to the actual physical properties of the reservoir and is related to the actual lithology distribution state of the reservoir as the boundary line, relevant parameters that can effectively characterize the actual lithology of the formation in the study area can be used to reduce the adverse impact of rock physical properties on resistivity, and results closer to the actual situation can be obtained, making the fracture network morphology identification more accurate. Among them, the difference in rock physical property parameters between the dominant transformation area and the non-dominant transformation area is large, and the calculation of the reduction boundary value classifies and discusses whether it is in the dominant transformation area, which is more in line with the actual situation of the study area, and the final fracture network morphology identification accuracy is higher.

[0055] According to the reservoir flowback after-fracture network morphology identification system of the second aspect of the present invention, the system includes a data acquisition unit, a sub-layer division unit, a sub-layer resistivity extraction unit, a resistivity reduction amplitude determination unit, a reduction boundary value calculation unit, and a fracture network identification unit.

[0056] The data acquisition unit is used to acquire the first apparent resistivity data before fracturing and the second apparent resistivity data after flowback of the target reservoir in the study area, as well as the elevation data of the target reservoir. The sub-layer division unit is used to perform equal-thickness sub-layer division on the target reservoir based on the elevation data to obtain G target sub-layers with a target thickness value. The sub-layer resistivity extraction unit is used to extract the corresponding data of G + 1 planes corresponding to the G target sub-layers from the first apparent resistivity data to obtain G + 1 first resistivity plane distribution maps, and extract the corresponding data of G + 1 planes corresponding to the G target sub-layers from the second apparent resistivity data to obtain G + 1 second resistivity plane distribution maps. The resistivity reduction amplitude determination unit is used to calculate the resistivity reduction amplitude after flowback according to the G + 1 first resistivity plane distribution maps and the G + 1 second resistivity plane distribution maps to obtain G + 1 apparent resistivity reduction value plane distribution maps before and after flowback. A reduction boundary value calculation unit is used to calculate the reduction boundary value corresponding to each plane distribution map of apparent resistivity reduction values according to the resistivity reduction amplitude, a preset lithology weighting parameter, a target thickness, and a flattened thickness; wherein, the flattened thickness is the thickness value of the corresponding target sub-layer after removing the thickness of ineffective lithology interlayers. In the plane distribution map of apparent resistivity reduction values, if it is not in the dominant transformation area, the reduction boundary value is the first boundary value, and if it is in the dominant transformation area, the reduction boundary value is the second boundary value. The dominant transformation area represents the shale oil enrichment area. A fracture network identification unit is used to determine the part enclosed by the reduction boundary value as the main body of the change in apparent resistivity reduction, and determine the part enclosed by the reduction boundary value and the zero value of the resistivity reduction amplitude as the predicted fracture zone, and complete the identification of the fracture network morphology after the backflow of the target reservoir based on the predicted fracture zone.

[0057] The apparent resistivity data is obtained through the following steps: Obtain the electromagnetic field information, seismic data, and geological data of the study area; Establish an initial geoelectric model based on the electromagnetic field information, seismic data, and geological data, and perform high-precision wide-area electromagnetic method inversion on the initial geoelectric model to obtain the inversion apparent resistivity distribution profile of the study area, so as to obtain the apparent resistivity data of the target reservoir in the study area.

[0058] The elevation data is obtained through the following steps: Obtain the seismic data and logging data of the study area; Determine the elevation range where the target reservoir is located according to the seismic data and logging data, and record the elevation range as the elevation data.

[0059] It should be noted that the elevation range refers to the elevation data that can describe the top and bottom interfaces of the target reservoir at any position within the study area. The elevations of the top and bottom boundaries of the target reservoir change continuously with the geographical location and formation trend, rather than being constant. The elevation data of the target reservoir can be represented in the form of coordinate points (x, y, z), where x and y are the x and y values of the geodetic coordinate system at this position, and z is the corresponding elevation depth.

