Method for identifying reservoir body structure of fractured-vuggy oil reservoir and application of method

Abstract

The invention provides a method for identifying a fractured-vuggy oil reservoir body structure and application thereof, and relates to the technical field of oil reservoir energy exploration. According to the method, static structure identification is carried out on the reservoir body structure of the target fracture-cavity type reservoir; carrying out dynamic parameter identification on the reservoir body structure of the target fracture-cavity type reservoir; and finally, based on static structure identification and dynamic parameter identification of the reservoir body structure of the target fracture-vug type oil reservoir, establishing a dynamic parameter reservoir body structure identification model, comprehensively analyzing different structural reservoir bodies of the fracture-vug type oil reservoir through multi-dimensional data, realizing semi-quantitative identification of the fracture-vug structure of the fracture-vug type oil reservoir, and improving the reliability of fracture-vug identification. The method can be widely applied to recognition of complex oil reservoir body structures.

Description

Technical Field

[0001] The invention belongs to the technical field of oil reservoir energy exploration, and in particular relates to a method for identifying the reservoir structure of a fracture-cavity oil reservoir and an application thereof. Background Art

[0002] Fracture-cavity oil reservoirs are a special type of oil reservoir, characterized by the presence of a large number of fractures and caves in the reservoir. This type of reservoir is particularly common in carbonate formations, because carbonate rocks are easily soluble and can form complex fracture and cave systems. The formation mechanism of fracture-cavity oil reservoirs is usually related to geological structure, karstification, diagenesis, etc. During tectonic movement, rocks break and deform to form fractures and caves. In addition, during the diagenesis process, due to changes in pressure and temperature, minerals in the rocks dissolve and reprecipitate, which can also form fractures and caves.

[0003] Fracture-cavity oil reservoirs are of great significance in oil exploration and development. Due to the presence of fractures and caves, the fluidity of oil and water in the reservoir is enhanced, which can improve the oil recovery rate. At the same time, fractures and caves can also provide favorable conditions for the accumulation and migration of oil and gas. However, fracture-cavity oil reservoirs also have some challenges. Due to the complexity and uncertainty of fractures and caves, it is difficult to predict and control the reservoir. In addition, during the development process, fractures and caves may be polluted or blocked, affecting the oil recovery effect. Therefore, targeted exploration and development technologies are needed based on the characteristics of fracture-cavity oil reservoirs.

[0004] Chinese invention patent 201710606989.4 discloses a method for controlling water and stabilizing oil in carbonate fracture-cave reservoirs. The method includes: finely identifying and characterizing the structure of the fracture-cave unit reservoir; evaluating the connectivity of the fracture-cave unit reservoir structure based on the results of the fine identification and characterization of the fracture-cave unit reservoir structure; characterizing the flow potential inside the fracture-cave unit based on the evaluation results of the connectivity of the fracture-cave unit reservoir structure; evaluating the reserve utilization of the fracture-cave unit based on the evaluation results of the connectivity of the fracture-cave unit reservoir structure and the flow potential characterization inside the fracture-cave unit; and reconstructing the flow potential balance of the fracture-cave unit based on the flow potential characterization and the reserve utilization evaluation results. This method can achieve balanced development of the fracture-cave unit economically and efficiently by adjusting the flow potential of the fracture-cave unit, effectively preventing or inhibiting the excessively rapid coning of bottom water, and will not passively lose the production capacity of the oil well.

[0005] Li Yong et al. (Li Yong, Deng Xiaojuan, Ning Chaozhong et al. "Secondary quantitative carving" technology for fracture-cavity carbonate reservoirs and its application [J]. Petroleum Exploration and Development, 2022, 49(04): 693-703.) Aiming at the problems of well-developed pores and caves in fracture-cavity carbonate reservoirs, strong heterogeneity, large uncertainty in the first carving results based on static seismic data, and difficulty in improving the quantitative carving accuracy of effective reservoirs, on the basis of first static carving, the "secondary quantitative carving" technology for fractures and caves was proposed by fully considering many key influencing factors in the carving process and combining static and dynamic data. This technology combines dynamic analysis and research methods such as well test analysis, production instability analysis, dynamic reserve analysis, and dynamic connectivity evaluation, and uses the reservoir knowledge of dynamic analysis as a statistical parameter to constrain seismic wave impedance inversion, improve the wave impedance and porosity relationship model, determine the fracture-cavity body morphology, calculate dynamic reserves, and then select a more accurate fracture-cavity model, and dynamically infer the oil-water interface based on the secondary carving results. This technology can greatly reduce the uncertainty of static one-time carving of fracture-cavity bodies, improve the accuracy of carving results, and has achieved good results in the development practice of fracture-cavity carbonate reservoirs in the Tarim Basin.

