Deep compact dessert reservoir prediction method
Through a systematic deep dense dessert reservoir prediction method, combined with seismic data and well logging data, phased seismic attribute quantification and OVT domain angle seismic attribute fusion, combined with quantitative version method-multiparameter-pre-post-overlap inversion method, the multi-solvency and low accuracy of deep dense dessert reservoir prediction is solved, and high-precision dessert reservoir prediction is achieved.
Patent Information
- Application Number
- CN202411664163.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2025-02-28
AI Technical Summary
The prior art is difficult to accurately identify and predict deep dense dessert reservoirs, especially under thin reservoirs and complex geological conditions, resulting in low prediction accuracy and strong multi-solvency.
A deep dense dessert reservoir prediction method is adopted, which includes synthesizing and recording calibration based on seismic data and well logging data, establishing the correspondence between reservoir and seismic reflection through fine calibration, and using threshold method to track sections to determine the favorable phase bands in the reservoir. Then, in the favorable development zone of the reservoir phase belt, the OVT domain angle seismic attribute fusion based on phased seismic attribute quantification is carried out to depict the main river sand body boundary and the favorable reservoir distribution area. Subsequently, the electrical identification criteria for the reservoir are determined to identify the favorable area dessert reservoir and elastic parameters that are sensitive to the reservoir's physical properties. Finally, the distribution range of dessert reservoirs in unknown underground space is reversed through the quantitative method-multi-parameter-pre-post-post-inversion method.
This method overcomes the problem of strong multi-solvability prediction of conventional single-use post-stack seismic data analysis methods, and better characterizes the unique seismic response characteristics of deep dense dessert reservoirs, realizes high-precision prediction of deep thin reservoirs, and improves exploration accuracy and reliability.
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Figure CN119535587A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of oil and gas exploration, and in particular, relates to a method for predicting deep and dense sweet spot reservoirs. Background Art
[0002] As the production of shallow main production areas of onshore oil fields gradually decreases, medium-deep tight reservoirs are becoming more and more important in future reserve replacement and production contribution, and are of great significance for increasing reserves and production of oil fields. However, due to the low physical properties of tight reservoirs, the difference in geophysical response between sweet spot reservoirs and non-sweet spot reservoirs is small, and it is difficult to identify them using seismic data. The geophysical community has currently studied a variety of "sweet spot" prediction methods for different types of oil and gas reservoirs. The existing publicly published articles mainly focus on the seismic response mechanism of thick reservoir "sweet spots", pre-stack and post-stack seismic multi-attribute fusion "sweet spot" prediction and other related research work. Through investigation, it is found that the seismic prediction method for sweet spots in thick reservoirs has been seen in some literature and research results. It can be divided into two seismic evaluation methods: one is to carry out reservoir porosity prediction. For reservoir porosity prediction, it is generally necessary to establish a velocity-porosity relationship. This relationship, whether linear or nonlinear, varies in time and space with the changes in longitudinal compaction and lateral deposition. Therefore, it is difficult to establish an accurate rock physics model of dense clastic reservoirs using existing technologies, resulting in low prediction accuracy when converting seismic parameters into porosity; the second "sweet spot" prediction method explores a certain favorable seismic attribute parameter and directly associates the prediction result of the attribute parameter with the "sweet spot" reservoir prediction. There are examples of "sweet spot" prediction of parameters such as seismic velocity anomaly and Poisson damping factor. However, the disadvantage is that a single attribute has a strong multi-solution disadvantage, making it difficult to conduct a comprehensive evaluation of the sweet spot reservoir.
[0003] In recent years, deep tight reservoirs have begun to be the focus of exploration. The existing conventional reservoir prediction technology is mainly aimed at medium-shallow sand layers. At present, the seismic prediction research work of deep reservoir "sweet spots" is mainly aimed at large sets of thick and gas-bearing reservoir types. A joint prediction method based on a specific seismic attribute parameter or multiple geophysical parameters has been formed, and the technical method has gradually matured. However, the above methods have strong multi-solutions for the prediction of thin reservoir sweet spots, and cannot identify thin reservoir sweet spots. On the other hand, deep tight reservoirs are buried deep, mostly below 3,500 meters, with complex and changeable geological characteristics, and lack of sweet spot distribution rules. At the same time, the conventional processing of seismic data in this range has a narrow frequency band and low main frequency. The main frequency is mostly below 25hz, there are few logging data and the location distribution is uneven, making it difficult to conduct a comprehensive evaluation of the sweet spot reservoir. The current prediction methods mainly include seismic inversion technology, seismic attribute analysis, etc., but for medium-deep tight oil fields, it is difficult to manually identify the difference in seismic response between sweet spots and non-sweet spots, and traditional reservoir prediction methods have many human factors, low accuracy, and strong multi-solutions.
