Carbonate rock base rock background phase prediction method, device and equipment based on multi-wave field

Abstract

The embodiment of the present application provides a kind of carbonate rock bed background facies prediction method, device and equipment based on multi-wave field, which comprises the following steps: obtaining the multi-wave field data of carbonate rock target layer;Determine the full-wave field post-stack wave impedance of carbonate rock target layer using constrained sparse pulse inversion technology;The diffraction wave band-limited wave impedance is fused with low-frequency impedance body to obtain the diffraction wave field post-stack wave impedance of carbonate rock target layer;Determine the reflection wave field post-stack wave impedance of carbonate rock target layer using constrained sparse pulse inversion technology;Full-wave field post-stack wave impedance, diffraction wave field post-stack wave impedance and reflection wave field post-stack wave impedance are analyzed by three-dimensional data body intersection, to determine the large-scale fracture-cave reservoir region, small-scale fracture-cave reservoir region and bed background facies region of carbonate rock target layer, which can not only describe different scale fracture-cave reservoir and bed background facies in carbonate rock target layer in detail, but also fill the blank of carbonate rock bed background facies prediction.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of oil and gas geophysics, specifically to a method, apparatus and equipment for predicting the background facies of carbonate bedrock based on multi-wave fields. Background Technology

[0002] Carbonate rocks comprise approximately 20% of global sedimentary rocks, yet their oil and gas production accounts for about 60% of global output, highlighting their crucial role in oil and gas exploration and development. Carbonate reservoirs are high-permeability reservoirs with fracture-vuggy reservoirs, meaning their storage space is primarily composed of fractures and cavities. The seepage pathways are typically formed by fractures and connected solution pores and cavities. With the continuous development of fracture-vuggy carbonate reservoirs, the prediction and quantitative analysis of the bedrock background facies (non-reservoir) are of significant value. This is crucial for identifying and describing fracture-vuggy structures, determining the separation and connectivity between cavities, and providing a method for fully utilizing the structural residual oil in fracture-vuggy carbonate reservoirs. Therefore, the prediction of the bedrock background facies in carbonate rocks is of paramount importance.

[0003] Chinese patent application 202011155062.1 proposes a wave impedance inversion method and a method and system for predicting heterogeneous carbonate reservoirs. This method utilizes a lithological probability volume calculation model to determine the lithological probability volume of the target layer carbonate pore reservoir and the non-reservoir lithological probability volume in the study area. Under the constraint of the lithological probability volume, geostatistical stochastic inversion is performed to obtain a third wave impedance inversion data volume, thus completing the wave impedance inversion. This method can distinguish between caverns and stable bedrock, but it cannot meet the requirements for small-scale geological targets. Chinese patent application 201711422492.3 provides a method and apparatus for obtaining the internal structure of carbonate fracture-cavity bodies. This method determines the spatial structure of the fracture-cavity body based on the beaded seismic facies outside the carbonate fracture-cavity body, the porosity threshold of the target layer inside the carbonate fracture-cavity body, the porosity data volume of cave-type reservoirs, the porosity data volume of pore-type reservoirs, and the porosity data volume of fracture-type reservoirs. This method only utilizes full-field seismic data and porosity data obtained through well logging calibration via seismic impedance inversion to identify the spatial structure of fractures and cavities, making it difficult to describe small-scale fractures and cavities and the background facies of carbonate bedrock. Zhang Yuanyin et al. proposed carbonate reservoir identification based on pure P-wave seismic data. Addressing the characteristics of deep burial, strong heterogeneity, and high seismic data quality requirements of the paleokarst carbonate reservoirs in the Tarim Basin, they introduced pre-stack inversion to obtain pure P-wave seismic data, replacing full-stack seismic data, to improve the accuracy of impedance inversion and reservoir prediction. Tang Xiangrong et al. proposed that well logging data is detailed vertically and sparse horizontally, while seismic data is coarse vertically and dense horizontally, and that well logging-constrained inversion is used for carbonate reservoir prediction.

[0004] In summary, existing methods are mostly focused on the identification and prediction of fractured-vuggy reservoirs, lacking research on the background facies of carbonate bedrock (non-reservoir). Therefore, a method for predicting the background facies of carbonate bedrock is urgently needed. Summary of the Invention

[0005] This invention provides a method, apparatus, and equipment for predicting the background facies of carbonate bedrock based on multi-wave fields, thereby filling the gap in the prediction of background facies of carbonate bedrock.

[0006] In a first aspect, embodiments of the present invention provide a method for predicting the background facies of carbonate bedrock based on multi-wave fields, including: Acquire pre-stack depth migration seismic data volumes, diffraction data volumes, reflection data volumes, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer; Based on pre-stack depth migration seismic data, sonic logging data, density logging data, well logging layer data, and seismic interpretation layer data, the full-field post-stack impedance of the target carbonate layer was determined using constrained sparse pulse inversion technology. The post-stack impedance of the diffraction wave field of the target carbonate rock layer is obtained by fusing the zone-limited impedance of the diffraction wave with the low-frequency impedance volume. The zone-limited impedance of the diffraction wave is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. Based on the reflected wave data volume and the low-frequency seismic inversion model, the post-stack wave impedance of the reflected wave field of the target carbonate rock layer was determined by constrained sparse pulse inversion technique. Based on the wave impedance range of various types of geological bodies, a three-dimensional data volume intersection analysis was conducted on the post-stack wave impedance of the full wave field, the post-stack wave impedance of the diffracted wave field, and the post-stack wave impedance of the reflected wave field to determine the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

[0007] In one embodiment, the method further includes: The stacked wave impedance of the full-wave field, the stacked wave impedance of the diffracted wave field, and the stacked wave impedance of the reflected wave field are fused to obtain a three-dimensional category fused data volume. Based on the basic color model, multi-attribute volume fusion and display of 3D category fusion data volume is performed.