[0006] In fact, at present, facing the complex reservoir fracture-cavity structure, researchers still have a single understanding of the fracture-cavity structure of carbonate fracture-cavity reservoirs, so they use different prediction and research methods for different fracture-cavity structures, and there is no development law. Related research such as the distribution pattern of remaining oil cannot be further promoted. Therefore, it is particularly important to provide a method to identify the reservoir structure of complex fracture-cavity reservoirs. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention provides a method for identifying the reservoir structure of fracture-vuggy oil reservoirs and its application, and comprehensively analyzes reservoirs of different structures of fracture-vuggy oil reservoirs through multi-dimensional data, thereby providing a basis for clarifying the development rules of different fracture-vuggy structures and establishing the remaining oil distribution pattern.

[0008] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0009] First, the present invention provides a method for identifying the reservoir structure of a fracture-cavity oil reservoir, comprising the steps of:

[0010] S101: Static structural identification of the reservoir structure of the target fracture-cavity oil reservoir;

[0011] S1011: Identify the reservoir type of the target fracture-cavity body;

[0012] S1012: Identify the target fracture-cavity body and the fracture-cavity structure between the fracture-cavity bodies;

[0013] S102: Dynamic parameter identification of the reservoir structure of the target fracture-cavity oil reservoir;

[0014] S1021: Dynamically identify well point reservoir structure based on multiple data;

[0015] S1022: Dynamically identify the reservoir structure around the well based on multiple data;

[0016] S1023: Dynamically identify inter-well reservoir structure based on multiple data;

[0017] S103: Based on the static structure identification and dynamic parameter identification of the reservoir structure of the target fracture-vuggy oil reservoir, a dynamic parameter reservoir structure identification model is established.

[0018] Preferably, step S1011 specifically comprises: classifying the reservoir according to the shape of the well test curve; the classification is divided into V-shaped, double concave, late drop type, rising closed type, horizontal straight line type, and rising straight line (slope 1 / 2) type.

[0019] Preferably, step S1012 specifically includes: classifying the fracture-cavity structure by statistically analyzing the well logging and drilling data of the fracture-cavity oil reservoir and combining the fracture-cavity structure knowledge of the seismic sculpture; and identifying the fracture-cavity combination structure according to the quantitative situation of the tracer.

[0020] Further preferably, the fracture-cavity structures are classified into three categories: caves, holes and cracks; and further divided into six subcategories: filled caves, unfilled caves, dispersed holes, bedding holes, structural fractures and dissolution fractures.

[0021] Further preferably, the fracture-cavity combination structure is identified, and the fracture-cavity combination structure includes: a single fracture type between wells, a single pipeline type, a fracture series cave type between wells, a pipeline series cave type between wells, a pipeline parallel type between wells, and a pipeline parallel type between wells containing caves. Different fracture-cavity combination structures show different characteristics in the morphology of the tracer production curve.

[0022] Preferably, in step S1021, the multiple data include acid fracturing data, water injection data, well testing data, and production data.

[0023] Further preferably, the acid fracturing data is to collect statistics on acid fracturing curves of reservoirs with different fracture-cavity structure types, and determine the acid fracturing curves to qualitatively judge the fracture-cavity structure chart.

[0024] Further preferably, the water injection data is used to draw a water injection indicator curve for a fracture-cavity oil reservoir, and the cumulative injection volume and the injection pressure are plotted into an indicator curve, wherein the cumulative injection volume is the horizontal coordinate and the injection pressure is the vertical coordinate, and the change in the reservoir scale of the fracture-cavity body at different water injection stages is judged by the change in the slope.