[0004] Tight oil reservoirs are rich in resources, but most reservoirs are low-grade oil reservoirs with tight permeability and low porosity. Although the P-wave velocity and P-wave impedance of sandstone in conventional oil reservoirs show the characteristics of "mudstone < oil and gas sandstone < water-bearing sandstone < tight sandstone", due to the poor physical properties of thin reservoirs in tight oil reservoirs, the seismic response characteristics of sweet spots are fuzzy, the overall difference is not large, and seismic prediction is difficult. Conventional attribute methods cannot characterize the development characteristics of the reservoir "sweet spots". Therefore, how to correctly describe and predict the distribution of sweet spots in thin reservoirs is the key to solving the optimization and adjustment of well locations in thin reservoirs in tight oil reservoirs. Summary of the invention
[0005] The present application provides a method for predicting deep and tight sweet spot reservoirs. The method has a more systematic and comprehensive overall consideration, strong operability, and more reliable comparison results, providing a basis for oil field well site deployment.
[0006] The embodiment of the present application provides a method for predicting deep tight sweet spot reservoirs, including: S1, performing synthetic record calibration based on seismic data and well logging data; S2, establishing a correspondence between the reservoir and seismic reflection through fine reservoir calibration, performing profile phase tracking using a threshold method, and determining a favorable phase belt where the reservoir exists; S3, performing OVT domain angle-based seismic attribute fusion based on phase-controlled seismic attribute quantification in favorable development areas of the reservoir phase belt to characterize the main channel sand body boundary and favorable reservoir distribution area; S4, determining the electrical identification standard of the reservoir, identifying the sweet spot reservoir in the favorable area and the elastic parameters sensitive to the reservoir physical properties; S5, inferring the distribution range of the sweet spot reservoir in the unknown underground space through the quantitative version method-multi-parameter-pre-stack and post-stack inversion method based on the elastic parameters.
[0007] Among them, step S1 includes: using the acoustic wave and density logging curve to calculate the reflection coefficient, convolving the reflection coefficient with the extracted seismic wavelet to obtain the initial synthetic record, and then matching and adjusting with the wellside seismic trace to obtain the final synthetic record. Then, the synthetic seismic record of the target layer is used for reservoir-level well seismic calibration.
[0008] Among them, in step S2, determining the favorable phase belt of the reservoir includes: using well data comparison for the main reservoir to clarify the lower limit of the effective reservoir amplitude, using the amplitude threshold method to carry out lateral tracking of the sand body on the profile, and determining the favorable phase belt.
[0009] Among them, determining the favorable phase belt for the existence of the reservoir in step S2 also includes: using the amplitude strength change characteristics of the seismic reflection axis corresponding to the main sand layer group on the well-linked seismic profile to compare with the effective reservoir interpreted by well logging, determining the amplitude threshold of the sweet spot reservoir, taking it as the lower limit, adjusting the color of the variable density seismic profile, the well without sweet spot reservoir corresponds to the cold blue tone, the seismic reflection axis on the well with the sweet spot reservoir corresponds to the warm yellow-red tone, and the reservoir range is plane-depicted for the warm-toned seismic reflection phase axis on the variable density seismic profile to obtain a favorable phase belt for the development of favorable reservoirs.
[0010] Among them, in step S3, the seismic attributes are preferably sensitive seismic attributes, and the types of sensitive seismic attributes are determined, including seismic attributes that are sensitive to reservoir lithology, physical properties and oil and gas properties.
[0011] Wherein, step S4 includes determining the relationship between the reservoir lithology, physical properties, electrical properties and oil content of the reservoir.