[0008] In one embodiment, the method further includes: Based on the three-dimensional category fusion data volume and the seismic properties of the target carbonate rock layer, the connectivity and separation relationships between wells and / or between caves are determined. The seismic properties include fractures and cracks.

[0009] In one embodiment, before performing a three-dimensional data volume intersection analysis on the post-stack wave impedance of the full-wave field, the post-stack wave impedance of the diffracted wave field, and the post-stack wave impedance of the reflected wave field according to the wave impedance range of various types of geological bodies, the method further includes: Obtain drilling vent loss and acid fracturing data for the target carbonate rock formation; Based on drilling venting and acid fracturing data, determine the venting and leakage fractured reservoir wave impedance threshold, the reservoir acid fracturing wave impedance threshold, and the bedrock background wave impedance threshold. The impedance ranges of large-scale fractured-vuggy reservoirs, small-to-medium-scale fractured-vuggy reservoirs, and bedrock background facies are determined based on the venting and leakage fractured-vuggy reservoir impedance threshold, the reservoir acid fracturing impedance threshold, and the bedrock background impedance threshold.

[0010] In one embodiment, the low-frequency seismic inversion model is determined according to the following process: Modify the logging impedance of the target carbonate rock layer to the bedrock background phase impedance; A low-frequency seismic inversion model was established by using the Kriging interpolation method and performing multiple iterations.

[0011] Secondly, embodiments of the present invention provide a multi-wave field-based device for predicting the background facies of carbonate bedrock, comprising: The acquisition module is used to acquire pre-stack depth migration seismic data volumes, diffraction wave data volumes, reflection wave data volumes, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer. The first determination module is used to determine the full-field post-stack impedance of the target carbonate rock layer based on pre-stack depth migration seismic data, sonic logging data, density logging data, logging layer data, and seismic interpretation layer data, using constrained sparse pulse inversion technology. The second determining module is used to fuse the diffraction wave zone-limited impedance with the low-frequency impedance volume to obtain the post-stack wave impedance of the diffraction wave field of the target layer of carbonate rock. The diffraction wave zone-limited impedance is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. The third determination module is used to determine the post-stack wave impedance of the reflected wave field of the target carbonate rock layer based on the reflected wave data volume and the seismic inversion low-frequency model, using constrained sparse pulse inversion technology. The analysis module is used to perform three-dimensional data volume intersection analysis on the post-stack impedance of the full wave field, the post-stack impedance of the diffracted wave field, and the post-stack impedance of the reflected wave field based on the wave impedance range of various types of geological bodies, in order to determine the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

[0012] In one embodiment, the device further includes: The fusion module is used to fuse the post-stacked wave impedance of the full-wave field, the post-stacked wave impedance of the diffracted wave field, and the post-stacked wave impedance of the reflected wave field to obtain a three-dimensional category fusion data volume. The display module is used to perform multi-attribute volume fusion display on 3D category fusion data based on the color basic model.

[0013] In one embodiment, the device further includes: The judgment module is used to determine the connectivity and separation relationships between wells and / or between caves based on the seismic attributes of the 3D category fusion data volume and the target carbonate rock layer. The seismic attributes include fractures and cracks.

[0014] Thirdly, embodiments of the present invention provide an electronic device, comprising: At least one processor and memory; The memory stores the instructions that the computer executes; At least one processor executes computer execution instructions stored in memory, causing the at least one processor to perform the multi-wave field-based carbonate bedrock background facies prediction method as described in any of the first aspects.

[0015] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the multi-wave field-based method for predicting the background facies of carbonate bedrock as described in any of the first aspects.

