Fractured reservoir determination method and apparatus, storage medium, and electronic device

Abstract

The application relates to the technical field of oil and gas exploration, in particular to a fracture reservoir determination method and device and electronic equipment. The method first establishes an initial low-frequency model according to seismic data and logging data of a target area, and then establishes a fracture impedance model according to the seismic data. Then, a mixed impedance low-frequency model is obtained according to the initial low-frequency model and the fracture impedance model, so that the mixed impedance low-frequency model can be used to depict the reservoir distribution in a three-dimensional space in the vertical and horizontal directions. The mixed impedance low-frequency model is inverted to obtain a P-wave impedance data body of the target area, and the P-wave impedance data body can reflect information such as lithology and physical properties of the target area. Therefore, the P-wave impedance data body and a relationship function between the P-wave impedance data body and porosity can be used to accurately depict the spatial distribution of the fracture-vug body in the target area, so that the fracture-vug connectivity of the reservoir can be more intuitively depicted.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration technology, and in particular to a method, apparatus, storage medium and electronic equipment for determining fractured reservoirs. Background Technology

[0002] Fractures are the smallest, most widely distributed, and most complex structures on the Earth's surface. In oil and gas exploration, fractures serve as valuable reservoir spaces and fluid migration channels, significantly impacting reservoir connectivity, productivity, and reserves. In recent years, various methods and technologies have been developed for the identification and description of fractured oil and gas reservoirs, including post-stack attribute techniques such as edge detection, eigenvalues, curvature, and ant-body analysis, as well as pre-stack techniques such as azimuthal anisotropy inversion. However, due to the complexity of fracture formation and the varying emphasis of different prediction methods and description parameters, single prediction methods, whether post-stack attribute calculations or pre-stack anisotropy inversions, often only predict a specific type of fault-fracture or fracture development zone. Furthermore, the prediction results are often a comprehensive response of fractured reservoirs at different levels and scales. Utilizing post-stack seismic data to develop techniques for describing fractures qualitatively characterizes their geometric features. The orientation and density of fractures can be characterized by pre-stack anisotropy inversion, but conventional inversion techniques using post-stack seismic data can only characterize the lateral features of the reservoir and cannot characterize the vertical features of fracture-like reservoirs. Summary of the Invention

[0003] To address the aforementioned issues, this application provides a method, apparatus, storage medium, and electronic device for determining fractured reservoirs.

[0004] In a first aspect, this application provides a method for determining fractured reservoirs, the method comprising:

[0005] An initial low-frequency model is established based on the acquired seismic and well logging data of the target area;

[0006] A fracture impedance model was established based on the aforementioned seismic data;

[0007] Based on the initial low-frequency model and the crack impedance model, a hybrid impedance low-frequency model is obtained;

[0008] Inversion is performed based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, and the spatial distribution of the target region is determined based on the longitudinal wave impedance data volume.

[0009] A relationship function representing the relationship between longitudinal wave impedance data volume and porosity is obtained, and the fracture reservoir is determined based on the spatial distribution according to the relationship function.

[0010] In the above implementation, an initial low-frequency model is established based on seismic and well logging data of the target area. Simultaneously, a fracture impedance model is established based on the seismic data. Then, a hybrid impedance low-frequency model is obtained from the initial low-frequency model and the fracture impedance model. This hybrid impedance low-frequency model allows for the depiction of the spatial distribution of the target area in both vertical and horizontal three-dimensional space. Inversion of this hybrid impedance low-frequency model yields the P-wave impedance data volume of the target area, which reflects information such as lithology and physical properties of the target area. Therefore, based on the P-wave impedance data volume and the relationship function between the P-wave impedance data volume and porosity, the spatial distribution of fractures and cavities within the target area can be accurately depicted, thus providing a more intuitive portrayal of the fracture-cavity connectivity of the reservoir.

[0011] According to an embodiment of this application, optionally, in the above-described method for determining fractured reservoirs, the step of establishing an initial low-frequency model based on the acquired seismic and well logging data in the target area includes:

[0012] Based on the acquired well logging data and seismic data, well-seismic calibration is performed to establish time-depth relationships;

[0013] Based on the time-depth relationship, a framework model of the clastic strata in the target area is established;

[0014] Based on the well logging data, determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area;

[0015] The frame model is laterally interpolated using the longitudinal wave impedance data to obtain the low-frequency impedance model of the clastic rock formation.

[0016] Based on the background P-wave impedance value, the background low-frequency P-wave impedance model of the carbonate rock strata in the target area is determined;

[0017] The initial low-frequency model is determined based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

[0018] According to an embodiment of this application, optionally, in the above-described method for determining fractured reservoirs, the well logging data includes: sonic data and density data of a single well, and the seismic data includes: seismic wavelet data. The step of establishing a time-depth relationship based on well-seismic calibration using the acquired well logging data and the seismic data includes:

[0019] The reflection coefficient is determined based on acoustic and density data from a single well.

[0020] The reflection coefficient and the seismic wavelet are convolved to obtain a synthetic seismic record;

[0021] The time-depth relationship is established based on the synthetic seismic record.

[0022] According to an embodiment of this application, optionally, in the above-described fracture reservoir determination method, establishing a fracture impedance model based on the seismic data includes:

[0023] The seismic data is subjected to structurally guided filtering to obtain filtered seismic data;

[0024] Based on the filtered seismic data, automatic fault detection (AFE) calculation is performed to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values.

[0025] Obtain the AFE threshold corresponding to the target region, and determine the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model.

[0026] According to an embodiment of this application, optionally, in the above-described fracture reservoir determination method, determining the fracture impedance model based on the AFE threshold and the AFE value in the intermediate fracture impedance model includes:

[0027] Obtain the constant impedance value corresponding to the target region;

[0028] The AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold are determined as the constant impedance values, and the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold are determined as null values, so as to obtain the crack impedance model.