[0060] The constraint formula for the target thickness is: ; Formula (1) Wherein, n is the target thickness, N is the thickness of the target reservoir, is the effective porosity, m is the preset porosity index, k is the preset saturation index, a and bAll are preset lithology coefficients. The thickness of the target reservoir is obtained from altitude data, and the effective porosity, porosity index, saturation index, and lithology coefficients can all be obtained from the existing geological data and seismic data in the study area. G is equal to N / n .

[0061] For the understanding of G target sub-layers and G + 1 resistivity plane distribution maps, refer to Figure 3 , Figure 3 which is a schematic diagram of the resistivity plane distribution map of an embodiment of the present invention. If the number of target sub-layers is 2 and they are divided into upper and lower sub-layers, then there are three corresponding resistivity plane distribution maps, namely the top boundary of the upper sub-layer, the boundary between the upper and lower sub-layers, and the bottom boundary of the lower sub-layer.

[0062] By equally dividing the target reservoir into sub-layers of equal thickness and then analyzing the resistivity reduction amplitudes before and after flowback for each of the G + 1 resistivity plane distribution maps corresponding to the G target sub-layers one by one, it is possible to intuitively display the variation of the resistivity of the target reservoir along the formation trend direction, and improve the accuracy of fracture network morphology recognition in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity.

[0063] In some embodiments, one or several production wells with logging data in the study area are selected for fracturing work, and the resistivity reduction amplitude after flowback is calculated based on the G + 1 first resistivity plane distribution maps and the G + 1 second resistivity plane distribution maps to obtain the G + 1 apparent resistivity drop value plane distribution maps before and after flowback.

[0064] The constraint formula for the resistivity reduction amplitude is: ; Formula (2) where is the resistivity reduction amplitude, is the resistivity before fracturing, is the resistivity after flowback.

[0065] In some embodiments of the present invention, referring to Figure 2 , Figure 4 and Figure 5 , the advantageous transformation area is determined through the following steps: Obtain the resistivity data of multiple production wells and the corresponding logging data of multiple production wells in the study area, and the logging data of production wells includes multiple logging parameters; Perform correlation fitting based on the resistivity data of multiple production wells and the corresponding logging data of multiple production wells to obtain the fitting relationship between resistivity and multiple logging parameters; Based on the fitting relationship, obtain the critical values of multiple logging parameters of the formation in the shale oil enrichment area in the study area to determine the lower limit of resistivity in the shale oil enrichment area in the study area; Determine the dominant transformation area based on the lower resistivity limit in G + 1 resistivity plane distribution maps. The dominant transformation area is the area where the resistivity in the resistivity plane distribution map is greater than the lower resistivity limit.

[0066] It should be noted that referring to Figure 2 , the resistivity data of multiple production wells are the resistivity data extracted by selecting several apparent resistivity profiles, and all apparent resistivity profiles must pass through one or several production wells with well logging data in the study area.

[0067] In some embodiments of the present invention, the multiple logging parameters are respectively effective porosity, water saturation, free hydrocarbon content, and organic carbon content. The constraint formula of the fitting relationship is: ; Formula (3) Wherein, is the resistivity, and are preset calculation parameters, e is the mathematical natural constant, is the effective porosity, is the water saturation, is the free hydrocarbon content, TOC is the organic carbon content, is the determination coefficient of the free hydrocarbon content, is the determination coefficient of the organic carbon content, m is the preset porosity index, k is the preset saturation index.

[0068] Perform correlation fitting based on the resistivity data of multiple production wells and the corresponding logging data of multiple production wells, and obtain the determination coefficient of the fitting curve according to the fitting result. The determination coefficient is which is the square of the correlation coefficient R .

[0069] Denote the power parameter of the effective porosity and the water saturation as x . Refer to Figure 4 , and perform calculation fitting with reference to Formula (3) until the determination coefficient between the resistivity x and the power parameter of the effective porosity and the water saturation reaches above 0.9. It should be noted that when the determination coefficients of the free hydrocarbon content and the organic carbon content TOC are each lower than 0.5, they will be determined to have no correlation. At this time, and TOC in the formula are assigned 0.