[0012] Among them, step S4 also includes, through the analysis of logging data, identifying the effective reservoirs on the wells that have been tested or cored, and then conducting rock physical analysis of the effective reservoirs, determining the electrical identification standards of the effective reservoirs, identifying the effective reservoirs that have been drilled, and establishing an effective reservoir interpretation plate. The interpretation plate is used to analyze the electrical difference values between the sweet spot reservoir and the dry layer, and the value range of the sweet spot reservoir parameter SP and the range of the longitudinal wave impedance value are clarified.
[0013] The sensitive elastic parameters in step S4 also include shear wave velocity and longitudinal wave velocity.
[0014] The deep and dense sweet spot reservoir prediction method of the present application embodiment has the following beneficial effects:
[0015] This application overcomes the difficulty of predicting multiple solutions using conventional single post-stack seismic data analysis methods, better characterizes the unique seismic response characteristics of deep and dense sweet spot reservoirs, and has a high coincidence rate verified by actual drilling, achieving high-precision prediction of deep thin reservoir sweet spots, and pointing out the direction for the exploration and development of deep and dense thin reservoir sweet spots. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1a This is a flowchart of a method for predicting a deep and dense sweet spot reservoir according to an embodiment of the present application;
[0017] Figure 1b This is a schematic diagram of the deep and dense sweet spot reservoir prediction method of the present application embodiment. Figure 2 ;
[0018] Figure 2 This is the fine calibration of the reservoir of the Zhen 86 well in the embodiment of this application;
[0019] Figure 3This is a comparison diagram of the geological sand bodies of the well E2d11 of Zhen84-Zhen59-Zhen86-Yong38-1-Yong38 in the embodiment of the present application;
[0020] Figure 4 It is a variable density section after adjusting the color based on the amplitude value range of the E2d11 well-joint seismic of Zhen84-Zhen59-Zhen86-Yong38-1-Yong38 wells in the embodiment of the present application;
[0021] Figure 5 This is the OVT division and imaging diagram in the cross arrangement of seismic data in Yong'an area in the embodiment of the present application;
[0022] Figure 6 Comparison of seismic attributes of different azimuth volumes in the OVT domain in the embodiment of this application;
[0023] Figure 7 This is the fusion map of the plane attributes and the approximate paleo-geomorphology of the OVT domain in the Yong'an area in the embodiment of the present application;
[0024] Figure 8 It is a longitudinal wave impedance histogram in the embodiment of the present application;
[0025] Fig. 9 This is a diagram showing the intersection of the acoustic wave and the SP in the embodiment of the present application;
[0026] Fig.10 This is the intersection diagram of elastic parameters of Well E2d11 of Yong 14-1 in the embodiment of the present application;
[0027] Fig.11 The multi-parameter constraint method in the embodiment of the present application is used for post-stack inversion to predict the sweet spot reservoir profile;
[0028] Fig.12 The cross-well random pre-stack-post-stack joint seismic inversion predicts the sweet spot reservoir profile in the embodiment of the present application;
[0029] Fig.13 This is a superposition diagram of the T25 reflection layer structure in Yong'an area and the E2d11 predicted sweet spot sandstone thickness in the embodiment of this application. DETAILED DESCRIPTION
[0030] The present application is further described below in conjunction with the accompanying drawings and embodiments.
[0031] In the following introduction, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present invention, and different embodiments can be replaced or combined, so this application can also be considered to include all possible combinations of the same and / or different embodiments recorded. Therefore, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more of all other possible combinations of features A, B, C, and D, even though the embodiment may not be clearly recorded in the following text.
[0032] Embodiment 1
[0033] The present invention is an improved method proposed for the prediction of deep tight sweet spot reservoirs. It carries out fine characterization of seismic phases based on the seismic attribute threshold method, combines the OVT domain seismic attribute fusion, and uses the quantitative version method-multi-parameter-pre-stack and post-stack joint step-by-step progressive method. Different seismic methods are used to predict the main parameters and characteristics affecting the reservoir grade, such as reservoir sedimentary phase belts and reservoir physical properties, and the sweet spot reservoirs are predicted by controlling the multiple prediction results step by step or superimposing them to obtain the intersection method.