[0029] According to an embodiment of this application, optionally, in the above-described fracture reservoir determination method, the process of inverting based on the hybrid impedance low-frequency model to determine the P-wave impedance data volume of the target region, and determining the spatial distribution of the target region based on the P-wave impedance data volume, includes:

[0030] Based on the seismic data, the hybrid impedance low-frequency model is used to perform constrained sparse pulse inversion to obtain the P-wave impedance data of the target area.

[0031] Based on the P-wave impedance data and the P-wave impedance threshold, the target P-wave impedance data is determined;

[0032] The spatial location corresponding to the target longitudinal wave impedance data is determined as the spatial distribution of the target region.

[0033] According to an embodiment of this application, optionally, in the above-described fracture reservoir determination method, obtaining a relationship function representing the relationship between P-wave impedance data and porosity, and determining the fracture reservoir based on the spatial distribution according to the relationship function, includes:

[0034] The porosity of the target region is calculated based on the relationship function and the longitudinal wave impedance data of the target region.

[0035] The fractured reservoir is determined based on the porosity.

[0036] Secondly, this application provides a fractured reservoir determination apparatus, the apparatus comprising:

[0037] The initial low-frequency model establishment module is used to establish an initial low-frequency model based on the acquired seismic and well logging data of the target area.

[0038] The fracture impedance model establishment module is used to establish a fracture impedance model based on the seismic data.

[0039] A hybrid impedance low-frequency model determination module is used to obtain a hybrid impedance low-frequency model based on the initial low-frequency model and the crack impedance model.

[0040] The longitudinal wave impedance data volume determination module is used to perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, so as to determine the spatial distribution of the target region based on the longitudinal wave impedance data volume.

[0041] The fracture determination module is used to obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function.

[0042] According to an embodiment of this application, optionally, in the above-mentioned fractured reservoir determination device, the initial low-frequency model establishment module includes:

[0043] The well-seismic calibration unit is used to establish time-depth relationships for well-seismic calibration based on the acquired well logging data and seismic data.

[0044] The frame model building unit is used to build a frame model of the clastic rock strata in the target area based on the time-depth relationship.

[0045] Impedance data determination unit, used to determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area based on the well logging data;

[0046] The low-frequency impedance model acquisition unit is used to perform lateral interpolation on the frame model using the longitudinal wave impedance data to obtain the low-frequency impedance model of the clastic rock strata.

[0047] The background low-frequency P-wave impedance model determination unit is used to determine the background low-frequency P-wave impedance model of the carbonate rock strata in the target area based on the background P-wave impedance value.

[0048] An initial low-frequency model determination unit is used to determine an initial low-frequency model based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

[0049] According to an embodiment of this application, optionally, in the above-mentioned fractured reservoir determination device, the logging data includes: acoustic data and density data of a single well, the seismic data includes: seismic wavelet data, and the well-seismic calibration unit includes:

[0050] The reflection coefficient determination sub-unit is used to determine the reflection coefficient based on acoustic and density data from a single well.

[0051] A synthetic seismic record acquisition sub-unit is used to convolve the reflection coefficient and the seismic wavelet to obtain a synthetic seismic record.

[0052] A time-depth relationship establishment sub-unit is used to establish the time-depth relationship based on the synthetic seismic record.

[0053] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture impedance model establishment module includes:

[0054] A construction-guided filtering unit is used to perform construction-guided filtering on the seismic data to obtain filtered seismic data.

[0055] The automatic fault detection unit is used to perform automatic fault detection AFE calculation based on the filtered seismic data to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values.

[0056] A crack impedance model determination unit is used to obtain the AFE threshold corresponding to the target region, and determine the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model.

[0057] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture impedance model determination unit includes:

[0058] A constant impedance value acquisition subunit is used to acquire the constant impedance value corresponding to the target region.

[0059] The crack impedance model sub-unit is used to determine the AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold as constant impedance values, and to determine the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold as null values, so as to obtain the crack impedance model.

[0060] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the longitudinal wave impedance data volume determination module includes:

[0061] The P-wave impedance data acquisition unit is used to perform constrained sparse pulse inversion based on the seismic data using the hybrid impedance low-frequency model to obtain the P-wave impedance data of the target area.

[0062] The target P-wave impedance data determination unit is used to determine the target P-wave impedance data based on the P-wave impedance data and the P-wave impedance threshold.

[0063] The spatial determination unit is used to determine the spatial location corresponding to the target longitudinal wave impedance data as the spatial distribution of the target region.

[0064] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture determination module includes:

[0065] A porosity calculation unit is used to calculate the porosity of the target region based on the relationship function and the longitudinal wave impedance data of the target region.

[0066] A fracture determination unit is used to determine the fractured reservoir based on the porosity.

[0067] Thirdly, this application provides a storage medium storing a computer program that can be executed by one or more processors and can be used to implement the fracture reservoir determination method described above.

[0068] Fourthly, this application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, which, when executed by the processor, performs the aforementioned fracture reservoir determination method.

[0069] In summary, this application provides a method, apparatus, storage medium, and electronic device for determining fractured reservoirs. The method includes: establishing an initial low-frequency model based on acquired seismic and well logging data of a target area; establishing a fracture impedance model based on the seismic data; obtaining a hybrid impedance low-frequency model based on the initial low-frequency model and the fracture impedance model; performing inversion on the hybrid impedance low-frequency model to determine the P-wave impedance data volume of the target area, and determining the spatial distribution of the target area based on the P-wave impedance data volume; obtaining a relationship function representing the relationship between the P-wave impedance data volume and porosity, and determining the fractured reservoir based on the spatial distribution based on the relationship function. Establishing an initial low-frequency model based on seismic and well logging data of the target area, and simultaneously establishing a fracture impedance model based on the seismic data, followed by the hybrid impedance low-frequency model obtained from the initial low-frequency model and the fracture impedance model, allows for the characterization of reservoir distribution in vertical and horizontal three-dimensional space based on the hybrid impedance low-frequency model. Inversion of the hybrid impedance low-frequency model yields the P-wave impedance data volume of the target area, which reflects information such as lithology and physical properties of the target area. Therefore, based on the P-wave impedance data volume and the relationship function between the P-wave impedance data volume and porosity, the spatial distribution of fractures and cavities within the target area can be accurately characterized, thus providing a more intuitive depiction of the fracture-cavity connectivity of the reservoir. Furthermore, this allows for accurate calculation of oil and gas resource scale, providing a reliable basis for well location deployment, thereby improving the success rate of exploration and development drilling and ultimately enhancing exploration and development efficiency. Moreover, this method is not limited by geographical location and has a wide range of applications. Attached Figure Description

[0070] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0071] Figure 1 This is a flowchart illustrating a method for determining fractured reservoirs provided in Embodiment 1 of this application.