[0016] The method, apparatus, and equipment for predicting the bedrock background facies of carbonate rocks based on multi-wavefield data provided in this invention first acquire multi-wavefield data (full-wavefield data, reflected wavefield data, and diffracted wavefield data), providing a data foundation for classifying and describing fractured-vuggy reservoirs and bedrock background facies. Then, based on pre-stack depth migration seismic data, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data, constrained sparse pulse inversion technology is used to determine the full-wavefield post-stack acoustic impedance of the target carbonate layer, identifying large-scale fractured-vuggy reservoirs. Finally, the diffracted waveband impedance is fused with the low-frequency impedance data to obtain... The post-stack impedance of the diffracted wave field of the target carbonate rock layer was obtained to identify small- and medium-scale fracture-vuggy reservoirs. Based on the reflected wave data and the low-frequency seismic inversion model, the constrained sparse pulse inversion technique was used to determine the post-stack impedance of the reflected wave field of the target carbonate rock layer and identify the bedrock background facies. Finally, through the cross-analysis of the three-dimensional data volume, the large-scale fracture-vuggy reservoir region, the small- and medium-scale fracture-vuggy reservoir region, and the bedrock background facies region of the target carbonate rock layer were determined. This not only provides a detailed description of fracture-vuggy reservoirs and bedrock background facies at different scales in the target carbonate rock layer, but also fills the gap in the prediction of bedrock background facies of carbonate rocks. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] Figure 1 A flowchart illustrating a method for predicting the background facies of carbonate bedrock based on multi-wave field according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the seismic profile of the full wave field, reflected wave field, and diffracted wave field of a target carbonate rock layer in a certain work area, provided as an embodiment of the present invention. Figure 3 This is a schematic cross-sectional view of the full-wave field post-stack impedance, reflected wave field post-stack impedance, and diffracted wave field post-stack impedance of the target carbonate rock layer in a certain work area through well W1, as provided in an embodiment of the present invention. Figure 4 This is a schematic cross-sectional view of the large-scale fractured-vuggy reservoir, medium- and small-scale fractured-vuggy reservoir, and bedrock background facies of the target carbonate layer in a certain work area provided by an embodiment of the present invention. Figure 5 A flowchart of a method for predicting the background facies of carbonate bedrock based on multi-wave field, provided in another embodiment of the present invention; Figure 6 This is a schematic diagram of the seismic profile and category fusion data volume of the target carbonate rock layer in a certain work area through well W1, provided in an embodiment of the present invention. Figure 7 A flowchart of a method for predicting the background facies of carbonate bedrock based on multi-wave field, provided for another embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of a multi-wave field-based carbonate bedrock background facies prediction device provided in an embodiment of the present invention. Figure 9 A schematic diagram of the structure of a multi-wave field-based carbonate bedrock background facies prediction device provided in another embodiment of the present invention; Figure 10 A schematic diagram of the structure of a multi-wave field-based carbonate bedrock background facies prediction device provided in another embodiment of the present invention; Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0019] The accompanying drawings have illustrated specific embodiments of the invention, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the invention in any way, but rather to illustrate the concept of the invention to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0020] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0021] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0022] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0023] Example 1 Figure 1 This is a flowchart illustrating a method for predicting the background facies of carbonate bedrock based on multi-wave fields, provided in an embodiment of the present invention. Figure 1 As shown, the method for predicting the background facies of carbonate bedrock based on multi-wave fields provided in this embodiment may include: S101. Acquire pre-stack depth migration seismic data volume, diffraction wave data volume, reflection wave data volume, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer.

[0024] In this embodiment, multi-wave field data of the target carbonate rock layer can be obtained directly by an instrument, or it can be obtained from publicly available literature, or it can be obtained from the intermediate process of data processing.

[0025] In this embodiment, the pre-stack depth migration seismic data, sonic logging data, density logging data, well logging stratigraphic data, and seismically interpreted stratigraphic data of the target carbonate rock layer reflect the full wavefield information of the target carbonate rock layer. Full wavefield information can accurately describe the large-scale fractures and cavities and structural features in the target carbonate rock layer. Please refer to [reference needed]. Figure 2 The diagram in (a) shows a full-wavefield seismic profile. The reflected wave data volume of the target carbonate rock layer embodies the reflected wavefield information of the target carbonate rock layer. This reflected wavefield information can describe the continuous and stable bedrock background facies in the target carbonate rock layer. Please refer to [reference needed]. Figure 2 The diagram in (b) shows a seismic profile of the reflected wave field. The diffraction wave data volume of the target carbonate rock layer embodies the diffraction wave field information of the target carbonate rock layer. The diffraction wave field information can describe the small-to-medium scale fractures and cavities and structural features in the target carbonate rock layer. Please refer to [reference needed]. Figure 2 The diagram in (c) shows a seismic profile of the diffracted wave field.

[0026] It should be noted that the large-scale and small-to-medium-scale cracks in this application follow the industry's generally accepted classification standards. If a scale threshold is set, cracks larger than the scale threshold are considered large-scale cracks, while cracks smaller than or equal to the scale threshold are considered small-to-medium-scale cracks.

[0027] S102. Based on the pre-stack depth migration seismic data, sonic logging data, density logging data, well logging layer data, and seismic interpretation layer data, the full-field post-stack impedance of the target carbonate layer is determined using constrained sparse pulse inversion technology.

[0028] Pre-stack depth migration seismic data volumes contain various geological information and can accurately describe large-scale fracture-cavity and structural features. In this embodiment, constrained sparse pulse inversion (CSSI) technology can be used to determine the full-field post-stack acoustic impedance of the target carbonate layer from pre-stack depth migration seismic data volumes, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data. Among these, CSSI technology is one of the more mature acoustic impedance inversion techniques. In this embodiment, existing CSSI technologies can be used, such as the CSSI technology described on pages 45-50 of the "Post-stack Constrained Sparse Pulse Inversion Chinese Training Tutorial" by Fugro Geosciences (Beijing) Co., Ltd.

[0029] Full-field post-stack impedance data can identify well-connected, large-scale fracture-vuggy reservoirs. The full-field post-stack impedance of the target carbonate layer determined in this embodiment can be referenced... Figure 3 As shown in (a). Figure 3As shown in (a), the full-wave field post-stack impedance identification of large-scale fracture-vuggy reservoirs is effective.