[0070] In some embodiments of the present invention, obtaining the critical values of multiple logging parameters of the formation in the shale oil enrichment area in the study area based on the fitting relationship formula to determine the lower resistivity limit in the shale oil enrichment area in the study area includes: Obtaining the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content of the formation in the shale oil enrichment area in the study area; Determining the lower resistivity limit according to the fitting relationship formula, the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content.

[0071] It can be understood that the larger the effective porosity and water saturation, and the smaller the free hydrocarbon content and organic carbon content, the more oil content the shale reservoir may have, and the more conducive it is to transformation. From the fitting relationship formula, when the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content are determined, and the coefficient of determination is a known value, the lower resistivity limit can be determined. Then, the dominant transformation area can be determined from the G + 1 resistivity plane distribution maps according to the lower resistivity limit. The dominant transformation area is the area where the resistivity in the resistivity plane distribution map is greater than the lower resistivity limit. Among them, the upper limit of effective porosity, the upper limit of water saturation, the lower limit of free hydrocarbon content, and the lower limit of organic carbon content can be obtained from the geological data, logging data, drilling data, and oil testing data of the study area.

[0072] In some embodiments of the present invention, the constraint formula for the first boundary value is: ; Formula (4) = ; Formula (5) The constraint formula for the second boundary value is: ; Formula (6) Among them, is the resistivity reduction amplitude, n is the target thickness, is the flattened thickness, E is the preset lithology weighting parameter, is the average interlayer thickness of shale, is the average interlayer thickness of mudstone, is the average interlayer thickness of sandstone, is the sum of the average interlayer thicknesses of carbonate rocks, is the weight coefficient of shale, is the weight coefficient of mudstone, is the weight coefficient of sandstone, is the weight coefficient of carbonate rocks.

[0073] The sum of the flattened thickness, the average interbed thickness of shale, the average interbed thickness of mudstone, the average interbed thickness of sandstone, and the average interbed thickness of carbonate rocks can all be obtained from the logging data in the study area; the weight coefficients of shale, mudstone, sandstone, and carbonate rocks can be obtained from the oil test data in the study area and through indoor physical property experiments on the core samples of the target reservoirs in multiple production wells in the study area.

[0074] The flattened thickness is the thickness value of the corresponding target sub-layer after removing the thickness of the ineffective lithologic interbeds, which refers to the total thickness of the superimposed mudstone, shale, and sandstone in the target sub-layer. The ineffective lithologic interbeds include carbonate rocks. The first boundary value and the second boundary value deduct the influence of the ineffective reservoirs and are more in line with the actual situation in the study area.

[0075] Reference Figure 6 , a closed irregular polygon can be visually observed, with the reduced boundary value as the boundary line, and the part inside the boundary line is determined as the main body of the apparent resistivity reduction change, and the part outside is the predicted fracture zone. Figure 6 The area enclosed by the dotted line and the coordinate axes in is the dominant transformation area, the area enclosed by the inner solid line is the main body of the apparent resistivity reduction change, the outer solid line represents the zero value of the resistivity reduction amplitude, indicating that the formation here is hardly affected by the fracturing fluid and the apparent resistivity change amplitude is basically zero. The part enclosed by the inner solid line and the outer solid line is the predicted fracture zone, and the part outside the outer solid line belongs to the area not affected by the fracturing operation.

[0076] It should be noted that Figure 5 and Figure 6 are both resistivity plan views, and the horizontal and vertical axes are the earth coordinate axes.

[0077] In some embodiments of the present invention, referring to Figure 6 , after the target reservoir is backflowed, the fracture network morphology recognition is completed based on the predicted fracture zone, including: Subdividing the grid for each plane distribution map of the apparent resistivity reduction value; Determining the spatial position, fracture width, and fracture length of the predicted fracture zone according to the number and positions of the grid points of the predicted fracture zone in each plane distribution map of the apparent resistivity reduction value; Completing the fracture network morphology recognition after the target reservoir is backflowed according to the spatial positions, fracture widths, and fracture lengths of all the predicted fracture zones in the G + 1 plane distribution maps of the apparent resistivity reduction value.