[0072] Figure 2 This is a structural block diagram of a fracture reservoir determination device provided in Embodiment 4 of this application.

[0073] Figure 3 This is a connection block diagram of an electronic device provided in Embodiment Six of this application.

[0074] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0075] The following detailed description of the embodiments of this application, in conjunction with the accompanying drawings, will provide a thorough understanding of how this application uses technical means to solve technical problems and achieve corresponding technical effects, enabling its implementation. The embodiments of this application and the various features within them can be combined with each other without conflict, and all resulting technical solutions are within the protection scope of this application.

[0076] Example 1

[0077] This invention provides a method for determining fractured reservoirs. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps:

[0078] Step S110: Establish an initial low-frequency model based on the acquired seismic and well logging data of the target area.

[0079] Based on seismic and well logging data, an initial low-frequency model reflecting the basic geological characteristics of sedimentary bodies can be established. This low-frequency model can be obtained by interpolating and extrapolating well logging data across the entire data volume, constrained by the interpretation of stratigraphic positions and sedimentary patterns from seismic data. Alternatively, seismic velocity spectrum information from seismic data can be combined with well logging data to establish the initial low-frequency model, which can compensate for some of the missing low-frequency information in the seismic data. When establishing the initial low-frequency model based on seismic and well logging data, high-quality well curves from the well logging data can be selected, and interpolation can be performed using certain algorithms under constraints such as stratigraphic positions and faults, such as weighted methods, kriging, and inverse distance weighting. Besides establishing a low-frequency model using seismic velocity conversion as mentioned above, a single-well interpolation can also be used to establish the initial low-frequency model. By comparing the differences between the synthetic record and the original seismic data through forward modeling, pseudo-wells can be added in areas with significant differences to alter the low-frequency model information. Through continuous updates, a relatively realistic low-frequency model can be obtained. To take into account the characteristics of earthquake reflection, the boundaries of different lithologies and fluids can be delineated by attributes such as earthquake amplitude and frequency, and different elastic properties can be defined for each phase zone to obtain an initial low-frequency model.

[0080] Step S120: Establish a fracture impedance model based on the seismic data.

[0081] Tectonic deformation is one of the main causes of fractured reservoir formation. Tectonic deformation and fractures share a common origin, and tectonic deformation has a significant impact on the spatial distribution characteristics of fractures. Faults are an important manifestation of tectonic deformation. Although faults receive relatively little attention during the exploration stage, they have a significant impact on oilfield development. Fractures can improve reservoir permeability and also serve as hydrocarbon reservoirs. The geometric characteristics of seismic data are important attributes for effectively describing fractured reservoirs. Common geometric seismic attributes include coherence, curvature, dip, and azimuth. Therefore, when establishing a fracture impedance model based on seismic data, it can be mainly based on the above-mentioned geometric seismic attributes. Specifically, the required geometric seismic attribute data in the seismic data is determined, then an eigenvalue coherence body is generated. Based on the coherence body, automatic fault extraction (AFE) calculation is performed, and then a fracture impedance model is established based on the results of the automatic fault extraction calculation.

[0082] Step S130: Based on the initial low-frequency model and the crack impedance model, obtain the hybrid impedance low-frequency model.

[0083] Specifically, the low-frequency model can be used to replace the corresponding null values ​​in the crack impedance model to obtain a hybrid impedance low-frequency model. Since the crack impedance model contains null values, replacing these null values ​​with the values ​​corresponding to the initial low-frequency model in step S110 yields the hybrid impedance low-frequency model.

[0084] The initial low-frequency model can characterize the lateral features of the target area, while the crack impedance model can qualitatively characterize the longitudinal geometric features of the crack. The hybrid impedance low-frequency model obtained from the initial low-frequency model and the crack impedance model can characterize the spatial distribution of the target area in both longitudinal and lateral three-dimensional space.

[0085] Step S140: Perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, and determine the spatial distribution of the target region based on the longitudinal wave impedance data volume.

[0086] According to an embodiment of this application, step S140 includes the following steps:

[0087] Step S141: Based on the seismic data, perform constrained sparse pulse inversion using the hybrid impedance low-frequency model to obtain the P-wave impedance data of the target area.

[0088] Inverting a low-frequency hybrid impedance model based on seismic data allows for the full utilization of structural, stratigraphic, and lithological information provided by both seismic and well logging data. This information transforms the changes in conventional seismic reflection amplitude into P-wave impedance data for the target area, reflecting its lithology and physical properties. The P-wave impedance data for the target area can accurately analyze the bedrock mineral composition and porosity. During the exposure period, the bedrock weakens and becomes less porous as weathering and leaching progresses from shallow to deep, resulting in a higher P-wave impedance. When the bedrock is completely unaffected by surface water weathering and leaching, its porosity approaches zero, and the P-wave impedance value is at its maximum and is only related to the mineral composition of the rock.

[0089] Specifically, the seismic data can be meticulously processed first to extract parameters such as the seismic body and seismic wavelet, and then constrained sparse pulse inversion can be performed on the initial low-frequency model. Constrained sparse pulse inversion is a recursive seismic impedance inversion method. It broadens the effective bandwidth of the input seismic data by adjusting the sparsity of the reflection coefficient sequence, and obtains an elastic parameter model, a sparsity constraint factor, seismic signal-to-noise ratio (SNR), merging frequency, and wavelet scaling factor. The seismic SNR is used to constrain the similarity between the inversion result and the seismic data. The higher the SNR setting, the more correlated the synthesized record converted from the inversion result is with the earthquake, and vice versa. The sparsity constraint factor is the sparsity of the reflection coefficient sequence. The smaller the value of the sparsity constraint factor, the sparser the reflection coefficient sequence.