[0025] More preferably, after judging the change in the scale of the fracture-cavity reservoir at different water injection stages by the change in slope, the volume of the fractures and caves affected during the water injection process is quantitatively calculated by the slope of the water injection indicator curve, thereby quantitatively characterizing the size of the reservoir; during the water injection process, the slope of the first curve section is k1, then the first set of affected volume V1=1 / k1Co, Co is the comprehensive compression coefficient; the second set of affected reservoir volume V2=1 / k1Co-1 / k1Co, V1+V2 is the volume of the entire fracture-cavity body.

[0026] Further preferably, the production data is for sorting out the production data in the identification of well point fracture and cave structures, screening three sensitive parameters including stable production period, water-free oil production period and water content change for range statistics, and establishing fracture and cave identification rules.

[0027] Preferably, step S1021 is specifically as follows: after inputting a variety of data, the first step is cumulative liquid production judgment, the second step is water-free oil production period, the first and second steps are cave identification modes, and the cave wells are output;

[0028] The third step is to determine the stable production period, and the fourth step is to determine the self-flowing period. The third and fourth steps are to exclude the fracture identification mode based on the cave well, obtain the fracture well, and output the fracture well;

[0029] The fifth step is to determine the stable production period, and the sixth step is to determine the cumulative liquid production, obtain the fracture hole wells, and output the fracture hole wells; the fifth and sixth steps are to exclude caves and fracture wells to carry out the fracture hole well identification mode.

[0030] Preferably, in step S1022, the multiple data include water injection curve, energy, production, and water content data.

[0031] Preferably, step S1022 is specifically as follows: after inputting various data related to the data, the first step is water injection judgment, the second step is water content judgment, and a fracture well is obtained; the first and second steps are fracture identification modes, and the fracture well is output;

[0032] The third step is water injection judgment, the fourth step is production judgment, and the fifth step is water content judgment. The third to fifth steps are fracture hole recognition modes, and fracture hole wells are output;

[0033] Excluding fracture holes and fracture wells, the sixth step is energy judgment, outputting cave wells.

[0034] Preferably, in step S1023, the multiple data include tracer data and production data.

[0035] Further preferably, the production data include injection-production response and inter-well pressure change response, and the qualitative judgment method mainly lies in simple judgments such as the injection-production correspondence relationship; the quantitative judgment of the inter-reservoir structure is: based on the analysis of the inter-well connectivity, dynamic parameters that are sensitive to the reservoir structure response are screened, including the unit injection pressure rise of the injection well to establish the water injection and gas injection oil increase effect identification index, and the energy change of other connected wells after the production of the recovery well is put into production to establish the production interference degree identification index.

[0036] Preferably, step S1023 specifically includes: inputting various data related to the first step of water injection production increase scale determination, obtaining fracture wells, and outputting fracture wells;

[0037] The second step is to determine the scale of water injection and production increase again, the third step is to determine the pressure difference between wells, and the fourth step is tracer; the second to fourth steps are to exclude the fracture hole identification mode based on the fracture wells and output the fracture hole wells.

[0038] Preferably, step S103 is specifically:

[0039] S1031, performing statistics on parameters of each well;

[0040] S1032. Comprehensively identify the reservoir structure of each well based on predetermined reservoir response parameters.

[0041] Further preferably, step S103 is specifically as follows:

[0042] S1031. Statistic the parameters such as the acid fracturing identification result, liquid production / water injection curve, water content curve, energy indication curve, water injection volume per unit pressure increase, energy indication curve, production curve, injection-production effect and tracer status of each well;

[0043] S1032, based on the predetermined reservoir response parameters, the reservoir structure of each well is comprehensively identified, and the parameters for dividing each well are as follows:

[0044] Well point: acid fracturing identification results, liquid production / water injection curve, water content curve, energy indication curve;

[0045] Well periphery: unit pressure rise water injection volume, energy indication curve, production curve, water content curve;

[0046] Interwell: energy indicator curve, injection-production effect, tracer.

[0047] Further preferably, in step S1032, the predetermined reservoir response parameter may also be a specific reservoir response parameter designated by the supervisor.

