Fine reservoir prediction method for carbonate fractured-vuggy reservoir and related device

Abstract

The invention discloses a carbonate fractured-vuggy reservoir-oriented fine reservoir prediction method and a related device, and belongs to the field of oil-gas exploration reservoir prediction. According to the method, firstly, coherence enhancement attribute is made based on original post-stack seismic data, then a threshold value is determined after a coherence enhancement attribute value is calibrated, and the coherence enhancement value and the threshold value are compared, so that the fracture-cavity type reservoir and the boundary range of the fracture-cavity type reservoir are obtained; performing post-stack deterministic inversion based on the original seismic data, determining a longitudinal wave impedance boundary value of the cave-type reservoir and the surrounding rock by using a well drilled to the cave-type reservoir, and engraving the post-stack deterministic inversion by using the boundary value so as to obtain the cave-type reservoir and a boundary range thereof; and removing the cave-type reservoir by using the predicted fracture-cave-type reservoir to obtain the fracture-hole-type reservoir and the boundary range of the fracture-hole-type reservoir. According to the method, the distribution range of the fracture-hole type reservoir is indirectly obtained through the seismic attribute and post-stack determinacy inversion method, and accurate prediction of the fracture-hole type reservoir is achieved.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas exploration reservoir prediction, in particular to a fine reservoir prediction method and related devices for carbonate fracture-cavity reservoirs. Background Art

[0002] The carbonate reservoirs in oil fields are mainly composed of caves and fracture-pore reservoirs, which are characterized by irregular shapes and non-uniform distribution, which brings great difficulties to reservoir prediction. Conventional inversion methods cannot well describe the reservoir distribution characteristics.

[0003] At present, the fracture-vuggy carbonate reservoirs in Tarim Oilfield can be divided into two categories: Class I reservoirs refer to large-scale cave reservoirs with relatively large reservoir space, and Class II reservoirs refer to relatively large-scale fracture-hole reservoirs. There are two main reservoir prediction methods for fracture-vuggy carbonate reservoirs. One is to qualitatively describe the fracture-vuggy reservoirs through seismic attributes, such as qualitatively characterizing the boundaries of the fracture-vuggy reservoirs through coherent attributes and structural tensor attributes, and then carving the obtained attributes with a given threshold to characterize the boundaries of the fracture-vuggy reservoirs. However, the selection of the threshold is usually calibrated based on engineering anomalies on the well, such as emptying and leakage. Although this method can characterize the outline of the fracture-vuggy reservoir, it does not further divide the interior of the fracture-vuggy reservoir, and the characterization results are relatively rough. At the same time, the results of characterization of different attributes are also quite different, resulting in uncertainty in the prediction results of fracture-vuggy reservoirs. Another method is to use seismic inversion to qualitatively or semi-quantitatively characterize fracture-cavity reservoirs. This method is a method that closely combines well and seismic data. First, a rock physics analysis is performed on the target layer section in the well in the research area to determine the elastic parameter response range of the well cave reservoir, fracture-cavity reservoir, non-reservoir, etc. Then, a seismic inversion is performed based on the seismic data to obtain a seismic inversion result data body. Finally, based on the seismic inversion data body, the interpretation is performed according to the well rock physics analysis results to obtain the distribution of cave reservoirs, fracture-cavity reservoirs, and non-reservoir. However, due to the resolution and accuracy of the seismic inversion results, this method can only achieve a relatively accurate prediction of cave reservoirs in the subdivision of fracture-cavity reservoirs. The distribution of fracture-cavity reservoirs obtained by this method is not accurate. Conventional seismic inversion methods cannot achieve a relatively accurate prediction of fracture-cavity reservoirs in the subdivision of fracture-cavity reservoirs.