[0078] The fracture network morphology recognition system proposed by the present invention innovatively presents a method of organically combining three technologies: seismic, electromagnetic, and logging, which makes up for some deficiencies existing when the three methods are used alone. The system proposed by the present invention is based on the concept of the mutual integration of three exploration methods: seismic, logging, and electromagnetic. When combining the three technologies, it is not a simple series formula. When combining the three types of data, the advantages of each type of data are fully utilized: (1) Combining seismic and electromagnetic technologies. The geological framework and boundary conditions provided by the seismic model are used to accurately identify the reservoir framework in the study area, filled with electromagnetic data, and high-precision wide-area electromagnetic inversion is carried out to obtain a wide-area apparent resistivity that is more sensitive to fluids, combining the characteristics that conventional seismic parameters are precise in identifying the reservoir framework but inaccurate in fluid identification, and the electromagnetic method is not precise in identifying the formation structure but sensitive to fluids; (2) Realizing the organic combination of electromagnetic technology and logging technology. When proposing the discriminant relation formula for the dominant transformation area in the study area, the present invention fully considers the complex actual situation of the study area. On the one hand, the resistivity profile passing through the well is mainly selected for correlation analysis, making the data more in line with the actual situation of the formation and having higher credibility. On the other hand, several logging parameters closely related to the oil and gas enrichment situation are mainly selected for fitting, and an empirical formula is established according to the fitting situation. When establishing the empirical formula, it is not a simple linear analysis, but the correlation between various logging parameters and resistivity is fully considered and substituted, making the formula parameters dynamic and having stronger wide applicability; (3) The present invention innovatively divides the target reservoir into several virtual small layers according to equal thickness and draws the apparent resistivity plan along the formation trend. Compared with the conventional two-dimensional profile results, the data is more refined and rich, with obvious multi-dimensional characteristics; (4) When identifying the fracture network morphology, the present invention establishes different formulas according to whether it is in the dominant transformation area or not. The influence of ineffective reservoirs is deducted by using the flattened thickness in the formula, making it more in line with the actual situation of the work area.

[0079] The reservoir fracture network morphology recognition system according to the embodiments of the present invention can visually display the change of the resistivity of the target reservoir along the formation trend direction by equally dividing the target reservoir into small layers of equal thickness and then analyzing the resistivity reduction amplitude before and after the flowback of the resistivity plane distribution maps corresponding to G target small layers one by one. This can improve the accuracy of fracture network morphology recognition in shale oil reservoirs where the horizontal homogeneity is significantly stronger than the vertical homogeneity. By dividing the fracturing fluid distribution area with the reduction boundary value that conforms to the actual physical properties of the reservoir and is related to the actual lithology distribution state of the reservoir as the boundary line, relevant parameters that can effectively characterize the actual lithology of the formation in the study area can be used to reduce the adverse impact of rock physical properties on resistivity, and more accurate results closer to the actual situation can be obtained, making the fracture network morphology recognition more accurate. Among them, there is a large difference in the rock physical property parameters between the dominant transformation area and the non-dominant transformation area, and the calculation of the reduction boundary value classifies and discusses whether it is in the dominant transformation area, which is more in line with the actual situation of the study area, and the final accuracy of fracture network morphology recognition is higher.

[0080] In addition, an embodiment of the present invention also provides a control device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor and the memory can be connected through a bus or other means.

[0081] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory can optionally include a memory remotely set relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0082] The non-transitory software programs and instructions required to implement the reservoir flowback fracture network morphology recognition method of the above embodiments are stored in the memory, and when executed by the processor, they execute the reservoir flowback fracture network morphology recognition method in the above embodiments.

[0083] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] In addition, an embodiment of the present invention further provides a computer-readable storage medium storing computer-executable instructions, which are executed by a processor or a controller, for example, executed by the processor in the above embodiment, enabling the processor to execute the method for identifying the fracture network morphology after reservoir flowback in the above embodiment.