[0090] Step S142: Determine the target longitudinal wave impedance data based on the longitudinal wave impedance data and the longitudinal wave impedance threshold.

[0091] After obtaining the inversion results through constrained sparse pulse inversion, the P-wave impedance threshold can be obtained. When obtaining the P-wave impedance threshold, based on the cavernous reservoir actually drilled, well-seismic calibration can be used to determine the P-wave impedance value corresponding to the position of the cavernous reservoir on the inverted P-wave impedance profile where the "beaded" reflections occur. Combined with the P-wave impedance value corresponding to the cavernous reservoir obtained from the actual well drilling, the P-wave impedance threshold of the cavernous reservoir is determined. Then, based on the P-wave impedance data and the P-wave impedance threshold, the target P-wave impedance data is determined from the P-wave impedance data.

[0092] Specifically, the target P-wave impedance data can be determined based on the following process: First, the P-wave impedance data is compared with the P-wave impedance threshold; then, the portion of the P-wave impedance data smaller than the P-wave impedance threshold is identified as the target P-wave impedance data. For example, in carbonate rock formations, P-wave impedance data smaller than this P-wave impedance threshold is identified as the target P-wave impedance data for cavernous reservoirs. Constrained sparse pulse inversion is performed on the target low-frequency model based on the P-wave impedance threshold to characterize the P-wave impedance data of the target region. P-wave impedance data smaller than the threshold is retained and identified as target P-wave impedance data, while P-wave impedance data larger than the threshold is discarded. Thus, the spatial characterization of the target region can be achieved based on the retained target P-wave impedance data.

[0093] Step S143: Determine the spatial location corresponding to the target longitudinal wave impedance data as the spatial distribution of the target region.

[0094] After obtaining the target P-wave impedance data, the obtained full-band target P-wave impedance volume can be used to more accurately characterize the cavern reservoir.

[0095] Step S150: Obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function.

[0096] The P-wave impedance data volume is related to porosity. Therefore, a corresponding functional relationship between the two can be established in advance based on the P-wave impedance data volume and porosity obtained from actual drilling data. Thus, the spatial porosity distribution of the target area can be calculated based on the target P-wave impedance data and the functional relationship, thereby enabling the determination of fractured reservoirs in the target area.

[0097] Specifically, when obtaining the relationship function representing the relationship between P-wave impedance data volume and porosity, and determining the fractured reservoir based on the spatial distribution according to the relationship function, the porosity of the target region can be calculated first according to the relationship function and the P-wave impedance data volume of the target region; then the fractured reservoir can be determined according to the porosity.

[0098] In summary, this application provides a method for determining fractured reservoirs, comprising: establishing an initial low-frequency model based on acquired seismic and well logging data of a target area; establishing a fracture impedance model based on the seismic data; obtaining a hybrid impedance low-frequency model based on the initial low-frequency model and the fracture impedance model; performing inversion based on the hybrid impedance low-frequency model to determine the P-wave impedance data volume of the target area, thereby determining the spatial distribution of the target area based on the P-wave impedance data volume; obtaining a relational function representing the relationship between the P-wave impedance data volume and porosity, thereby determining the fractured reservoir based on the spatial distribution based on the relational function. The method establishes an initial low-frequency model based on seismic and well logging data of the target area, and simultaneously establishes a fracture impedance model based on the seismic data. Then, the hybrid impedance low-frequency model obtained from the initial low-frequency model and the fracture impedance model enables the depiction of reservoir distribution in vertical and horizontal three-dimensional space based on the hybrid impedance low-frequency model. The P-wave impedance data volume of the target area is obtained by inversion of the hybrid impedance low-frequency model, and the P-wave impedance data volume reflects information such as lithology and physical properties of the target area. Therefore, based on the longitudinal wave impedance data volume and the relationship function between the longitudinal wave impedance data volume and porosity, the spatial distribution of fractures and cavities within the target area can be accurately characterized, thereby intuitively depicting the fracture-cavity connectivity of the reservoir.

[0099] Example 2

[0100] Based on Example 1, this example illustrates the method in Example 1 through specific implementation cases.

[0101] The method for determining fractured reservoirs provided in this application includes:

[0102] Step S110: Establish an initial low-frequency model based on the acquired seismic and well logging data of the target area.

[0103] Step S120: Establish a fracture impedance model based on the seismic data.

[0104] Step S130: Based on the initial low-frequency model and the crack impedance model, obtain the hybrid impedance low-frequency model.

[0105] Step S140: Perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, and determine the spatial distribution of the target region based on the longitudinal wave impedance data volume.

[0106] Step S150: Obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function.

[0107] In the above-mentioned method for determining fractured reservoirs, step S110 includes the following steps:

[0108] Step S1110: Based on the acquired well logging data and seismic data, perform well-seismic calibration to establish time-depth relationship.

[0109] Seismic and well logging data can be used to interpret the structure of a target area and predict reservoirs, thus providing a detailed description of the oil reservoir. However, well logging data describes the vertical scale as depth, while seismic data describes the profile as time. These two data types have different description methods and therefore cannot be directly used together. Well-seismic calibration between the two data types is necessary. Well-seismic calibration can be performed based on the correlation between the synthetic seismic record in the seismic data and the waveform of the seismic trace near the well. Alternatively, reflection coefficients can be calculated using sonic and density logging data. A synthetic seismic record similar to the seismic trace can be constructed using the convolution of the emission coefficient and the wavelet. The calibration results can then be adjusted by comparing the synthetic seismic record with the seismic trace near the well. For example, a sample well in the target area can be identified, and a single-well depth-domain synthetic seismic record can be obtained based on this sample well. Then, based on the single-well depth-domain synthetic seismic record, a correspondence between time and depth at a single well can be established. Next, the geological strata of a single well are converted from the depth domain to the time domain, and a time domain geological strata model is established. Finally, the remaining well strata in the study area are automatically matched to the time domain geological strata model, thereby realizing the rapid well-seismic calibration of all wells.