[0034] As shown in Figure 1, the present application provides a deep tight sweet spot reservoir prediction method including: S1, synthetic record calibration based on seismic data and logging data; S2, establishing the correspondence between reservoir and seismic reflection through fine reservoir calibration, using the threshold method to carry out profile phase tracking, and determining the favorable phase belt where the reservoir exists; S3, in the favorable development area of the reservoir phase belt, OVT domain angle-based seismic attribute fusion based on phase-controlled seismic attribute quantification is carried out to characterize the main channel sand body boundary and the favorable reservoir distribution area; S4, determining the electrical identification standard of the reservoir, identifying the sweet spot reservoir in the favorable area and the elastic parameters sensitive to the reservoir physical properties; S5, according to the elastic parameters, the quantitative version method-multi-parameter-pre-stack and post-stack inversion method is used to infer the distribution range of the sweet spot reservoir in the unknown underground space.
[0035] The deep tight sweet spot reservoir prediction method provided in this application has a more systematic and comprehensive overall consideration, strong operability, and more reliable comparison results, providing a basis for oil field well site deployment.
[0036] Embodiment 2
[0037] In this application, the first step is to interpret the structure of the seismic data reflection standard layer. On the basis of the layer calibration, the seismic reflection standard layer tracking is carried out to understand the underground strata, especially the stratum structure morphology and fault distribution of the target layer. In the framework of large structural interpretation, the reservoir is finely calibrated. On this basis, combined with the forward simulation results, the influence of the sand body development degree on the seismic reflection characteristics is analyzed.
[0038] In order to determine the plane boundary of the sand body, the amplitude threshold method is used to carry out lateral tracking of the sand body on the profile and the frequency profile respectively. In addition, the sand body boundary is finely characterized by combining seismic phase characterization, phase-controlled attribute analysis and OVT domain angle attribute fusion. In order to address the difficulties in quantitative prediction of sweet spot reservoirs, the phase control-multi-parameter-pre-stack and post-stack combined step-by-step progressive method is used to carry out quantitative prediction of sweet spot reservoirs.
[0039] The deep tight sweet spot reservoir prediction method of this application specifically includes:
[0040] Step 1: Based on the fine calibration of the reservoir, the corresponding relationship between the reservoir and the seismic reflection is clarified. For the main reservoir, the lower limit of the effective reservoir amplitude is determined by comparing the well data. The amplitude threshold method is used to conduct lateral tracking of the sand body on the profile to determine the favorable phase belt.
[0041] In this step, synthetic record calibration is carried out on the basis of comprehensive research on seismic, logging and core data. The reflection coefficient is calculated using the acoustic wave and density logging curve, and the reflection coefficient is convolved with the extracted seismic wavelet to obtain the initial synthetic record, which is then matched and adjusted with the seismic trace beside the well to obtain the final synthetic record. Then, the synthetic seismic record of the target layer is calibrated at the reservoir level. The corresponding relationship between the main oil-producing sand layer group and the seismic reflection phase axis is clarified, and the amplitude strength change characteristics of the seismic reflection axis corresponding to the main sand layer group on the well-joint seismic profile are compared with the effective reservoir interpreted by the logging, and the amplitude threshold of the sweet spot reservoir is determined, which is used as the lower limit to adjust the color of the variable density seismic profile. The wells without sweet spot reservoirs correspond to blue cold tones, and the seismic reflection axes on the wells with sweet spot reservoirs correspond to yellow-red warm tones. The reservoir range plane is depicted for the warm-toned seismic reflection phase axis on the variable density seismic profile to obtain a favorable phase belt for favorable reservoir development.
[0042] Step 2: Based on the phase-controlled seismic attribute quantitative analysis technology, sensitive seismic attributes are selected, and seismic attribute fusion is carried out using the OVT domain angle-divided seismic data. The main channel sand body boundary and favorable reservoir distribution area within the favorable sedimentary facies belt are characterized in combination with paleogeomorphic characteristics.