[0030] S103. The diffraction wave zone-limited impedance and the low-frequency impedance volume are fused to obtain the post-stack wave impedance of the diffraction wave field of the target carbonate rock layer. The diffraction wave zone-limited impedance is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model.

[0031] Diffraction wave data volumes can reflect information about geological anomalies that differ from the background bedrock facies, such as small- to medium-scale fractures, pinch-outs, and fault boundaries. However, due to the strong amplitude and waveform variations of diffraction information, it cannot be directly predicted or inverted. In this embodiment, the band-limited impedance of the diffraction wave is first obtained from the diffraction wave data volume. Then, the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. Finally, the band-limited impedance of the diffraction wave is fused with the low-frequency impedance volume of the low-frequency model to obtain the absolute impedance volume of the diffraction wave, i.e., the post-stack impedance of the diffraction wave field.

[0032] Post-stack diffraction wavefield impedance data can identify small- to medium-scale fracture-vuggy reservoirs. The post-stack diffraction wavefield impedance of the target carbonate layer determined in this embodiment can be referenced... Figure 3 As shown in (c). Figure 3 As shown in (c), the post-stack wave impedance identification of diffracted wave fields has a significant effect on small-scale fracture-cavity reservoirs.

[0033] Given the strong lateral heterogeneity of carbonate rocks, the establishment of a low-frequency model is crucial during the inversion process. In one optional implementation, the seismic inversion low-frequency model is determined according to the following process: first, the well logging impedance of the target carbonate layer is modified to the bedrock background facies impedance; then, Kriging interpolation is used and iterated multiple times to establish the seismic inversion low-frequency model. In this embodiment, during the low-frequency model establishment process, the well logging impedance of the target carbonate layer can be manually modified to the bedrock background facies impedance, and Kriging interpolation is used to establish the well-controlled low-frequency model. Multiple iterations are then performed to obtain a relatively smooth and stable low-frequency model, thereby ensuring that the inversion effect can reflect the fracture-cavity characteristics to the greatest extent.

[0034] S104. Based on the reflected wave data volume and the low-frequency seismic inversion model, the post-stack impedance of the reflected wave field of the target carbonate rock layer is determined using the constrained sparse pulse inversion technique.

[0035] Although the reflected wave field can reflect continuous and stable background response information, it cannot obtain the background response information of the bedrock before the development of fractures and cavities. Therefore, the reflected wave field cannot be directly equated with the bedrock wave field. In this embodiment, the reflected wave data volume obtained in step S101 and the seismic inversion low-frequency model in step S103 are used to determine the post-stack wave impedance of the reflected wave field of the target carbonate rock layer using constrained sparse pulse inversion technology.

[0036] The post-stack acoustic impedance data volume of the reflected wave field can identify the stable sedimentary bedrock background facies. The post-stack acoustic impedance of the carbonate rock target layer determined in this embodiment can be referenced... Figure 3 As shown in (b). Figure 3 As shown in (b), the reflection wave field after stacking impedance is effective in identifying the background facies of stable sedimentary bedrock.

[0037] S105. Based on the wave impedance range of each type of geological body, perform three-dimensional data volume intersection analysis on the full-field post-stack wave impedance, diffraction wave field post-stack wave impedance, and reflection wave field post-stack wave impedance to determine the large-scale fracture-cavity reservoir region, medium- and small-scale fracture-cavity reservoir region, and bedrock background facies region of the target carbonate rock layer.

[0038] It is understandable that different types of geological bodies have different wave impedance ranges. For example, large-scale fracture-cavity reservoirs correspond to the first wave impedance range, medium- and small-scale fracture-cavity reservoirs correspond to the second wave impedance range, and bedrock backgrounds correspond to the third wave impedance range.

[0039] After obtaining the wave impedance ranges of various types of geological bodies, three-dimensional data volume intersection analysis can be performed on the full-field post-stack wave impedance determined in step S102, the diffraction wave field post-stack wave impedance determined in step S103, and the reflection wave field post-stack wave impedance determined in step S104, thereby determining the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

[0040] Please refer to Figure 4 , Figure 4 (a) is a schematic cross-section of a large-scale fractured-vuggy reservoir in the target carbonate rock layer of a certain work area through well W1. Figure 4 (b) is a schematic cross-section of a small-scale fractured-vuggy reservoir in the target carbonate rock layer of a certain work area through well W1. Figure 4 (c) is a schematic cross-section of the target carbonate rock layer in a certain work area through the bedrock background facies of well W1.