[0004] In recent years, some improvements have been made to the seismic inversion of carbonate fracture-cavity reservoirs, and a phase-controlled inversion method has been developed, which organically combines the temporal and spatial distribution of seismic phases with seismic inversion operations, so that seismic inversion can eliminate boundary effects to the greatest extent, thereby improving the accuracy of the inversion results. However, this method still only predicts the distribution range of fracture-cavity reservoirs by combining seismic inversion with logging rock physics analysis, and does not help to accurately predict the subdivision types within fracture-cavity reservoirs. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a fine reservoir prediction method and related devices for carbonate fracture-cavity reservoirs.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: A fine reservoir prediction method for carbonate fracture-vuggy reservoirs comprises the following steps: Step 1: Based on the original post-stack seismic data, coherence enhancement attributes are made, and the reservoir top position interpreted by well logging is used to calibrate the coherence enhancement attributes. The coherence enhancement attribute value corresponding to the reservoir top position interpreted by logging is used as a threshold, and a judgment is made based on the relationship between the coherence enhancement attribute value and the threshold to obtain the predicted fracture-cavity reservoir and its boundary; Performing post-stack deterministic inversion on the original post-stack seismic data and obtaining the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; carving the post-stack deterministic inversion results using the boundary value to obtain the predicted cave-type reservoir and its boundary; Step 2: Based on the predicted fracture-cavity reservoir, the cave-type reservoir is removed to obtain the fracture-cavity reservoir and its boundary range.

[0007] Furthermore, in step 1, the judgment is made according to the magnitude relationship between the coherence enhancement attribute value and the threshold, specifically: The coherence enhancement attribute value greater than the threshold is defined as 0, corresponding to the surrounding rock; all the coherence enhancement attribute values ​​less than or equal to the threshold are defined as 1, corresponding to the fracture-cavity reservoir, thereby obtaining the fracture-cavity reservoir and its boundary range.

[0008] Furthermore, in step 1, the demarcation value is used to carve the post-stack deterministic inversion result to obtain the predicted cave-type reservoir and its boundary range, specifically: The deterministic inversion result value greater than the cutoff value is defined as 0, representing the surrounding rock; The value of the deterministic inversion result less than or equal to the demarcation value is defined as 1, representing a cave-type reservoir, thereby obtaining a cave-type reservoir and its boundary range.

[0009] Furthermore, step 2 is specifically as follows: The definition value of the predicted fracture-cavity reservoir is subtracted from the definition value of the cave-type reservoir. If the difference between the two is 1, it represents a fracture-cavity reservoir, and if the difference is 0, it represents the surrounding rock, thus obtaining the fracture-cavity reservoir and its boundary.

[0010] Furthermore, in step 1, the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock is obtained, specifically: Well logging rock physics analysis is carried out on the wells drilled in the work area that encounter cavernous reservoirs to obtain the longitudinal wave impedance distribution map of the cavernous reservoirs and surrounding rocks, and then the boundary value of the longitudinal wave impedance of the cavernous reservoirs and surrounding rocks is determined.

[0011] Furthermore, the longitudinal wave impedance of the cave-type reservoir and the surrounding rock in step (1) is obtained from the same well that encounters the cave-type reservoir.

[0012] A fine reservoir prediction device for carbonate fracture-cavity reservoirs, comprising fracture-cavity and cave reservoir prediction modules and fracture-cavity reservoir prediction modules; The fracture-cavity and cave-type reservoir prediction module is used to make coherent enhancement attributes based on the original post-stack seismic data, use the reservoir top position interpreted by well logging to calibrate the coherent enhancement attribute body, use the coherent enhancement attribute value corresponding to the reservoir top position interpreted by well logging as a threshold, and make a judgment based on the size relationship between the coherent enhancement attribute value and the threshold to obtain the fracture-cavity reservoir and its boundary; It is also used to perform post-stack deterministic inversion on the original post-stack seismic data and obtain the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; the boundary value is used to carve the post-stack deterministic inversion results to obtain the cave-type reservoir and its boundary; The fracture-hole type reservoir prediction module is used to remove the cave type reservoir based on the predicted fracture-hole type reservoir, so as to obtain the fracture-hole type reservoir and its boundary range.