[0043] In this step, within the favorable phase belt obtained in step 1, the main distribution direction of the reservoir is determined in combination with the sedimentary microfacies characteristics, and the direction perpendicular to / consistent with the distribution characteristics is selected to carry out angle division of the OVT domain seismic data. The various seismic attributes of the nearby seismic traces are extracted using the OVT domain data after angle division, and compared with the logging results to determine the types of sensitive seismic attributes, including seismic attributes that are sensitive to the lithology, physical properties, and oil and gas content of the reservoir. The sensitive seismic attributes are extracted along the target layer to obtain a plane map, and attribute fusion is carried out using the OVT domain angle data. The attribute fusion results are superimposed on the paleo-geomorphological map, and the color boundaries are further adjusted according to the paleo-geomorphological characteristics to obtain the main channel sand body boundary and the favorable area where the thick reservoir may be distributed.
[0044] Step 3: Determine the relationship between the reservoir lithology, physical properties, electrical properties and oil content of the reservoir, as well as the electrical property identification standard of the reservoir, and identify the effective reservoir in the study area according to the electrical property identification standard of the reservoir. Quantitative prediction of sweet spot reservoirs is carried out using the scale method-multiple parameters-pre-stack and post-stack combined step-by-step progressive method.
[0045] In this step, in the favorable area where the possible thick sweet spot reservoir is predicted to be distributed in step 2, the effective reservoir on the well that has been tested or cored is identified through the analysis of logging data, and then the rock physical analysis of the effective reservoir is carried out, the electrical identification standard of the effective reservoir is determined, the effective reservoir that has been drilled is identified, and the interpretation volume plate of the effective reservoir is established. The electrical difference between the sweet spot reservoir and the dry layer is analyzed by using the interpretation volume plate, and the value range of the sweet spot reservoir parameter SP and the range of the longitudinal wave impedance value are clarified; then the multi-parameter constraint method is used to carry out post-stack prediction, and the waveform indication inversion method suitable for the area is preferably used for inversion to obtain the original wave impedance inversion data body. Secondly, the natural potential inversion is carried out to obtain the lithology inversion data body, and this set of data is mutually constrained with the wave impedance data body to obtain the post-stack sweet spot reservoir inversion result; finally, the pre-stack simultaneous inversion is carried out, and the quality of the pre-stack inversion is mainly analyzed from the following two aspects: first, whether the result of the pre-stack inversion is consistent with the well; second, whether the inversion result is consistent with the result of the rock physical analysis, that is, whether the abnormal part in the inversion result corresponds to a specific lithology and reservoir. According to the results of rock physics research, it is believed that the elastic parameter sensitive to lithology is the shear wave velocity, and the elastic parameter sensitive to reservoir physical properties is the longitudinal wave velocity. Therefore, the elastic inversion before stacking in this area is mainly based on these two sensitive elastic parameters. The longitudinal and shear wave velocity ratio inversion data and the post-stack sweet spot reservoir inversion results are mutually constrained. The overlap range of the three is taken as the distribution range of the sweet spot reservoir.
[0046] The present invention firstly uses the amplitude threshold method based on reservoir fine calibration to characterize the boundary of the favorable phase belt of the reservoir, thereby delineating the distribution range of the favorable sedimentary phase belt of the target layer; then adopts quantitative analysis based on phase-controlled seismic attributes, combined with OVT domain angle attribute fusion, to predict the distribution range of the main channel sand body within the distribution range of the favorable sedimentary phase belt; finally, the sweet spot reservoir distribution of the main channel sand body of the target layer is predicted by the scale method-multiple parameters-pre-stack and post-stack combined step-by-step progressive method.
[0047] The deep tight sweet spot reservoir prediction method provided in the present application is a new idea of step-by-step prediction through phase belt-river channel-sweet spot reservoir, which applies OVT domain angle, pre-stack and post-stack seismic data, and reduces the multi-solution caused by directly using post-stack three-dimensional seismic data to predict sweet spot reservoirs in the prior art, thereby improving the accuracy of deep tight reservoir prediction.
[0048] Embodiment 3
[0049] The present invention is further described below by taking XX depression in XX oilfield in XX basin in China as an example.
[0050] like Figure 1a , 1b As shown, step 101 is to collect basic seismic data of the study area and well data in the work area and carry out data preprocessing.