[0048] Further preferably, the identification method statically identifies different dynamic parameters at the same well to obtain different reservoir types for results evaluation, thereby comprehensively identifying the correct reservoir and then dividing the range; the range division should cover as many dynamic parameter points of all wells of the same reservoir type as possible under the response of a certain parameter, and obtain the response range of each parameter of different reservoir types; the parameter range is divided in a manner of continuously adjusting the multi-parameter range to correctly identify all wells.

[0049] Then, the present invention provides application of the above method in semi-quantitatively identifying fracture-cavity structure of fracture-cavity oil reservoir.

[0050] Furthermore, the present invention provides a dynamic parameter reservoir structure identification chart and / or a dynamic parameter reservoir structure identification model established by the above method.

[0051] Finally, the present invention provides the application of the above-mentioned dynamic parameter reservoir structure discrimination chart and / or dynamic parameter reservoir structure identification model in identifying the reservoir structure of complex oil reservoirs.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The method of the present invention realizes the semi-quantitative identification of the fracture-cavity structure of the fracture-cavity oil reservoir, and improves the reliability of fracture-cavity identification. The method of the present invention can be widely used in the identification of complex oil reservoir reservoir structures. Compared with the traditional method, the method of the present invention forms a quantitative standard suitable for the sample area, and establishes a corresponding discrimination chart, which can be applied to the later development practice of the sample area. At the same time, the application process of the method described in the present invention can be used as a reference for the development practice of the fracture-cavity oil reservoir with the same background. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1a It is a flow chart of the method for identifying the structure of fracture-vuggy oil reservoir in step S101 of the present invention.

[0055] Figure 1b It is a well test curve morphology diagram for classifying reservoir bodies in the present invention.

[0056] Figure 2 It is a flow chart of identifying well point reservoir structure of the present invention.

[0057] Figure 3 It is a flow chart of identifying the reservoir structure around a well according to the present invention.

[0058] Figure 4 It is a reservoir range map around the well for evaluating the overall dynamic data of the unit of the present invention.

[0059] Figure 5 It is a flow chart of inter-well reservoir structure identification of the present invention. DETAILED DESCRIPTION

[0060] The following non-limiting examples can make those of ordinary skill in the art understand the present invention more comprehensively, but do not limit the present invention in any way. The following content is merely an exemplary description of the scope of the present invention, and those skilled in the art can make various changes and modifications to the present invention according to the disclosed content, and it should also belong to the scope of the present invention. When the embodiment gives a numerical range, it should be understood that, unless otherwise specified in the present invention, the two endpoints of each numerical range and any numerical value between the two endpoints can be selected. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meanings as those of ordinary skill in the art to which the present invention belongs. The present invention will be further described below in the form of specific embodiments.

[0061] in, Figure 1a It is a flow chart of the method for identifying the structure of fracture-vuggy oil reservoirs described in Example 1 of the present invention.

[0062] Example 1

[0063] S101. Perform static structural identification on the reservoir body of the target fracture-vuggy oil reservoir.

[0064] By statistically analyzing the logging and drilling data of fracture-cavity reservoirs and combining the understanding of the fracture-cavity structure of seismic sculptures, the fracture-cavity structure of this embodiment is divided into three categories: caves, holes, and cracks, and six subcategories: filled holes, unfilled holes, scattered holes, bedding holes, structural fractures, and dissolution fractures. Table 1 shows the indicators for identifying reservoir structure using logging and drilling data.

[0065] Table 1

[0066]

[0067]

[0068] Table 2 shows the identification criteria for fracture-hole combination structures based on tracer quantitative conditions. Different fracture-hole combination structures show different characteristics in the tracer production curve morphology.

[0069] Table 2

[0070]

[0071]

[0072] Figure 1b A well test curve morphology diagram for classifying reservoirs is given; the classification is divided into V-shaped, double concave, late drop, rising closed, horizontal straight line, and rising straight line (slope 1 / 2). Figure 1bAs shown: V-shaped: vertical fractures are well developed and the reservoir is relatively large; double concave type: has 2 or more sets of reservoirs of a certain size; late drop type: has a reservoir of a certain size; rising straight line (slope 1 / 2) type: the reservoir is limited in size, with fractures or small fracture-cavities; rising closed type: constant volume reservoir; horizontal straight line type: radial flow, no boundary is detected, and the reservoir is relatively large in size.