[0013] Further, the fracture-cavity and cave-type reservoir prediction module includes a fracture-cavity reservoir prediction unit and a cave-type reservoir prediction unit; The fracture-cavity reservoir prediction unit is used to make coherent enhancement attributes based on the original post-stack seismic data, use the reservoir top position interpreted by well logging to calibrate the coherent enhancement attribute body, use the coherent enhancement attribute value corresponding to the reservoir top position interpreted by well logging as a threshold, and make a judgment based on the size relationship between the coherent enhancement attribute value and the threshold to obtain the fracture-cavity reservoir and its boundary; The cave-type reservoir prediction unit is used to perform post-stack deterministic inversion on the original post-stack seismic data and obtain the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; the post-stack deterministic inversion result is carved using the boundary value to obtain the cave-type reservoir and its boundary; A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned fine reservoir prediction method for carbonate fracture-vuggy reservoirs when executing the computer program.

[0014] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to perform the steps of the above-mentioned fine reservoir prediction method for carbonate fracture-vuggy reservoirs.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The invention provides a fine reservoir prediction method for carbonate fracture-cavity reservoirs. Firstly, coherence enhancement attributes are performed based on original post-stack seismic data, and the coherence enhancement attribute value is calibrated by using the reservoir top position interpreted by logging to determine the threshold, and the coherence enhancement attribute value and the threshold are compared to obtain the fracture-cavity reservoir and its boundary range; then, post-stack deterministic inversion is performed based on the original post-stack seismic data, and the longitudinal wave impedance boundary value between the cave-type reservoir and the surrounding rock is determined by using the wells that encounter the cave-type reservoir, and the post-stack deterministic inversion result is carved by using the boundary value to obtain the cave-type reservoir and its boundary range; since it is difficult to accurately distinguish the cave-type reservoir from the fracture-cavity reservoir by the longitudinal wave impedance on the well, the fracture-cavity reservoir is difficult to be directly distinguished by inversion, and the fracture-cavity reservoir can be roughly divided into the cave-type reservoir and the fracture-cavity reservoir, so the predicted fracture-cavity reservoir is used to remove the cave-type reservoir, that is, the fracture-cavity reservoir and its boundary range are obtained, and further accurate prediction of the fracture-cavity reservoir is achieved. The present invention realizes a more accurate prediction of fracture-hole type reservoirs among the subdivided types of fracture-hole type reservoirs. Compared with the traditional method of directly predicting the boundaries of fracture-hole type reservoirs through seismic inversion combined with logging rock physics analysis, this method can combine seismic attributes and post-stack deterministic inversion to indirectly obtain the distribution range of fracture-hole type reservoirs, thereby realizing a more accurate prediction of fracture-hole type reservoirs.

[0016] The present invention provides a fine reservoir prediction device for carbonate fracture-vuggy reservoirs, comprising a specific module for completing the above working method.

[0017] The present invention provides a computer device and a storage medium for a fine reservoir prediction method for carbonate fracture-vuggy reservoirs, which are used to implement the specific steps of the above working method. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the present invention; Figure 2 This is the original seismic profile of the well; Figure 3The coherent enhancement attribute map after the reservoir top is calibrated for the original post-stack seismic data section of the well; Figure 4 It is a diagram showing the fracture-cavity reservoir and its boundary range; Figure 5 This is the longitudinal wave impedance distribution diagram of the cave-type reservoir and surrounding rock above the well; Figure 6 This is the P-wave impedance result diagram obtained by deterministic inversion based on the original seismic data; Figure 7 This is a map of cave-type reservoirs and their distribution range carved based on deterministic inversion results; Figure 8 The final fracture-pore type reservoir and its distribution range map; Fig. 9 This is a fracture-cavity reservoir map obtained by combining seismic inversion results with logging rock physics analysis. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] In order to improve the reservoir prediction accuracy of fracture-hole type reservoirs in the subdivision type of fracture-hole type reservoirs, the present invention predicts fracture-hole type reservoirs using seismic attributes based on original post-stack seismic data, and predicts cave type reservoirs using post-stack deterministic inversion. The predicted fracture-hole type reservoirs are used to remove the cave type reservoirs to obtain fracture-hole type reservoirs and their distribution ranges, thereby achieving further prediction of fracture-hole type reservoirs in the subdivision type of fracture-hole type reservoirs. The present invention plays an important role in correctly understanding the subdivision types of fracture-hole type reservoirs and their distribution ranges.