[0110] Step S1120: Establish a framework model of the clastic rock strata in the target area based on the time-depth relationship.

[0111] The time-depth relationship obtained from well-seismic calibration can map different geological interfaces from single-well analysis onto seismic profiles, that is, from the depth domain to the time domain. Therefore, seismic data can be used to spatially track different geological interfaces and obtain their spatial distribution. These different geological interfaces can then be used to establish a framework model of clastic rock strata.

[0112] Step S1130: Determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area based on the well logging data;

[0113] Step S1140: Use the longitudinal wave impedance data to perform lateral interpolation on the frame model to obtain the low-frequency impedance model of the clastic rock formation.

[0114] Step S1150: Based on the background P-wave impedance value, determine the background low-frequency P-wave impedance model of the carbonate rock strata in the target area;

[0115] Step S1160: Determine the initial low-frequency model based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

[0116] Under the constraints of the frame model, the P-wave impedance values ​​of different single wells are interpolated laterally to obtain the low-frequency impedance model interpolated within the well. Due to the strong lateral heterogeneity of carbonate rocks, the single-well lateral interpolation model cannot reflect the lateral distribution characteristics of carbonate strata. Therefore, the low-frequency model interpolated within the well can be used for the clastic rock strata above the top surface of the carbonate rocks (T74 seismic reflection interface); below T74, the carbonate rock strata are represented by the background P-wave impedance values ​​of the carbonate rock strata, thus replacing the low-frequency model. In this case, the low-frequency model for the carbonate rock strata is a constant, flat low-frequency model. Here, the background P-wave impedance value can be represented by a constant to represent the background value of the carbonate rocks. Through this method, the anomalies in the seismic data of the carbonate rock strata can reflect reservoir changes, eliminating the artifacts caused by the anomalies in the low-frequency model interpolated within the well, and truly reflecting the actual subsurface conditions.

[0117] In the aforementioned method for determining fractured reservoirs, the well logging data includes: sonic data and density data from a single well; the seismic data includes: seismic wavelet data; and step S1110 includes the following steps:

[0118] Step S1111: Determine the reflection coefficient based on the acoustic and density data of a single well.

[0119] After converting the time-domain wavelet to the depth domain, the waveform undergoes either compression or stretching with depth due to the influence of velocity. Therefore, the reflection coefficient can be calculated based on acoustic and density data. When calculating the reflection coefficient, a high-quality well-side seismic trace should be selected on the depth migration profile to calculate the dominant frequency of the wavelet. A zero-phase wavelet should be used. Before calculating the reflection coefficient, the acoustic transit time curve and density curve should be corrected and outlier removed.

[0120] Step S1112: Convolve the reflection coefficient and the seismic wavelet to obtain a synthetic seismic record.

[0121] Convolution, also known as integral transformation, is a mathematical method of integral transformation. It is a mathematical operator that generates a third function from two functions, representing the integral of the product of the overlapping function values ​​of two functions after flipping and translation, over the overlap length. Synthetic seismic records obtained through convolution are seismic records, or seismic traces, artificially synthesized from sonic logging or vertical seismic profile data. It is a widely used technique in seismic modeling and forms the basis for stratigraphic calibration, reservoir characterization, and other work, serving as an intermediate medium for converting geological models into seismic information. Synthetic seismic records bridge the gap between high-resolution logging information and regional seismic information; their accuracy directly affects the accurate calibration of geological stratigraphic levels.

[0122] Step S1113: Establish the time-depth relationship based on the synthetic seismic record.

[0123] Well data is in the depth domain, while seismic data is in the time domain. Reflection coefficients are obtained from the sonic and density data of a single well. A synthetic seismic record is generated by convolving the seismic wavelet with the reflection coefficients. The synthetic record profile is then calibrated against the seismic profiles obtained through the well, thus converting the depth-domain data to the time domain. By convolving the reflection coefficients and the seismic wavelet into a synthetic seismic record, a precise time-depth relationship can be established, ensuring accurate identification of fractured reservoirs.

[0124] Example 3

[0125] Based on Example 1, this example illustrates the method in Example 1 through specific implementation cases.

[0126] When establishing a fracture impedance model based on the seismic data, the following process can be adopted. First, the seismic data is subjected to structurally guided filtering to obtain filtered seismic data; then, automatic fault detection (AFE) calculation is performed based on the filtered seismic data to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values; finally, the AFE threshold corresponding to the target area is obtained, and the fracture impedance model is determined based on the AFE threshold and the AFE values ​​in the intermediate fracture impedance model.

[0127] Specifically, when determining the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model, the constant impedance value corresponding to the target region can be obtained first; then, the AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold are determined as the constant impedance values, and the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold are determined as null values, so as to obtain the crack impedance model.

[0128] Specifically, structurally guided filtering is applied to the raw seismic data. This improves the signal-to-noise ratio, making the continuity or discontinuity of seismic phase axes more apparent, facilitating the interpretation of seismic horizons and faults, and providing a data foundation for subsequent correlation calculations and fault identification. AFE (Advanced Element Filtering) is then calculated based on the filtered seismic data to obtain AFE values. Furthermore, when obtaining the AFE threshold for the target area, relevant data on drilled fractures can be acquired first. Well-seismic calibration is then performed based on this data to determine the AFE value corresponding to the fracture location; this value serves as the fracture's AFE threshold. When determining the fracture impedance model based on the AFE threshold and the AFE values ​​in the intermediate fracture impedance model, AFE values ​​greater than the threshold are replaced with a constant carbonate background impedance value, representing fractures in the target area; AFE values ​​less than or equal to the threshold are set to null values, representing non-fractures in the target area, thus establishing the fracture impedance model.