[0085] Those of ordinary skill in the art can understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and their appropriate combinations. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or a non-transitory medium) and a communication medium (or a transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technologies, CD-ROM, digital versatile disk (DVD), or other optical disk storage, magnetic cassette, tape, magnetic disk storage, or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0086] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Various changes can be made without departing from the spirit of the present invention within the scope of knowledge possessed by those of ordinary skill in the art.

Claims

1. A method for identifying the fracture network morphology after reservoir flowback, characterized in that: The method comprises: Obtaining first apparent resistivity data of a target reservoir in a study area before fracturing and second apparent resistivity data after flowback, as well as altitude data of the target reservoir; Divide the target reservoir into small layers of equal thickness based on the altitude data to obtain G target small layers with thickness values ​​of target thickness; Extracting corresponding data of G+1 planes corresponding to G target sublayers from the first apparent resistivity data to obtain G+1 first resistivity plane distribution maps, and extracting corresponding data of G+1 planes corresponding to G target sublayers from the second apparent resistivity data to obtain G+1 second resistivity plane distribution maps; Calculating the resistivity reduction amplitude after flowback according to G+1 first resistivity plane distribution diagrams and G+1 second resistivity plane distribution diagrams to obtain G+1 apparent resistivity reduction amplitude plane distribution diagrams before and after flowback; The reduction boundary value corresponding to each plane distribution diagram of the apparent resistivity reduction amplitude is calculated according to the resistivity reduction amplitude, the preset lithology weighting parameter, the target thickness and the rolling thickness; wherein the rolling thickness is the thickness value of the target sublayer after removing the invalid lithology interlayer thickness; if the plane distribution diagram of the apparent resistivity reduction amplitude is not in the advantageous transformation zone, the reduction boundary value is the first boundary value; if it is in the advantageous transformation zone, the reduction boundary value is the second boundary value; the advantageous transformation zone represents a shale oil-rich area; The portion enclosed by the drop boundary value is determined as the main body of the apparent resistivity drop change, and the portion enclosed by the drop boundary value and the zero value of the resistivity reduction amplitude is determined as the predicted fracture zone, and the fracture network morphology of the target reservoir after flowback is identified based on the predicted fracture zone.

2. The method for identifying fracture network morphology after reservoir flowback according to claim 1, characterized in that: The advantageous transformation area is determined by the following steps: Acquire resistivity data of a plurality of production wells in the study area and corresponding well logging data of a plurality of production wells, wherein the well logging data of the production wells includes a plurality of well logging parameters; Perform correlation fitting based on the resistivity data of the plurality of production wells and the corresponding logging data of the plurality of production wells to obtain a fitting relationship between the resistivity and the plurality of logging parameters; Based on the fitting relationship, critical values ​​of a plurality of the logging parameters of the strata in the shale oil-rich region in the study area are obtained to determine the lower limit of the resistivity of the shale oil-rich region in the study area; The advantageous transformation area is determined in G+1 resistivity plane distribution maps according to the resistivity lower limit, and the advantageous transformation area is an area in the resistivity plane distribution map where the resistivity is greater than the resistivity lower limit.

3. The method for identifying fracture network morphology after reservoir flowback according to claim 2, characterized in that: The plurality of logging parameters are effective porosity, water saturation, free hydrocarbon content and organic carbon content, and the constraint formula of the fitting relationship is: ； in, is the resistivity, and are the preset calculation parameters. e is a mathematical constant of nature, is the effective porosity, is the water saturation, is the free hydrocarbon content, TOC is the organic carbon content, is the determination coefficient of the free hydrocarbon content, is the determination coefficient of the organic carbon content, m is the preset porosity index, k is the preset saturation index.

4. The method for identifying fracture network morphology after reservoir flowback according to claim 3, characterized in that: The step of obtaining critical values ​​of a plurality of logging parameters of the strata in the shale oil-rich region in the study area based on the fitting relationship to determine the lower limit of the resistivity of the shale oil-rich region in the study area includes: Obtaining the upper limit of effective porosity, upper limit of water saturation, lower limit of free hydrocarbon content and lower limit of organic carbon content of strata in shale oil-rich areas within the study area; The resistivity lower limit is determined according to the fitting relationship, the effective porosity upper limit, the water saturation upper limit, the free hydrocarbon content lower limit and the organic carbon content lower limit.