[0022] The present invention is further described in detail below in conjunction with the accompanying drawings: See also Figure 1 , Figure 1 The flowchart of the present invention is a fine reservoir prediction method for carbonate fracture-cavity reservoirs, comprising the following steps: Step 1: Make coherent enhancement attributes based on the original post-stack seismic data; Step 2: calibrate the coherence enhancement attribute value using the reservoir top interpreted by well logging, and use the coherence enhancement attribute value corresponding to the reservoir top position interpreted by well logging as the threshold; Step 3: define the coherence enhancement attribute value greater than the threshold as 0, representing the surrounding rock; define all the coherence enhancement attribute values ​​less than or equal to the threshold as 1, representing the fracture-cavity reservoir, and then obtain the fracture-cavity reservoir and its boundary range; Step 4: Select wells that encounter cavernous reservoirs in the work area and conduct logging rock physics analysis on them to determine the boundary value of the longitudinal wave impedance of the cavernous reservoirs and the surrounding rocks; Step 5: Perform post-stack deterministic inversion based on the original post-stack seismic data; Step 6: Use the cutoff value to carve the post-stack deterministic inversion results. The deterministic inversion result value greater than the cutoff value is defined as 0, representing the surrounding rock, and the value less than or equal to the cutoff value is defined as 1, representing the cave-type reservoir, thereby obtaining the cave-type reservoir and its boundary range; Step 7: Subtract the cave-type reservoir from the predicted fracture-cavity reservoir. A value of 1 represents a fracture-cavity reservoir, and a value of 0 represents the surrounding rock, thereby obtaining the fracture-cavity reservoir and its boundary range.

[0023] Through the above specific steps, a more accurate prediction of fracture-hole reservoirs in the subdivision of fracture-hole reservoirs is achieved. Compared with the traditional method of directly predicting the boundaries of fracture-hole reservoirs through seismic inversion combined with logging rock physics analysis, this method can combine seismic attributes and post-stack deterministic inversion methods to indirectly obtain the distribution range of fracture-hole reservoirs and achieve a more accurate prediction of fracture-hole reservoirs.

[0024] The present invention also provides a fine reservoir prediction device for carbonate fracture-cavity reservoirs, comprising a fracture-cavity and cave reservoir prediction module and a fracture-pore-cavity reservoir prediction module; the fracture-cavity and cave reservoir prediction module is used to perform coherence enhancement attributes based on original seismic data, use the reservoir top position interpreted by well logging to calibrate the coherence enhancement attribute body, use the coherence enhancement attribute value corresponding to the reservoir top position interpreted by logging as a threshold, and make a judgment based on the size relationship between the coherence enhancement attribute value and the threshold to obtain the fracture-cavity reservoir and its boundary; it is also used to perform post-stack deterministic inversion on the original post-stack seismic data, and obtain the boundary value of the longitudinal wave impedance of the cave reservoir and the surrounding rock, and use the boundary value to carve the post-stack deterministic inversion result to obtain the cave reservoir and its boundary; the fracture-pore-cavity reservoir prediction module is used to remove the cave reservoir on the basis of the predicted fracture-cavity reservoir, so as to obtain the fracture-pore-cavity reservoir and its boundary range.

[0025] In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the computer program is executed by the processor, a working method of a fine reservoir prediction device for carbonate fracture-cavity reservoirs is implemented.