[0041] The multi-wavelength-field-based method for predicting the bedrock background facies of carbonate rocks provided in this embodiment first acquires multi-wavelength-field data (full-wavelength data, reflected wavelength data, and diffracted wavelength data), providing a data foundation for classifying and describing fractured-vuggy reservoirs and bedrock background facies. Then, based on pre-stack depth migration seismic data, sonic logging data, density logging data, well logging layer data, and seismic interpretation stratigraphic data, the constrained sparse pulse inversion technique is used to determine the full-wavelength post-stack acoustic impedance of the target carbonate layer, identifying large-scale fractured-vuggy reservoirs. Finally, the diffracted wavelength-limited impedance is fused with the low-frequency impedance volume to obtain the carbonate... The post-stack impedance of the diffracted wave field of the target carbonate rock layer was used to identify small- and medium-scale fracture-vuggy reservoirs. Based on the reflected wave data and the low-frequency seismic inversion model, the post-stack impedance of the reflected wave field of the target carbonate rock layer was determined using constrained sparse pulse inversion technology to identify the bedrock background facies. Finally, through three-dimensional data volume intersection analysis, the large-scale fracture-vuggy reservoir region, the small- and medium-scale fracture-vuggy reservoir region, and the bedrock background facies region of the target carbonate rock layer were determined. This not only provides a detailed description of fracture-vuggy reservoirs and bedrock background facies at different scales in the target carbonate rock layer, but also fills the gap in the prediction of bedrock background facies of carbonate rocks.

[0042] Example 2 Figure 5 This is a flowchart illustrating a method for predicting the background facies of carbonate bedrock based on multi-wave fields, provided as another embodiment of the present invention. Figure 5 As shown, the method for predicting the background facies of carbonate bedrock based on multi-wave fields provided in this embodiment may include: S101. Acquire pre-stack depth migration seismic data volume, diffraction wave data volume, reflection wave data volume, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer.

[0043] S102. Based on the pre-stack depth migration seismic data, sonic logging data, density logging data, well logging layer data, and seismic interpretation layer data, the full-field post-stack impedance of the target carbonate layer is determined using constrained sparse pulse inversion technology.

[0044] S103. The diffraction wave zone-limited impedance and the low-frequency impedance volume are fused to obtain the post-stack wave impedance of the diffraction wave field of the target carbonate rock layer. The diffraction wave zone-limited impedance is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model.

[0045] S104. Based on the reflected wave data volume and the low-frequency seismic inversion model, the post-stack impedance of the reflected wave field of the target carbonate rock layer is determined using the constrained sparse pulse inversion technique.

[0046] S105. Based on the wave impedance range of each type of geological body, perform three-dimensional data volume intersection analysis on the full-field post-stack wave impedance, diffraction wave field post-stack wave impedance, and reflection wave field post-stack wave impedance to determine the large-scale fracture-cavity reservoir region, medium- and small-scale fracture-cavity reservoir region, and bedrock background facies region of the target carbonate rock layer.

[0047] The specific implementation of steps S101-S105 in this embodiment can be referred to in Embodiment 1, and will not be repeated here.

[0048] S106. The stacked wave impedance of the full wave field, the stacked wave impedance of the diffracted wave field, and the stacked wave impedance of the reflected wave field are fused to obtain a three-dimensional category fused data volume.

[0049] S107. Based on the color basic model, perform multi-attribute volume convergence and display on the three-dimensional category fusion data volume.

[0050] After determining the full-field post-stack impedance, diffracted-field post-stack impedance, and reflected-field post-stack impedance of the target carbonate rock layer, these impedances can be fused to obtain a three-dimensional category-fused data volume that can finely characterize the spatial distribution of fracture-vuggy reservoirs and bedrock background facies at different scales within the target carbonate rock layer. This provides a data foundation for determining the structure and connectivity of fracture-vuggy reservoirs. Furthermore, for greater intuitiveness, the three-dimensional category-fused data volume can be displayed through multi-attribute volume convergence based on a color-based model. For example, different colors can be used to represent large-scale fracture-vuggy reservoir regions, medium- and small-scale fracture-vuggy reservoir regions, and bedrock background facies regions.

[0051] Please refer to Figure 6 , Figure 6 This is a schematic diagram of the seismic profile and category fusion data volume of the target carbonate rock layer in a certain work area provided by an embodiment of the present invention. Figure 6 The upper image is a schematic diagram of a seismic profile, and the lower image is a schematic diagram of a 3D category-fused data volume profile. In the lower image, three different grayscale values ​​are used to represent large-scale fracture-cavities, medium- and small-scale fracture-cavities, and bedrock, respectively. By comparing the two images, the spatial distribution of fracture-cavity reservoirs and bedrock background facies at different scales in the target carbonate rock layer can be more clearly and intuitively understood.

[0052] The multi-wavefield-based method for predicting the bedrock background facies of carbonate rocks provided in this embodiment, based on the above embodiment, further obtains a three-dimensional category fusion data volume by fusing the full-wavefield post-stack impedance, the diffracted wavefield post-stack impedance, and the reflected wavefield post-stack impedance. This can more clearly characterize the fractured-vuggy reservoirs and bedrock background facies at different scales in the target carbonate rock layer. Furthermore, based on the color basic model, the three-dimensional category fusion data volume is displayed through multi-attribute volume convergence and fusion, which can more intuitively show the fractured-vuggy reservoirs and bedrock background facies at different scales in the target carbonate rock layer.

[0053] Example 3 Figure 7 A flowchart illustrating a method for predicting the background facies of carbonate bedrock based on multi-wave fields, provided in another embodiment of the present invention. Figure 7 As shown, the method for predicting the background facies of carbonate bedrock based on multi-wave fields provided in this embodiment may include: S101. Acquire pre-stack depth migration seismic data volume, diffraction wave data volume, reflection wave data volume, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer.