[0073] S102. Dynamic parameter identification of the reservoir structure of the target fracture-vuggy oil reservoir.

[0074] S1021. Dynamically identify well point reservoir structure based on acid fracturing, water injection, well testing data, and production data;

[0075] (1) Acid fracturing data: Acid fracturing curves can characterize the communication of reservoirs. According to the curve shape, if the displacement remains basically unchanged, the pump pressure drops significantly, the acidizing effect is good, and there are fractures and caves with a communication scale. Based on this principle, the acid fracturing curves of reservoirs with different fracture-cavity structure types are statistically analyzed to determine the acid fracturing curves for qualitatively judging the fracture-cavity structure.

[0076] (2) Water injection data: The water injection indicator curve of the fracture-cavity reservoir is drawn using the water injection data. The water injection pressure wave is judged by the curve shape, and the fracture-cavity structure is inferred. The water injection indicator curve is used to qualitatively judge the fracture-cavity structure, which is divided into a single-cavity model, a fracture-cavity model, and two double-cavity models with different pressures.

[0077] The water injection indicator curve of fracture-cavity reservoirs plots the cumulative injection volume (abscissa) and the injection pressure (ordinate) into an indicator curve, and the change in the reservoir scale of the fracture-cavity body at different water injection stages is judged by the change in the slope.

[0078] After qualitatively judging the reservoir structure through the curve morphology, the volume of fractures and caves affected during the water injection process can be quantitatively calculated through the slope of the water injection indicator curve, thereby quantitatively characterizing the size of the reservoir. During the water injection process, the slope of the first section of the curve is k1, then the first set of affected volume V1 = 1 / k1Co, Co is the comprehensive compression coefficient; the second set of affected reservoir volume V2 = 1 / k1Co-1 / k1Co, V1+V2 is the volume of the entire fracture body.

[0079] (3) Well test data: Reservoirs are classified according to the shape of the well test curve.

[0080] (4) Production data: In the identification of well point fracture and cave structures, production data are sorted out, and three sensitive parameters, namely, stable production period, water-free oil production period and water content change, are selected for range statistics to establish fracture and cave identification rules. The stable production period characterizes the scale of the reservoir and reservoir properties; the water-free oil production period characterizes the scale of the reservoir; and the water content change characterizes the relationship between the reservoir and the edge and bottom water.

[0081] Among them, the relationship between the range of reservoir structure parameters for quantitative judgment of liquid production change, water content change and production performance is shown in Table 3:

[0082] Table 3

[0083]

[0084] Figure 2 The specific method flow of dynamically identifying the well point reservoir structure described in step S1021 is further given: after inputting data (acid fracturing, water injection, well test data, production data), the first step is to determine the cumulative liquid production: stable liquid production ≥ 40t / d, slowly decreasing in the later period, cumulative liquid production ≥ 7×10 4 t is the cave identification condition. The second step is the waterless oil production period: the cave identification condition is that the waterless oil production period is ≥650d. The first and second steps are the cave identification mode, and the output is the cave well. The third step is the stable production period judgment: the judgment condition is that there is no stable production period. The fourth step is the self-flowing period judgment: the judgment condition is that the self-flowing period is ≤2 months. The third and fourth steps are the fracture identification mode based on the exclusion of the cave well, and the fracture well is obtained, and the fracture well is output. The fifth step is the stable production period judgment, and the judgment condition is that the stable production period is 138-398d. The sixth step is the cumulative liquid production judgment, and the judgment condition is the cumulative liquid production of 4.9-6.4×10 4 t, get the fracture hole well, output the fracture hole well, the fifth and sixth steps are to exclude the cave and fracture wells to carry out the fracture hole well identification mode.