[0026] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the following steps are implemented when the processor executes the computer program: Step 1, performing coherence enhancement attributes based on original post-stack seismic data, using the reservoir top position interpreted by well logging to calibrate the coherence enhancement attributes, using the coherence enhancement attribute value corresponding to the reservoir top position interpreted by logging as a threshold, and performing a judgment based on the magnitude relationship between the coherence enhancement attribute value and the threshold to obtain a predicted fracture-cavity reservoir and its boundary; performing post-stack deterministic inversion on the original post-stack seismic data, and obtaining a boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; and using the boundary value to carve the post-stack deterministic inversion results to obtain a predicted fracture-cavity reservoir and its boundary; Step 2, removing the cave-type reservoir on the basis of the predicted fracture-cavity reservoir, thereby obtaining a fracture-pore-cavity reservoir and its boundary. In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: Step 1, based on the original post-stack seismic data, coherence enhancement attributes are performed, and the coherence enhancement attributes are calibrated using the reservoir top position interpreted by well logging, and the coherence enhancement attribute value corresponding to the reservoir top position interpreted by logging is used as a threshold, and a judgment is made based on the relationship between the coherence enhancement attribute value and the threshold to obtain a predicted fracture-cavity reservoir and its boundary; the original post-stack seismic data is subjected to post-stack deterministic inversion, and the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock is obtained; the post-stack deterministic inversion result is carved using the boundary value to obtain a predicted fracture-cavity reservoir and its boundary; Step 2, based on the predicted fracture-cavity reservoir, the cave-type reservoir is removed to obtain a fracture-pore-cavity reservoir and its boundary.

[0027] Example See also Figure 2 , Figure 2 is the original seismic profile of the well; See also Figure 3 , Figure 3 This is the coherence enhancement attribute map after calibration of the original seismic profile superimposed with the well logging interpretation reservoir top. First, the coherence enhancement attribute is made based on the original seismic data, and the coherence enhancement attribute is calibrated according to the well logging interpretation reservoir top to determine the threshold of the coherence enhancement attribute, that is, the coherence enhancement attribute value corresponding to the logging interpretation reservoir top position is set as the threshold. For this work area, the threshold is 0.5. Coherence enhancement attribute values ​​greater than the threshold are not displayed, and those less than or equal to the threshold are displayed. The displayed coherence enhancement attribute values ​​are as follows: Figure 2 This is shown as the superimposed shaded portion on the original seismic section of the well.

[0028] See also Figure 4 , Figure 4 The fracture-cavity reservoir and its boundary range are displayed. All the coherent enhancement attribute values ​​less than or equal to the threshold are defined as 1, representing the fracture-cavity reservoir, and those greater than the threshold are defined as 0, representing the surrounding rock, so as to obtain the fracture-cavity reservoir and its boundary range map, such as Figure 4 shown.

[0029] See also Figure 5 , Figure 5 This is the distribution diagram of the longitudinal wave impedance of the cavernous reservoir and the surrounding rock on the well that hits the cavernous reservoir. It can be seen from the figure that the distribution range of the longitudinal wave impedance values ​​of the cavernous reservoir and the surrounding rock is different. Take 1.55e 7 kg / m 3 *m / s is the threshold value, greater than 1.55e 7 kg / m 3 *m / s is considered as surrounding rock, less than or equal to 1.55e 7 kg / m 3*m / s is considered as a cave reservoir.

[0030] Figure 6 Based on Figure 1 The deterministic inversion result volume obtained by deterministic inversion of the original seismic data.

[0031] Figure 7 This is a cave-type reservoir carved based on the deterministic inversion results. Figure 5 The threshold value obtained by Nakanoue's analysis is 1.55e 7 kg / m 3 *m / s is used to carve the deterministic inversion result volume, and the deterministic inversion result value is less than or equal to 1.55e 7 kg / m 3 *m / s is defined as 1, representing a cave reservoir, and is greater than 1.55e 7 kg / m 3 *m / s is defined as 0, representing the surrounding rock, such as Figure 7 shown.

[0032] Figure 8 The final fracture-pore reservoir and its distribution range map are shown in Figure 2. Figure 4 The fracture-cavity reservoir obtained by subtracting Figure 6 The cave-type reservoir obtained by deterministic inversion carving in , the value obtained is 1 represents the fracture-pore type reservoir, and the value is 0 represents the surrounding rock, and the final fracture-pore type reservoir and its distribution range are obtained, such as Figure 8 So far, fracture-cavity reservoirs are subdivided.