[0054] S102. Based on the pre-stack depth migration seismic data, sonic logging data, density logging data, well logging layer data, and seismic interpretation layer data, the full-field post-stack impedance of the target carbonate layer is determined using constrained sparse pulse inversion technology.

[0055] S103. The diffraction wave zone-limited impedance and the low-frequency impedance volume are fused to obtain the post-stack wave impedance of the diffraction wave field of the target carbonate rock layer. The diffraction wave zone-limited impedance is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model.

[0056] S104. Based on the reflected wave data volume and the low-frequency seismic inversion model, the post-stack impedance of the reflected wave field of the target carbonate rock layer is determined using the constrained sparse pulse inversion technique.

[0057] S105. Based on the wave impedance range of each type of geological body, perform three-dimensional data volume intersection analysis on the full-field post-stack wave impedance, diffraction wave field post-stack wave impedance, and reflection wave field post-stack wave impedance to determine the large-scale fracture-cavity reservoir region, medium- and small-scale fracture-cavity reservoir region, and bedrock background facies region of the target carbonate rock layer.

[0058] S106. The stacked wave impedance of the full wave field, the stacked wave impedance of the diffracted wave field, and the stacked wave impedance of the reflected wave field are fused to obtain a three-dimensional category fused data volume.

[0059] S107. Based on the color basic model, perform multi-attribute volume convergence and display on the three-dimensional category fusion data volume.

[0060] The specific implementation of steps S101-S107 in this embodiment can be referred to the above embodiment, and will not be repeated here.

[0061] S108. Based on the three-dimensional category fusion data volume and the seismic attributes of the target carbonate rock layer, determine the connectivity and separation relationships between wells and / or between caves. The seismic attributes include fractures and cracks.

[0062] After obtaining the three-dimensional category fusion data volume, it is possible to further combine seismic attributes such as fractures and cracks to determine the connectivity and separation between wells and between cavities. This provides a technical means for identifying the structure of fractured-cavity reservoirs, a better discrimination method for identifying fractured-cavity structures and connectivity and separation, and technical support for finding structural residual oil in fractured-cavity reservoirs. It has great practical value and is worth further promotion and application.

[0063] The multi-wave field-based method for predicting the background facies of carbonate bedrock provided in this embodiment, based on the above embodiment, further determines the connectivity and separation relationships between wells and / or between cavities by using the three-dimensional category fusion data volume and the seismic attributes of the target carbonate layer. This provides a technical means for identifying fracture-cavity structures and connectivity separations, and provides technical support for finding structural residual oil in fracture-cavity reservoirs, which has great practical value.

[0064] Example 4 It is understandable that the acoustic impedance ranges of the same type of geological body in different carbonate rocks may not be exactly the same. For example, the acoustic impedance range of a large-scale fracture-vuggy reservoir in carbonate rocks located at location A is not the same as that of a large-scale fracture-vuggy reservoir in carbonate rocks located at location B. Therefore, to further improve the accuracy of spatial regions of fractured-vuggy reservoirs and bedrock background facies at different scales in the target carbonate rock layer, the multi-wavefield-based carbonate rock bedrock background facies prediction method provided in this embodiment may include, before performing three-dimensional data volume intersection analysis on the full-wavefield post-stack wave impedance, diffracted wavefield post-stack wave impedance, and reflected wavefield post-stack wave impedance according to the wave impedance intervals of various types of geological bodies, the following steps may also be taken: acquiring well venting and acid fracturing data of the target carbonate rock layer; determining the wave impedance threshold values ​​of venting and leaking fractured-vuggy reservoirs, reservoir acid fracturing wave impedance threshold values, and bedrock background wave impedance threshold values ​​based on the well venting and leaking fractured-vuggy reservoirs and acid fracturing data; and determining the wave impedance intervals of large-scale fractured-vuggy reservoirs, medium- and small-scale fractured-vuggy reservoirs, and bedrock background facies based on the wave impedance threshold values ​​of venting and leaking fractured-vuggy reservoirs, reservoir acid fracturing wave impedance threshold values, and bedrock background wave impedance threshold values. The wave impedance ranges of large-scale fractured-vuggy reservoirs, medium- and small-scale fractured-vuggy reservoirs, and bedrock background facies, determined by drilling venting and acid fracturing data of the target carbonate layer, help improve the accuracy of identifying spatial regions of fractured-vuggy reservoirs and bedrock background facies at different scales in the target carbonate layer.

[0065] Example 5 Figure 8 This is a schematic diagram of a multi-wave field-based carbonate bedrock background facies prediction device provided in an embodiment of the present invention. Figure 8As shown, the carbonate bedrock background facies prediction device 20 based on multi-wave field provided in this embodiment may include: an acquisition module 201, a first determination module 202, a second determination module 203, a third determination module 204, and an analysis module 205.