[0129] The crack impedance model contains null values. By replacing the null values ​​in the crack impedance model with the values ​​corresponding to the initial low-frequency model in step S110, the hybrid impedance low-frequency model can be obtained.

[0130] Example 4

[0131] Please refer to Figure 2 This application provides a fracture reservoir identification apparatus 200, which includes:

[0132] The initial low-frequency model establishment module 210 is used to establish an initial low-frequency model based on the acquired seismic and well logging data of the target area.

[0133] The fracture impedance model establishment module 220 is used to establish a fracture impedance model based on the seismic data.

[0134] The mixed impedance low-frequency model determination module 230 is used to obtain a mixed impedance low-frequency model based on the initial low-frequency model and the crack impedance model.

[0135] The longitudinal wave impedance data volume determination module 240 is used to perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, so as to determine the spatial distribution of the target region based on the longitudinal wave impedance data volume.

[0136] The fracture determination module 250 is used to obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function.

[0137] According to an embodiment of this application, optionally, in the above-mentioned fractured reservoir determination device, the initial low-frequency model establishment module includes:

[0138] The well-seismic calibration unit is used to establish time-depth relationships for well-seismic calibration based on the acquired well logging data and seismic data.

[0139] The frame model building unit is used to build a frame model of the clastic rock strata in the target area based on the time-depth relationship.

[0140] Impedance data determination unit, used to determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area based on the well logging data;

[0141] The low-frequency impedance model acquisition unit is used to perform lateral interpolation on the frame model using the longitudinal wave impedance data to obtain the low-frequency impedance model of the clastic rock strata.

[0142] The background low-frequency P-wave impedance model determination unit is used to determine the background low-frequency P-wave impedance model of the carbonate rock strata in the target area based on the background P-wave impedance value.

[0143] An initial low-frequency model determination unit is used to determine an initial low-frequency model based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

[0144] According to an embodiment of this application, optionally, in the above-mentioned fractured reservoir determination device, the logging data includes: acoustic data and density data of a single well, the seismic data includes: seismic wavelet data, and the well-seismic calibration unit includes:

[0145] The reflection coefficient determination sub-unit is used to determine the reflection coefficient based on acoustic and density data from a single well.

[0146] A synthetic seismic record acquisition sub-unit is used to convolve the reflection coefficient and the seismic wavelet to obtain a synthetic seismic record.

[0147] A time-depth relationship establishment sub-unit is used to establish the time-depth relationship based on the synthetic seismic record.

[0148] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture impedance model establishment module includes:

[0149] A construction-guided filtering unit is used to perform construction-guided filtering on the seismic data to obtain filtered seismic data.

[0150] The automatic fault detection unit is used to perform automatic fault detection AFE calculation based on the filtered seismic data to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values.

[0151] A crack impedance model determination unit is used to obtain the AFE threshold corresponding to the target region, and determine the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model.

[0152] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture impedance model determination unit includes:

[0153] A constant impedance value acquisition subunit is used to acquire the constant impedance value corresponding to the target region.

[0154] The crack impedance model sub-unit is used to determine the AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold as constant impedance values, and to determine the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold as null values, so as to obtain the crack impedance model.

[0155] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the longitudinal wave impedance data volume determination module includes:

[0156] The P-wave impedance data acquisition unit is used to perform constrained sparse pulse inversion based on the seismic data using the hybrid impedance low-frequency model to obtain the P-wave impedance data of the target area.

[0157] The target P-wave impedance data determination unit is used to determine the target P-wave impedance data based on the P-wave impedance data and the P-wave impedance threshold.

[0158] The spatial determination unit is used to determine the spatial location corresponding to the target longitudinal wave impedance data as the spatial distribution of the target region.

[0159] According to an embodiment of this application, optionally, in the above-mentioned fracture reservoir determination device, the fracture determination module includes:

[0160] A porosity calculation unit is used to calculate the porosity of the target region based on the relationship function and the longitudinal wave impedance data of the target region.

[0161] A fracture determination unit is used to determine the fractured reservoir based on the porosity.

[0162] In summary, this application provides a fractured reservoir determination device, comprising: an initial low-frequency model establishment module, used to establish an initial low-frequency model based on acquired seismic and well logging data of a target area; a fracture impedance model establishment module, used to establish a fracture impedance model based on the seismic data; a mixed impedance low-frequency model determination module, used to obtain a mixed impedance low-frequency model based on the initial low-frequency model and the fracture impedance model; a P-wave impedance data volume determination module, used to perform inversion based on the mixed impedance low-frequency model to determine the P-wave impedance data volume of the target area, so as to determine the spatial distribution of the target area based on the P-wave impedance data volume; and a fracture determination module, used to obtain a relationship function representing the relationship between the P-wave impedance data volume and porosity, so as to determine the fractured reservoir based on the spatial distribution based on the relationship function. By establishing an initial low-frequency model based on seismic and well logging data of the target area, simultaneously establishing a fracture impedance model based on the seismic data, and then obtaining a mixed impedance low-frequency model based on the initial low-frequency model and the fracture impedance model, the reservoir distribution can be characterized in vertical and horizontal three-dimensional space based on the mixed impedance low-frequency model. Inverting the hybrid impedance low-frequency model yields the P-wave impedance data volume for the target region, which reflects information such as lithology and physical properties. Therefore, based on the P-wave impedance data volume and the relationship function between the P-wave impedance data volume and porosity, the spatial distribution of fractures and cavities within the target region can be accurately characterized, thus providing a direct depiction of the fracture-cavity connectivity of the reservoir.

[0163] Example 5

[0164] This embodiment also provides a computer-readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, server, app store, etc., which stores a computer program. When the computer program is executed by a processor, it can implement the following method steps:

[0165] Step S110: Establish an initial low-frequency model based on the acquired seismic and well logging data of the target area.

[0166] Step S120: Establish a fracture impedance model based on the seismic data.

[0167] Step S130: Based on the initial low-frequency model and the crack impedance model, obtain the hybrid impedance low-frequency model.