[0033] Fig. 9 The fracture-pore type reservoir is obtained by combining the seismic inversion results with the logging rock physics analysis. Since the fracture-pore type reservoir is relatively dense, the longitudinal wave impedance values ​​of the fracture-pore type reservoir and the surrounding rock have a high degree of coincidence. The fracture-pore type reservoir obtained by interpreting the conventional inversion results through logging rock physics analysis is not accurate. Some surrounding rocks are interpreted as fracture-pore type reservoirs, and a very small part of the surrounding rocks are interpreted as cave reservoirs, such as Fig. 9 As shown in the dashed box. By comparison, the boundary of the fracture-cavity reservoir in the present invention is obtained by calibrating the fracture-cavity reservoir based on the coherent enhancement attribute combined with the actual engineering anomalies such as emptying and leakage, and the fracture-cavity reservoir and its distribution range are obtained on this basis. The obtained fracture-cavity reservoir and its distribution range are more accurate and reliable. At the same time, the present invention also greatly reduces the probability of identifying the surrounding rock as a reservoir, and the surrounding rock background is also relatively clean, which is more in line with geological knowledge.

[0034] The present invention uses the reservoir top position interpreted by well logging to calibrate the coherent enhancement attribute body, that is, the coherent enhancement attribute value corresponding to the reservoir top position interpreted by logging is set as a threshold, and the coherent enhancement attribute value greater than the threshold is defined as 0, representing the surrounding rock, and all values ​​less than or equal to the threshold are defined as 1, representing the fracture-cavity reservoir, thereby obtaining the fracture-cavity reservoir and its boundary range. The boundary identification of the fracture-cavity reservoir is realized through this method flow. Since the actual logging data is fully referenced on the basis of the coherent enhancement attribute, the boundary identification result of the fracture-cavity reservoir is relatively reliable; The present invention selects wells drilled in a work area that encounter cave-type reservoirs for logging rock physics analysis, thereby determining the longitudinal wave impedance boundary value of the cave-type reservoir and the surrounding rock, and uses the boundary value to carve the post-stack deterministic inversion result. A deterministic inversion result value greater than the boundary value is defined as 0, representing the surrounding rock, and a deterministic inversion result value less than or equal to the boundary value is defined as 1, representing the cave-type reservoir, thereby obtaining the cave-type reservoir and its boundary range. The determination of the cave-type reservoir and its boundary is achieved through this method flow.

[0035] Carbonate fracture-cavity reservoirs can be roughly divided into cave-type and fracture-cavity reservoirs, so the fracture-cavity reservoir and its boundary range are obtained by subtracting the cave-type reservoir from the predicted fracture-cavity reservoir, with a value of 1 representing the fracture-cavity reservoir and a value of 0 representing the surrounding rock. This method indirectly obtains the fracture-cavity reservoir and its boundary range, and realizes the further accurate prediction of the fracture-cavity reservoir in the subdivision type of carbonate fracture-cavity reservoir, overcomes the problem of inaccurate characterization of fracture-cavity reservoir by conventional seismic inversion combined with logging rock physics analysis, and realizes the further accurate prediction of the fracture-cavity reservoir in the subdivision type of fracture-cavity reservoir.

[0036] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A fine reservoir prediction method for carbonate fracture-vuggy reservoirs, characterized in that: The following steps are involved: Step 1: Based on the original post-stack seismic data, coherence enhancement attributes are made, and the reservoir top position interpreted by well logging is used to calibrate the coherence enhancement attributes. The coherence enhancement attribute value corresponding to the reservoir top position interpreted by logging is used as a threshold, and a judgment is made based on the relationship between the coherence enhancement attribute value and the threshold to obtain the predicted fracture-cavity reservoir and its boundary; Performing post-stack deterministic inversion on the original post-stack seismic data and obtaining the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; carving the post-stack deterministic inversion results using the boundary value to obtain the predicted cave-type reservoir and its boundary; Step 2: Based on the predicted fracture-cavity reservoir, the cave-type reservoir is removed to obtain the fracture-cavity reservoir and its boundary range.