[0066] Module 201 is used to acquire pre-stack depth migration seismic data volume, diffraction wave data volume, reflection wave data volume, sonic logging data, density logging data, logging layer data and seismic interpretation layer data of the target carbonate rock layer. The first determining module 202 is used to determine the full-field post-stack impedance of the target layer of carbonate rock by using constrained sparse pulse inversion technology based on the pre-stack depth migration seismic data volume, sonic logging data, density logging data, logging layer data and seismic interpretation layer data. The second determining module 203 is used to fuse the diffraction wave zone-limited impedance with the low-frequency impedance volume to obtain the post-stack wave impedance of the diffraction wave field of the target layer of carbonate rock. The diffraction wave zone-limited impedance is determined according to the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. The third determination module 204 is used to determine the post-stack wave impedance of the reflected wave field of the target layer of carbonate rock based on the reflected wave data volume and the seismic inversion low-frequency model, using constrained sparse pulse inversion technology. Analysis module 205 is used to perform three-dimensional data volume intersection analysis on the post-stack wave impedance of the whole wave field, the post-stack wave impedance of the diffracted wave field, and the post-stack wave impedance of the reflected wave field according to the wave impedance range of various types of geological bodies, so as to determine the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

[0067] The apparatus of this embodiment can be used to perform Figure 1 The technical solutions of the method embodiments shown are similar in principle and in effect, and will not be described again here.

[0068] Example 6 Figure 9 This is a schematic diagram of a multi-wave field-based carbonate bedrock background facies prediction device provided in another embodiment of the present invention. Figure 9 As shown, the multi-wave field-based carbonate bedrock background facies prediction device 20 provided in this embodiment predicts the background facies of the bedrock in carbonate rocks. Figure 8 Based on the embodiment shown, it also includes: a fusion module 206 and a display module 207.

[0069] The fusion module 206 is used to fuse the post-stacked wave impedance of the full-wave field, the post-stacked wave impedance of the diffracted wave field, and the post-stacked wave impedance of the reflected wave field to obtain a three-dimensional category fusion data volume. Display module 207 is used to perform multi-attribute volume convergence and display of three-dimensional category fusion data volume based on the color basic model.

[0070] The apparatus of this embodiment can be used to perform Figure 5 The technical solutions of the method embodiments shown are similar in principle and in effect, and will not be described again here.

[0071] Example 7 Figure 10 This is a schematic diagram of a multi-wave field-based carbonate bedrock background facies prediction device provided in another embodiment of the present invention. Figure 10 As shown, the multi-wave field-based carbonate bedrock background facies prediction device 20 provided in this embodiment predicts the background facies of the bedrock in carbonate rocks. Figure 9 Based on the illustrated embodiment, it also includes: The judgment module 208 is used to determine the connectivity and separation relationships between wells and / or between caves based on the three-dimensional category fusion data volume and the seismic attributes of the target carbonate rock layer. The seismic attributes include fractures and cracks.

[0072] The apparatus of this embodiment can be used to perform Figure 7 The technical solutions of the method embodiments shown are similar in principle and in effect, and will not be described again here.

[0073] Example 8 In one optional implementation, the analysis module is used to acquire wellbore leakage and acid fracturing data of the target carbonate rock layer before performing three-dimensional data volume intersection analysis on the full-wavelength back-stack impedance, diffracted wavelength back-stack impedance, and reflected wavelength back-stack impedance based on the wave impedance range of various types of geological bodies; determine the wave impedance threshold values ​​of the leakage fractured-vuggy reservoir, the reservoir acid fracturing wave impedance threshold value, and the bedrock background wave impedance threshold value based on the wellbore leakage fractured-vuggy reservoir and acid fracturing data; and determine the wave impedance ranges of large-scale fractured-vuggy reservoirs, medium- and small-scale fractured-vuggy reservoirs, and bedrock background facies based on the wave impedance threshold values ​​of the leakage fractured-vuggy reservoir, the reservoir acid fracturing wave impedance threshold value, and the bedrock background wave impedance threshold value.

[0074] Example 9 This invention also provides an electronic device, please refer to [link to relevant documentation]. Figure 11 As shown, the embodiments of the present invention are only used as examples. Figure 11 The examples are provided for illustration only and do not imply that the invention is limited to these examples. Figure 11 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present invention. Figure 11 As shown, the electronic device 30 provided in this embodiment may include: a memory 301, a processor 302, and a bus 303. The bus 303 is used to connect the various components.

[0075] The memory 301 stores a computer program, which, when executed by the processor 302, can implement the technical solutions of any of the above method embodiments.

[0076] The memory 301 and processor 302 are electrically connected directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines, such as bus 303. The memory 301 stores a computer program that implements a method for predicting the background facies of carbonate bedrock based on multi-wave fields, including at least one software functional module that can be stored in the memory 301 in the form of software or firmware. The processor 302 executes various functional applications and data processing by running the software program and modules stored in the memory 301.

[0077] The memory 301 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 301 stores programs, and the processor 302 executes the programs after receiving execution instructions. Furthermore, the software programs and modules within the memory 301 may also include an operating system, which may include various software components and / or drivers for managing system tasks (such as memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components.

[0078] Processor 302 can be an integrated circuit chip with signal processing capabilities. The aforementioned processor 302 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. It is understood that... Figure 11 The structure shown is for illustrative purposes only and may include more... Figure 11 The more or fewer components shown, or having the same Figure 11 The different configurations shown. Figure 11 The components shown can be implemented in hardware and / or software.

[0079] This invention also provides a computer-readable storage medium storing a computer program thereon, which is executed by a processor to implement the technical solutions of any of the above method embodiments.

[0080] The various embodiments in this disclosure are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0081] The scope of protection of this disclosure is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its scope and spirit. If such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, then the intent of this disclosure also includes such modifications and variations.