5. The method for identifying fracture network morphology after reservoir flowback according to claim 1, characterized in that: The constraint formula of the first boundary value is: ； = ； The constraint formula of the second boundary value is: ； in, is the magnitude of the resistivity reduction, n is the target thickness, is the rolling thickness, E is the preset lithology weighting parameter, is the average interlayer thickness of shale, is the average interlayer thickness of mudstone, is the average interlayer thickness of sandstone, is the sum of the average interlayer thickness of carbonate rocks, is the weight coefficient of shale, is the weight coefficient of mudstone, is the weight coefficient of sandstone, is the weight coefficient of carbonate rocks.

6. The method for identifying fracture network morphology after reservoir flowback according to claim 1, characterized in that: The constraint formula of the target thickness is: ； in, n is the target thickness, N is the thickness of the target reservoir, is the effective porosity, m is the preset porosity index, k is the preset saturation index, a and b All are preset lithology coefficients.

7. The method for identifying fracture network morphology after reservoir flowback according to claim 1, characterized in that: The identification of the fracture network morphology after flowback of the target reservoir based on the predicted fracture zone includes: Subdividing each of the plane distribution diagrams of apparent resistivity drop amplitude into grids; Determine the spatial position, crack width and crack length of the predicted crack zone according to the number and positions of the grid points of the predicted crack zone in each of the plane distribution diagrams of the apparent resistivity drop amplitude; The fracture network morphology of the target reservoir after flowback is identified based on the spatial positions, fracture widths and fracture lengths of all the predicted fracture zones in the G+1 plane distribution maps of the apparent resistivity drop amplitudes.

8. A system for identifying the morphology of a fracture network after reservoir flowback, characterized in that: The system comprises: A data acquisition unit, used to acquire first apparent resistivity data of a target reservoir in a study area before fracturing and second apparent resistivity data after flowback, as well as altitude data of the target reservoir; A small layer division unit is used to divide the target reservoir into small layers of equal thickness based on the altitude data to obtain G target small layers with thickness values ​​of target thickness; A small layer resistivity extraction unit is used to extract corresponding data of G+1 planes corresponding to G target small layers from the first apparent resistivity data to obtain G+1 first resistivity plane distribution maps, and to extract corresponding data of G+1 planes corresponding to G target small layers from the second apparent resistivity data to obtain G+1 second resistivity plane distribution maps; a resistivity reduction amplitude determination unit, configured to calculate the resistivity reduction amplitude after flowback according to G+1 first resistivity plane distribution diagrams and G+1 second resistivity plane distribution diagrams, so as to obtain G+1 apparent resistivity reduction amplitude plane distribution diagrams before and after flowback; A reduction boundary value calculation unit is used to calculate the reduction boundary value corresponding to each of the apparent resistivity reduction amplitude plane distribution diagrams according to the resistivity reduction amplitude, the preset lithology weighting parameter, the target thickness and the rolling thickness; wherein the rolling thickness is the thickness value of the invalid lithology interlayer thickness removed from the target sublayer, and if the apparent resistivity reduction amplitude plane distribution diagram is not in the dominant transformation zone, the reduction boundary value is the first boundary value, and if it is in the dominant transformation zone, the reduction boundary value is the second boundary value, and the dominant transformation zone represents a shale oil-rich area; The fracture network identification unit is used to determine the part surrounded by the drop boundary value as the main body of the apparent resistivity drop change, determine the part surrounded by the drop boundary value and the zero value of the resistivity drop as the predicted fracture zone, and complete the fracture network morphology identification of the target reservoir after flowback based on the predicted fracture zone.

9. A control device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for identifying the fracture network morphology after reservoir flowback according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing computer-executable instructions, characterized in that: The computer executable instructions are used to execute the method for identifying fracture network morphology after reservoir flowback according to any one of claims 1 to 7.

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