[0085] S1022. Dynamically identify the reservoir structure around the well based on injection curve, energy, production and water content data;

[0086] Figure 3 The specific method flow of dynamically identifying the structure of the reservoir around the well is further given: after inputting relevant data (water injection curve, production curve, energy indication curve), the first step is water injection judgment: the judgment condition is that the pressure rise water injection volume in the water injection curve is <0.008 ten thousand cubic meters / MPa in the early stage of the fracture and <0.06 ten thousand cubic meters / Mpa in the later stage; the second step is water content judgment: the judgment condition is that the step production period of the water cut curve is <60 days; and the fracture well is obtained. The first and second steps are the fracture identification mode, and the fracture well is output; the third step is water injection judgment, and the judgment condition is that the pressure rise water injection volume in the water injection curve is <0.6 ten thousand cubic meters / MPa in the early stage and 0.08-0.3 ten thousand cubic meters / MPa in the later stage; the fourth step is production judgment, and the judgment condition is that the step production period of the water cut curve is 60-210 days; the fifth step is water content judgment, and the fracture hole well is obtained. The third to fifth steps are the fracture and hole identification mode, outputting fracture and hole wells; excluding fracture and hole wells, the sixth step is energy judgment: the judgment condition is that the slope increase factor of the pressure drop and liquid production in the energy indication curve is ≥0.8, and the cave wells are output.

[0087] Figure 4 A graphic representation of the reservoir range around the well is given using the overall dynamic data of the unit. Figure 3 The identification process makes a chart after distinguishing all sample points. The division range is to cover all the dynamic parameter points of the same reservoir type in the well as much as possible under the response of a certain parameter, and obtain the response range of each parameter of different reservoir types. In this process, refer to the following principles: ① When there is an interval in the dynamic parameter range of different reservoir types, divide it according to the main range and interval distance; ② When there is no obvious interval between single dynamic parameters, divide it according to ①, and combine multiple methods (>50%) to identify the correct reservoir with a high probability. In the later stage, the sample data that needs to be verified will be directly put into the chart for judgment.

[0088] S1023. Dynamic identification of reservoir structure between wells based on tracers and production data;

[0089] (1) Tracer data: The tracer data interpretation method can quantitatively or semi-quantitatively characterize the flow channels of the reservoir, and finely characterize the flow channels between reservoirs and other information based on the fracture-cavity configuration method tracer interpretation model. Different tracer curve shapes represent the patterns of reservoir configurations, including fractures, faults, caves, and various types of their combinations.

[0090] (2) Production data: There is a large amount of data to support the judgment of connectivity and connectivity structure, including injection-production response (scale of water injection to increase production) and inter-well pressure change response (inter-well pressure difference). The qualitative judgment method mainly relies on simple judgments such as the injection-production correspondence relationship. The quantitative judgment of the reservoir inter-structure is as follows: based on the analysis of the inter-well connectivity, dynamic parameters that are sensitive to the reservoir structure response are screened, including the unit injection pressure rise of the injection well to establish the water injection and gas injection oil increase effect identification index, and the energy change of other connected wells after the production of the recovery well is used to establish the production interference identification index.

[0091] Table 4 gives the equivalent interpretation technical indicators of interwell tracers for typical unit fracture-cavity reservoirs of S74, T739 and TH12402.

[0092] Table 4

[0093]

[0094] Figure 5A specific flow chart of the method for identifying the inter-well reservoir structure described in this step is given: after inputting relevant data (water injection production increase scale, inter-well pressure difference, tracer), the first step is water injection production increase scale judgment: the judgment condition is 0-0.5 million cubic meters / MPa, and fracture wells are obtained and output fracture wells; the second step is water injection production increase scale judgment again: the judgment condition is 0.5-2.5 million cubic meters / MPa; the third step is inter-well pressure difference judgment: the judgment condition is inter-well pressure difference 1-8MPa; the fourth step is tracer: the judgment condition is advancement speed 5-150m / d, and the response well concentration expansion multiple is 5-20. The second to fourth steps are the fracture hole identification mode based on the exclusion of fracture wells, and the fracture hole wells are output.

[0095] S103. Based on the static structure identification and dynamic parameter identification of the reservoir structure of the target fracture-vuggy oil reservoir, a dynamic parameter reservoir structure identification model is established.

[0096] Through the comprehensive understanding of the fracture-cavity structure of the dynamic and static data of the three units, the sensitive parameters and value ranges of the dynamic parameter identification fracture-cavity structure are statistically analyzed, and finally a dynamic parameter reservoir structure discrimination chart is formed. It can assist in the judgment of fracture-cavity structure and strengthen the understanding of the fracture-cavity structure of the wells in the study area.