[0168] Step S140: Perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, and determine the spatial distribution of the target region based on the longitudinal wave impedance data volume.

[0169] Step S150: Obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function.

[0170] Optionally, in the above method for determining fractured reservoirs, step S110 includes the following steps:

[0171] Based on the acquired well logging data and seismic data, well-seismic calibration is performed to establish time-depth relationships;

[0172] Based on the time-depth relationship, a framework model of the clastic strata in the target area is established;

[0173] Based on the well logging data, determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area;

[0174] The frame model is laterally interpolated using the longitudinal wave impedance data to obtain the low-frequency impedance model of the clastic rock formation.

[0175] Based on the background P-wave impedance value, the background low-frequency P-wave impedance model of the carbonate rock strata in the target area is determined;

[0176] The initial low-frequency model is determined based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

[0177] Optionally, in the above method for determining fractured reservoirs, the well logging data includes: sonic data and density data of a single well; the seismic data includes: seismic wavelet data; and the step of establishing a time-depth relationship based on well-seismic calibration using the acquired well logging data and seismic data includes:

[0178] The reflection coefficient is determined based on acoustic and density data from a single well.

[0179] The reflection coefficient and the seismic wavelet are convolved to obtain a synthetic seismic record;

[0180] The time-depth relationship is established based on the synthetic seismic record.

[0181] Optionally, in the above method for determining fractured reservoirs, establishing a fracture impedance model based on the seismic data includes:

[0182] The seismic data is subjected to structurally guided filtering to obtain filtered seismic data;

[0183] Based on the filtered seismic data, automatic fault detection (AFE) calculation is performed to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values.

[0184] Obtain the AFE threshold corresponding to the target region, and determine the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model.

[0185] Optionally, in the above method for determining fractured reservoirs, determining the fracture impedance model based on the AFE threshold and the AFE value in the intermediate fracture impedance model includes:

[0186] Obtain the constant impedance value corresponding to the target region;

[0187] The AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold are determined as the constant impedance values, and the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold are determined as null values, so as to obtain the crack impedance model.

[0188] Optionally, in the above-mentioned fractured reservoir determination method, the process of inverting based on the hybrid impedance low-frequency model to determine the P-wave impedance data volume of the target region, and determining the spatial distribution of the target region based on the P-wave impedance data volume, includes:

[0189] Based on the seismic data, the hybrid impedance low-frequency model is used to perform constrained sparse pulse inversion to obtain the P-wave impedance data of the target area.

[0190] Based on the P-wave impedance data and the P-wave impedance threshold, the target P-wave impedance data is determined;

[0191] The spatial location corresponding to the target longitudinal wave impedance data is determined as the spatial distribution of the target region.

[0192] Optionally, in the above-described method for determining fractured reservoirs, obtaining a relationship function representing the relationship between P-wave impedance data and porosity, and determining the fractured reservoir based on the spatial distribution according to the relationship function, includes:

[0193] The porosity of the target region is calculated based on the relationship function and the longitudinal wave impedance data of the target region.

[0194] The fractured reservoir is determined based on the porosity.

[0195] For a detailed description of the above method steps, please refer to Example 1. This example will not be repeated here.

[0196] Example 6

[0197] This application provides an electronic device, which may be a mobile phone, computer, or tablet computer, etc., including a memory and a processor. The memory stores a calculator program, which, when executed by the processor, implements the fractured reservoir determination method as described in Embodiment 1. It can be understood that... Figure 3 As shown, the electronic device 300 may further include: a processor 301, a memory 302, a multimedia component 303, an input / output (I / O) interface 304, and a communication component 305.

[0198] The processor 301 is used to execute all or part of the steps in the fractured reservoir determination method as described in Embodiment 1. The memory 302 is used to store various types of data, which may include, for example, instructions for any application or method in an electronic device, as well as application-related data.

[0199] The processor 301 may be implemented as an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field-programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the fracture reservoir determination method in Embodiment 1 above.

[0200] The memory 302 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0201] Multimedia component 303 may include a screen, which may be a touchscreen, and an audio component for outputting and / or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory or transmitted via a communication component. The audio component also includes at least one speaker for outputting audio signals.

[0202] I / O interface 304 provides an interface between processor 301 and other interface modules, such as keyboards, mice, and buttons. These buttons can be virtual or physical buttons.

[0203] The communication component 305 is used for wired or wireless communication between the electronic device 300 and other devices. Wireless communication includes, for example, Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination thereof. Therefore, the corresponding communication component 305 may include: a Wi-Fi module, a Bluetooth module, or an NFC module.

[0204] In summary, this application provides a method, apparatus, storage medium, and electronic device for determining fractured reservoirs. The method includes: establishing an initial low-frequency model based on acquired seismic and well logging data of a target area; establishing a fracture impedance model based on the seismic data; obtaining a hybrid impedance low-frequency model based on the initial low-frequency model and the fracture impedance model; performing inversion on the hybrid impedance low-frequency model to determine the P-wave impedance data volume of the target area, thereby determining the spatial distribution of the target area based on the P-wave impedance data volume; and obtaining a relational function representing the relationship between the P-wave impedance data volume and porosity, thereby determining the fractured reservoir based on the spatial distribution according to the relational function. Establishing an initial low-frequency model based on seismic and well logging data of the target area, and simultaneously establishing a fracture impedance model based on the seismic data, followed by the hybrid impedance low-frequency model obtained from the initial low-frequency model and the fracture impedance model, allows for the characterization of reservoir distribution in vertical and horizontal three-dimensional space based on the hybrid impedance low-frequency model. Inversion of the hybrid impedance low-frequency model yields the P-wave impedance data volume of the target area, which reflects information such as lithology and physical properties of the target area. Therefore, based on the longitudinal wave impedance data volume and the relationship function between the longitudinal wave impedance data volume and porosity, the spatial distribution of fractures and cavities within the target area can be accurately characterized, thus enabling a more intuitive depiction of the fracture-cavity connectivity of the reservoir.