[0051] Step 102, through the reservoir fine calibration, establish the corresponding relationship between the reservoir and the seismic reflection, such as Figure 2 As shown in Figure 1, the overall reservoir of Well Zhen 86 is not well developed, and the correspondence between the reservoir and the well is good. The seven sets of sand layers correspond to the reflection characteristics of the seven seismic phase axes on the seismic data. Taking E2d11 as an example, sand body identification is carried out. Figure 4 As shown in the figure, the well-joint profile shows that the sand body in Well Yong 38 is relatively developed, which decreases significantly to the south to Well Zhen 59, and the sand body in Well Zhen 84 disappears. Taking Well Zhen 84 as the color lower limit, the color of the variable density profile is adjusted, where cold colors indicate undeveloped sandstone and warm colors indicate developed sandstone. The threshold method is used to carry out profile phase tracking to clarify the favorable phase belt of the reservoir. Figure 5 As shown in the figure, the seismic event axis of Yong 38 well shows strong energy, which gradually weakens towards the south. The Zhen 86 well shows medium amplitude characteristics, and the Zhen 59 becomes a weak amplitude characteristic and disappears towards the south. The characteristics of this wave group in Zhen 84 well have disappeared, which is consistent with the actual drilling situation on the well. Based on this, the plane range of the reservoir can be preliminarily characterized.
[0052] Step 103, combining the initially described reservoir plane range, such as Figure 5 As shown in Figure 1, the seismic data is divided into four azimuth data, and four seismic data volumes with different azimuths and shot spacings are obtained. Figure 6 , Figure 7 As shown in the figure, seismic attributes are used to carry out reservoir prediction analysis. The seismic sample point values of the corresponding layers are extracted within a certain time window in four seismic data volumes with different azimuths and offsets. Under the phase control constraint, the angle is optimized for attribute fusion, and the fused attribute map is superimposed with the paleo-geomorphology to depict the boundary of the main channel sand body.
[0053] Step 104, determine the electrical property identification standard of the reservoir, identify the sweet spot reservoir in the favorable area and the elastic parameters sensitive to the reservoir physical properties. Figure 8 , Fig. 9 The analysis shows that the range of the sweet spot reservoir parameter SP is 10mv~40mv, the P-wave impedance of the sweet spot sandstone is between 7000~10000, and the P-wave impedance of the tight sandstone is above 10000; using the logging data of known wells and rock physics analysis, the elastic parameters that reflect the lithology and fluid sensitivity of the target layer are selected for intersection analysis. Fig.10As shown in the figure, the sweet spot reservoir is within the blue circle. The rock physical characteristics are analyzed. Since the P-wave and S-wave velocities are affected by physical properties and oil content to different degrees, the two show differences in the P-wave and S-wave velocity intersection diagram. The better the physical properties, the farther it deviates from the mudstone baseline. The sensitive elastic parameter is the P-wave and S-wave velocity ratio.
[0054] Step 105, based on the elastic parameters, the distribution range of the sweet spot reservoir in the unknown underground space is inferred by the quantitative version method, multi-parameter, pre-stack and post-stack inversion method. Fig.11 As shown in the figure, the multi-parameter constraint method is used to carry out post-stack prediction based on the sweet spot reservoir range data determined by the quantitative version, and the wave impedance inversion results are integrated with the SP simulation results to obtain the post-stack sweet spot reservoir inversion results; Fig.12 As shown in the figure, the pre-stack simultaneous inversion was carried out using pre-stack data, and the P-S wave velocity ratio inversion data and the post-stack sweet spot reservoir inversion results were selected to constrain each other, and the hydrocarbon detection profile was obtained. The overall relationship with the well was good. The oil test conclusions of Yong 102 oblique, Yong 55, Yong 38-1, and Yong 38 wells were all oil layers, and there were obvious anomalies in the detection profile. Yong 38-2 was a dry layer, without a sweet spot reservoir, and there was no anomaly in the detection result. Fig.13 As shown, the sweet spot reservoir distribution range (warm color range) is finally predicted.
[0055] From the perspective of exploration results, the sweet spot reservoir development area identified by the deep tight sweet spot reservoir prediction technology of the present invention is consistent with the actual drilling results. Practice has proved that the technology is feasible for predicting deep tight sweet spot reservoirs and is worth learning from and applying in similar areas.