[0097] S1031. Statistic the parameters such as the acid fracturing identification result, liquid production / water injection curve, water content curve, energy indication curve, water injection volume per unit pressure increase, energy indication curve, production curve, injection-production effect and tracer status of each well;

[0098] S1032, based on the predetermined reservoir response parameters, the reservoir structure of each well is comprehensively identified, and the parameters for dividing each well are as follows: well point (acid fracturing identification result, liquid production / water injection curve, water content curve, energy indication curve);

[0099] Well periphery (unit pressure rise water injection volume, energy indication curve, production curve, water content curve);

[0100] Interwell (energy indication curve, injection-production effect, tracer).

[0101] The predetermined reservoir response parameters may be specific reservoir response parameters designated based on expert supervision.

[0102] Among them, the identification method uses static identification of different dynamic parameters at the same well to evaluate the results of different reservoir types, thereby comprehensively identifying the correct reservoir and then dividing the range. The division range should cover all dynamic parameter points of the same reservoir type well as much as possible under the response of a certain parameter, and obtain the response range of each parameter of different reservoir types. In this process, refer to the following principles: ① When there is an interval in the dynamic parameter range of different reservoir types, divide it according to the main range and interval distance; ② When there is no obvious interval between single dynamic parameters, divide it according to ①, and combine multiple methods (>50%) to identify the correct reservoir with a high probability. Continuously adjust the multi-parameter range to correctly identify all wells and divide the parameter range.

[0103] Taking the typical unit S80 as a sample, the reservoir types of each well were classified according to the comprehensive identification results, and the statistics of various parameters were carried out, and their corresponding ranges were determined according to the division principles.

[0104] Table 5 is the dynamic parameter identification record of the S80 unit well point.

[0105] Table 5

[0106]

[0107]

[0108]

[0109] Table 6 is the record of dynamic parameter identification around the well of S80 unit.

[0110] Table 6

[0111]

[0112]

[0113] Table 7 is the S80 unit well dynamic parameter identification record.

[0114] Table 7

[0115]

[0116] According to the above method, the final effect of the application of the method of the present invention is: Figure 4 , Table 5-Table 7, using the method described in the present invention to establish Figure 4 The template can be used for prediction in the unimplemented areas later; the traditional method can only identify a certain fracture-cavity structure from a single factor, and cannot predict the later development practice. Compared with the traditional method of the prior art, the present invention realizes the semi-quantitative identification of the fracture-cavity structure of fracture-cavity reservoirs and improves the reliability of fracture-cavity identification.

[0117] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than limiting the protection scope of the present invention. Any simple modification or equivalent replacement made by those of ordinary skill in the art to the technical solution of the present invention shall not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for identifying the reservoir structure of fracture-cavity oil reservoirs. It is characterized in that Includes steps: S101: Static structural identification of the reservoir structure of the target fracture-cavity oil reservoir; S1011: Identify the reservoir type of the target fracture-cavity body; S1012: Identify the target fracture-cavity body and the fracture-cavity structure between the fracture-cavity bodies; S102: Dynamic parameter identification of the reservoir structure of the target fracture-cavity oil reservoir; S1021: Dynamically identify well point reservoir structure based on multiple data; S1022: Dynamically identify the reservoir structure around the well based on multiple data; S1023: Dynamically identify inter-well reservoir structure based on multiple data; S103: Based on the static structure identification and dynamic parameter identification of the reservoir structure of the target fracture-vuggy oil reservoir, a dynamic parameter reservoir structure identification model is established.

2. The method according to claim 1, It is characterized in that Step S1011 is specifically: classifying the reservoir body according to the shape of the well test curve; the classification is divided into V-shaped, double concave type, late drop type, rising closed type, horizontal straight line type, and rising straight line type.

3. The method according to claim 1, It is characterized in that Step S1012 is specifically as follows: classify the fracture-cavity structure by statistically analyzing the well logging and drilling data of the fracture-cavity oil reservoir and combining the fracture-cavity structure knowledge of the seismic sculpture; and identify the fracture-cavity combination structure according to the quantitative situation of the tracer.

4. The method according to claim 1, It is characterized in that In step S1021, the various data include acid fracturing data, water injection data, well testing data, and production data.