Claims

1. A method for predicting the background facies of carbonate bedrock based on multi-wave field, characterized in that, include: Acquire pre-stack depth migration seismic data volumes, diffraction data volumes, reflection data volumes, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer; Based on the pre-stack depth migration seismic data, the sonic logging data, the density logging data, the logging layer data, and the seismic interpretation layer data, the full-field post-stack impedance of the target carbonate layer is determined using constrained sparse pulse inversion technology. The diffraction wave field post-stack impedance of the target carbonate rock layer is obtained by fusing the diffraction wave zone-limited impedance with the low-frequency impedance volume. The diffraction wave zone-limited impedance is determined based on the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. Based on the reflected wave data volume and the seismic inversion low-frequency model, the post-stack wave impedance of the reflected wave field of the target carbonate rock layer is determined by constrained sparse pulse inversion technology. Based on the wave impedance range of each type of geological body, a three-dimensional data volume intersection analysis is performed on the full-field post-stack wave impedance, the diffracted wave field post-stack wave impedance, and the reflected wave field post-stack wave impedance to determine the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

2. The method according to claim 1, characterized in that, The method further includes: The full-wave field stacked wave impedance, the diffracted wave field stacked wave impedance, and the reflected wave field stacked wave impedance are fused to obtain a three-dimensional category fusion data volume; The three-dimensional category fusion data volume is displayed by multi-attribute volume convergence and fusion based on the basic color model.

3. The method according to claim 2, characterized in that, The method further includes: Based on the three-dimensional category fusion data volume and the seismic properties of the target carbonate rock layer, the connectivity and separation relationships between wells and / or between caves are determined, and the seismic properties include fractures and cracks.

4. The method according to claim 1, characterized in that, Before performing three-dimensional data volume intersection analysis on the post-stacked wave impedance of the full-wave field, the post-stacked wave impedance of the diffracted wave field, and the post-stacked wave impedance of the reflected wave field according to the wave impedance range of each type of geological body, the method further includes: Obtain drilling venting and acid pressure data for the target carbonate rock formation; Based on the drilling venting and acid fracturing data, determine the venting and acid fracturing reservoir background wave impedance threshold, the reservoir acid fracturing wave impedance threshold, and the bedrock background wave impedance threshold. The impedance ranges of large-scale fractured-vuggy reservoirs, medium- and small-scale fractured-vuggy reservoirs, and bedrock background facies are determined based on the venting and leakage fractured-vuggy reservoir impedance threshold value, the reservoir acid fracturing impedance threshold value, and the bedrock background impedance threshold value.

5. The method according to any one of claims 1-4, characterized in that, The earthquake inversion low-frequency model is determined according to the following process: The logging impedance of the target carbonate rock layer was modified to the bedrock background phase impedance. A low-frequency seismic inversion model was established by using the Kriging interpolation method and performing multiple iterations.

6. A device for predicting the background facies of carbonate bedrock based on multi-wave fields, characterized in that, include: The acquisition module is used to acquire pre-stack depth migration seismic data volumes, diffraction wave data volumes, reflection wave data volumes, sonic logging data, density logging data, well logging stratigraphic data, and seismic interpretation stratigraphic data of the target carbonate rock layer. The first determining module is used to determine the full-field post-stack impedance of the target carbonate rock layer using constrained sparse pulse inversion technology based on the pre-stack depth migration seismic data volume, the sonic logging data, the density logging data, the logging layer data, and the seismic interpretation layer data. The second determining module is used to fuse the diffraction wave zone-limited impedance with the low-frequency impedance volume to obtain the post-stack wave impedance of the diffraction wave field of the target carbonate rock layer. The diffraction wave zone-limited impedance is determined according to the diffraction wave data volume, and the low-frequency impedance volume is obtained from the seismic inversion low-frequency model. The third determination module is used to determine the post-stack wave impedance of the reflected wave field of the target carbonate rock layer based on the reflected wave data volume and the seismic inversion low-frequency model, using constrained sparse pulse inversion technology. The analysis module is used to perform three-dimensional data volume intersection analysis on the full-field post-stack wave impedance, the diffraction wave field post-stack wave impedance, and the reflection wave field post-stack wave impedance according to the wave impedance range of each type of geological body, so as to determine the large-scale fracture-cavity reservoir region, the medium- and small-scale fracture-cavity reservoir region, and the bedrock background facies region of the target carbonate rock layer.

7. The apparatus according to claim 6, characterized in that, include: The fusion module is used to fuse the full-wave field stacked wave impedance, the diffracted wave field stacked wave impedance, and the reflected wave field stacked wave impedance to obtain a three-dimensional category fusion data volume. The display module is used to perform multi-attribute volume convergence and display on the three-dimensional category fusion data volume based on the color basic model.

8. The apparatus according to claim 7, characterized in that, include: The judgment module is used to determine the connectivity and separation relationships between wells and / or between caves based on the three-dimensional category fusion data volume and the seismic attributes of the target carbonate rock layer. The seismic attributes include fractures and cracks.

9. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes the computer execution instructions stored in the memory, causing the at least one processor to perform the multi-wave field-based carbonate bedrock background facies prediction method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the multi-wave field-based carbonate bedrock background facies prediction method as described in any one of claims 1-5.

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