[0205] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system and method embodiments described above are merely illustrative.

[0206] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0207] Although the embodiments disclosed in this application are as described above, the content is merely for the purpose of facilitating understanding of this application and is not intended to limit this application. Any person skilled in the art to which this application pertains may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application; however, the scope of patent protection of this application shall still be determined by the scope defined in the appended claims.

Claims

1. A method for determining fractured reservoirs, characterized in that, The method includes: An initial low-frequency model is established based on the acquired seismic and well logging data of the target area; A fracture impedance model was established based on the aforementioned seismic data; Based on the initial low-frequency model and the crack impedance model, a hybrid impedance low-frequency model is obtained; Inversion is performed based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, and the spatial distribution of the target region is determined based on the longitudinal wave impedance data volume. Obtain a relational function representing the relationship between longitudinal wave impedance data volume and porosity, and determine the fracture reservoir based on the spatial distribution according to the relational function; The fracture impedance model established based on the aforementioned seismic data includes: The seismic data is subjected to structurally guided filtering to obtain filtered seismic data; Based on the filtered seismic data, automatic fault detection (AFE) calculation is performed to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values. Obtain the AFE threshold corresponding to the target region, and determine the fracture impedance model based on the AFE threshold and the AFE value in the intermediate fracture impedance model; The determination of the crack impedance model based on the AFE threshold and the AFE value in the intermediate crack impedance model includes: Obtain the constant impedance value corresponding to the target region; The AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold are determined as the constant impedance values, and the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold are determined as null values, so as to obtain the crack impedance model. The process of obtaining a hybrid impedance low-frequency model based on the initial low-frequency model and the crack impedance model includes: filling the empty values ​​in the crack impedance model with the impedance values ​​corresponding to the initial low-frequency model to achieve vertical and horizontal three-dimensional spatial fusion, thereby obtaining the hybrid impedance low-frequency model.

2. The method according to claim 1, characterized in that, The acquired seismic and well logging data for the target area are used to establish an initial low-frequency model, including: Based on the acquired well logging data and seismic data, well-seismic calibration is performed to establish time-depth relationships; Based on the time-depth relationship, a framework model of the clastic strata in the target area is established; Based on the well logging data, determine the depth-direction P-wave impedance data and background P-wave impedance data of the target area; The frame model is laterally interpolated using the longitudinal wave impedance data to obtain the low-frequency impedance model of the clastic rock formation. Based on the background P-wave impedance data, the background low-frequency P-wave impedance model of the carbonate rock strata in the target area is determined. The initial low-frequency model is determined based on the low-frequency impedance model and the background low-frequency longitudinal wave impedance model.

3. The method according to claim 2, characterized in that, The well logging data includes: sonic data and density data of a single well; the seismic data includes: seismic wavelet data; the well-seismic calibration based on the acquired well logging data and seismic data to establish a time-depth relationship includes: The reflection coefficient is determined based on acoustic and density data from a single well. The reflection coefficient and the seismic wavelet are convolved to obtain a synthetic seismic record; The time-depth relationship is established based on the synthetic seismic record.

4. The method according to claim 1, characterized in that, Inversion is performed based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region. Determining the spatial distribution of the target region based on the longitudinal wave impedance data volume includes: Based on the seismic data, the hybrid impedance low-frequency model is used to perform constrained sparse pulse inversion to obtain the P-wave impedance data of the target area. Based on the P-wave impedance data and the P-wave impedance threshold, the target P-wave impedance data is determined; The spatial location corresponding to the target longitudinal wave impedance data is determined as the spatial distribution of the target region.

5. The method according to claim 1, characterized in that, Obtaining a relationship function representing the relationship between P-wave impedance data volume and porosity, and determining the fracture reservoir based on the spatial distribution according to the relationship function, includes: The porosity of the target region is calculated based on the relationship function and the longitudinal wave impedance data of the target region. The fractured reservoir is determined based on the porosity.

6. A device for determining fractured reservoirs, characterized in that, The device includes: The initial low-frequency model establishment module is used to establish an initial low-frequency model based on the acquired seismic and well logging data of the target area. The fracture impedance model establishment module is used to establish a fracture impedance model based on the seismic data. A hybrid impedance low-frequency model determination module is used to obtain a hybrid impedance low-frequency model based on the initial low-frequency model and the crack impedance model. The longitudinal wave impedance data volume determination module is used to perform inversion based on the hybrid impedance low-frequency model to determine the longitudinal wave impedance data volume of the target region, so as to determine the spatial distribution of the target region based on the longitudinal wave impedance data volume. The fracture determination module is used to obtain a relationship function representing the relationship between longitudinal wave impedance data volume and porosity, so as to determine the fracture reservoir based on the spatial distribution according to the relationship function; The crack impedance model establishment module is also used for: The seismic data is subjected to structurally guided filtering to obtain filtered seismic data; Based on the filtered seismic data, automatic fault detection (AFE) calculation is performed to obtain the intermediate fracture impedance model of the target area; the intermediate fracture impedance model includes AFE values. Obtain the AFE threshold corresponding to the target region, and determine the fracture impedance model based on the AFE threshold and the AFE value in the intermediate fracture impedance model; The crack impedance model establishment module is also used for: Obtain the constant impedance value corresponding to the target region; The AFE values ​​in the intermediate crack impedance model that are greater than the AFE threshold are determined as the constant impedance values, and the AFE values ​​in the intermediate crack impedance model that are less than the AFE threshold are determined as null values, so as to obtain the crack impedance model. The hybrid impedance low-frequency model determination module is also used for: The null values ​​in the crack impedance model are filled with the impedance values ​​corresponding to the initial low-frequency model to achieve three-dimensional spatial fusion of longitudinal and transverse aspects, thus obtaining the hybrid impedance low-frequency model.

7. A storage medium, characterized in that, The computer program stored in the storage medium, when executed by one or more processors, is used to implement the fracture reservoir determination method as described in any one of claims 1-5.

8. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the fractured reservoir determination method as described in any one of claims 1-5.

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