2. The fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to claim 1 is characterized in that: In step 1, the judgment is made according to the magnitude relationship between the coherence enhancement attribute value and the threshold, specifically: The coherence enhancement attribute value greater than the threshold is defined as 0, corresponding to the surrounding rock; all the coherence enhancement attribute values ​​less than or equal to the threshold are defined as 1, corresponding to the fracture-cavity reservoir, thereby obtaining the fracture-cavity reservoir and its boundary range.

3. The fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to claim 2 is characterized in that: In step 1, the demarcation value is used to carve the post-stack deterministic inversion result to obtain the predicted cave-type reservoir and its boundary range, specifically: The deterministic inversion result value greater than the cutoff value is defined as 0, representing the surrounding rock; The value of the deterministic inversion result less than or equal to the demarcation value is defined as 1, representing a cave-type reservoir, thereby obtaining a cave-type reservoir and its boundary range.

4. The fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to claim 3 is characterized in that: Step 2 is as follows: The definition value of the predicted fracture-cavity reservoir is subtracted from the definition value of the cave-type reservoir. If the difference between the two is 1, it represents a fracture-cavity reservoir, and if the difference is 0, it represents the surrounding rock, thus obtaining the fracture-cavity reservoir and its boundary.

5. The fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to any one of claims 1 to 4, characterized in that: In step 1, the boundary value of the longitudinal wave impedance of the cave reservoir and the surrounding rock is obtained, specifically: Well logging rock physics analysis is carried out on the wells drilled in the work area that encounter cavernous reservoirs to obtain the longitudinal wave impedance distribution map of the cavernous reservoirs and surrounding rocks, and then the boundary value of the longitudinal wave impedance of the cavernous reservoirs and surrounding rocks is determined.

6. The fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to any one of claims 1 to 4, characterized in that: The longitudinal wave impedance of the cave-type reservoir and the surrounding rock in step (1) is obtained from the same well in which the cave-type reservoir is drilled.

7. A fine reservoir prediction device for carbonate fracture-cavity reservoirs, characterized in that: Including fracture-cavity and cave-type reservoir prediction modules and fracture-cavity reservoir prediction modules; The fracture-cavity and cave-type reservoir prediction module is used to make coherent enhancement attributes based on the original post-stack seismic data, use the reservoir top position interpreted by well logging to calibrate the coherent enhancement attribute body, use the coherent enhancement attribute value corresponding to the reservoir top position interpreted by well logging as a threshold, and make a judgment based on the size relationship between the coherent enhancement attribute value and the threshold to obtain the fracture-cavity reservoir and its boundary; It is also used to perform post-stack deterministic inversion on the original post-stack seismic data and obtain the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; the boundary value is used to carve the post-stack deterministic inversion results to obtain the cave-type reservoir and its boundary; The fracture-hole type reservoir prediction module is used to remove the cave type reservoir based on the predicted fracture-hole type reservoir, so as to obtain the fracture-hole type reservoir and its boundary range.

8. The fine reservoir prediction device for carbonate fracture-vuggy reservoirs according to claim 7, characterized in that: The fracture-cavity and cave-type reservoir prediction module includes a fracture-cavity reservoir prediction unit and a cave-type reservoir prediction unit; The fracture-cavity reservoir prediction unit is used to make coherent enhancement attributes based on the original post-stack seismic data, use the reservoir top position interpreted by well logging to calibrate the coherent enhancement attribute body, use the coherent enhancement attribute value corresponding to the reservoir top position interpreted by well logging as a threshold, and make a judgment based on the size relationship between the coherent enhancement attribute value and the threshold to obtain the fracture-cavity reservoir and its boundary; The cave-type reservoir prediction unit is used to perform post-stack deterministic inversion on the original post-stack seismic data and obtain the boundary value of the longitudinal wave impedance of the cave-type reservoir and the surrounding rock; the post-stack deterministic inversion result is carved using the boundary value to obtain the cave-type reservoir and its boundary.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the fine reservoir prediction method for carbonate fracture-vuggy reservoirs according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the fine reservoir prediction method for carbonate fracture-vuggy reservoirs described in any one of claims 1 to 6 are implemented.

Images