[0056] The prediction method for deep tight sweet spot reservoirs provided in the present application is based on basic seismic data and fully exploits the information of original seismic data. When the reservoir is a tight reservoir, on the basis of phase control, the sweet spot reservoir logging data analysis can be combined with reservoir parameter prediction. By integrating and converging independent prediction results of multiple methods, it is beneficial to narrow the sweet spot area, accurately predict the distribution of the sweet spot reservoir, improve the reliability of the prediction results and the success rate of drilling, and has been confirmed in the proven reserves in the actual work area.
[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A method for predicting deep and tight sweet spot reservoirs, characterized in that: include: S1, carry out record calibration based on seismic data and well logging data; S2, through fine reservoir calibration, establish the corresponding relationship between reservoir and seismic reflection, use the threshold method to carry out profile phase tracking, and determine the favorable phase belt of the reservoir; S3, in the favorable development area of reservoir facies, carry out OVT domain angle-based seismic attribute fusion based on phase-controlled seismic attribute quantification to characterize the main channel sand body boundary and favorable reservoir distribution area; S4, determine the electrical identification criteria of the reservoir, identify the sweet spot reservoir in the favorable area and the elastic parameters that are sensitive to the reservoir physical properties; S5, based on elastic parameters, the distribution range of sweet spot reservoirs in unknown underground space is inferred through the quantitative version method, multi-parameter, pre-stack and post-stack inversion method.
2. The deep and dense sweet spot reservoir prediction method according to claim 1 is characterized in that: Step S1 includes: using the acoustic wave and density logging curve to calculate the reflection coefficient, convolving the reflection coefficient with the extracted seismic wavelet to obtain an initial synthetic record, and then matching and adjusting it with the seismic trace near the well to obtain the final synthetic record. Then, the synthetic seismic record of the target layer is calibrated at the reservoir level.
3. The deep and dense sweet spot reservoir prediction method according to claim 1 is characterized in that: In step S2, the favorable phase belt of the reservoir is clarified, including: using well data comparison for the main reservoir to clarify the lower limit of the effective reservoir amplitude, and using the amplitude threshold method to carry out lateral tracking of the sand body on the profile to determine the favorable phase belt.
4. The deep dense sweet spot reservoir prediction method according to any one of claims 1 to 3, characterized in that: In step S2, clarifying the favorable phase belt where the reservoir exists also includes: using the amplitude strength change characteristics of the seismic reflection axis corresponding to the main sand layer group on the well-linked seismic section to compare with the effective reservoir interpreted by well logging, determining the amplitude threshold of the sweet spot reservoir, taking it as the lower limit, adjusting the color of the variable density seismic section, the well without sweet spot reservoir corresponds to the cold blue tone, the seismic reflection axis on the well with the sweet spot reservoir corresponds to the warm yellow-red tone, and the reservoir range is plane-depicted for the warm-toned seismic reflection phase axis on the variable density seismic section to obtain the favorable phase belt for the development of favorable reservoirs.
5. The deep and dense sweet spot reservoir prediction method according to any one of claims 1 to 3, characterized in that: In step S3, the seismic attributes are preferably sensitive seismic attributes, and the types of sensitive seismic attributes are determined, including seismic attributes that are sensitive to reservoir lithology, physical properties, and oil and gas properties.
6. The deep and dense sweet spot reservoir prediction method according to any one of claims 1 to 3, characterized in that: Step S4 includes determining the relationship between the reservoir lithology, physical properties, electrical properties and oil content of the reservoir.
7. The method for predicting deep and dense sweet spot reservoirs according to any one of claims 1 to 3, characterized in that: Step S4 also includes: identifying effective reservoirs on wells that have been tested or cored through logging data analysis, and then conducting rock physical analysis of the effective reservoirs, determining electrical identification standards for effective reservoirs, identifying effective reservoirs that have been drilled, establishing an effective reservoir interpretation plate, using the interpretation plate to analyze the electrical difference between the sweet spot reservoir and the dry layer, and clarifying the value range of the sweet spot reservoir parameter SP and the range of the longitudinal wave impedance value.
8. The method for predicting deep and dense sweet spot reservoirs according to any one of claims 1 to 3, characterized in that: In step S4, the sensitive elastic parameters include: shear wave velocity and longitudinal wave velocity.