5. The method according to claim 4, It is characterized in that The acid fracturing data is to statistically analyze the acid fracturing curves of reservoirs with different fracture-cavity structural types and determine the acid fracturing curves for qualitatively judging the fracture-cavity structure.

6. The method according to claim 4, It is characterized in that The water injection data is used to draw a water injection indicator curve for fracture-cavity oil reservoirs. The cumulative injection volume and injection pressure are plotted into an indicator curve, wherein the cumulative injection volume is the horizontal axis and the injection pressure is the vertical axis. The change in the reservoir scale of the fracture-cavity body at different water injection stages is judged by the change in the slope.

7. The method according to claim 6, It is characterized in that After judging the change of fracture-cavity reservoir scale at different water injection stages through the change of slope, the volume of fractures and caves affected during water injection is quantitatively calculated through the slope of water injection indicator curve, so as to quantitatively characterize the reservoir size; during water injection, the slope of the first curve is k1, then the first set of affected volume V1=1 / k1Co, Co is the comprehensive compression coefficient; The volume of the second set of affected reservoirs is V2 = 1 / k1Co-1 / k1Co, and V1+V2 is the volume of the entire fracture-cavity body.

8. The method according to claim 4, It is characterized in that The production data is used to sort out the production data in the identification of well point fracture and cave structures, select three sensitive parameters, namely, stable production period, water-free oil production period and water content change, for range statistics, and establish fracture and cave identification rules.

9. The method according to claim 1, It is characterized in that Step S1021 is specifically as follows: after inputting a variety of data, the first step is cumulative liquid production judgment, the second step is water-free oil production period, the first and second steps are cave identification modes, and the cave wells are output; The third step is to determine the stable production period, and the fourth step is to determine the self-flowing period. The third and fourth steps are to exclude the fracture identification mode based on the cave well, obtain the fracture well, and output the fracture well; The fifth step is to determine the stable production period, and the sixth step is to determine the cumulative liquid production, obtain the fracture hole wells, and output the fracture hole wells; the fifth and sixth steps are to exclude caves and fracture wells to carry out the fracture hole well identification mode.

10. The method according to claim 1, It is characterized in that In step S1022, the various data include water injection curve, energy, production, and water content data.

11. The method according to claim 1, It is characterized in that Step S1022 is specifically as follows: after inputting various data related to the data, the first step is water injection judgment, the second step is water content judgment, and a fracture well is obtained; the first and second steps are fracture identification modes, and a fracture well is output; The third step is water injection judgment, the fourth step is production judgment, and the fifth step is water content judgment. The third to fifth steps are fracture hole recognition modes, and fracture hole wells are output; Excluding fracture holes and fracture wells, the sixth step is energy judgment, outputting cave wells.

12. The method according to claim 1, It is characterized in that In step S1023, the multiple data include tracer data and production data.

13. The method according to claim 12, It is characterized in that The production data include injection-production response and inter-well pressure change response, and the qualitative judgment method mainly lies in simple judgments such as the injection-production correspondence relationship; the quantitative judgment of the inter-reservoir structure is: based on the analysis of the inter-well connectivity, dynamic parameters that are sensitive to the reservoir structure response are screened, including the unit injection pressure rise of the injection well to establish the water injection and gas injection oil increase effect identification index, and the energy change of other connected wells after the production of the recovery well is put into production to establish the production interference degree identification index.

14. The method according to claim 1, It is characterized in that Step S1023 specifically includes: inputting various data related to the first step of water injection production increase scale determination, obtaining fracture wells, and outputting fracture wells; The second step is to determine the scale of water injection and production increase again, the third step is to determine the pressure difference between wells, and the fourth step is tracer; the second to fourth steps are to exclude the fracture hole identification mode based on the fracture wells and output the fracture hole wells.

15. The method according to claim 1, It is characterized in that Step S103 is specifically as follows: S1031, performing statistics on parameters of each well; S1032. Comprehensively identify the reservoir structure of each well based on predetermined reservoir response parameters.

16. The method according to claim 15, It is characterized in that Step S103 is specifically as follows: S1031. Statistic the parameters such as the acid fracturing identification result, liquid production / water injection curve, water content curve, energy indication curve, water injection volume per unit pressure increase, energy indication curve, production curve, injection-production effect and tracer status of each well; S1032, based on the predetermined reservoir response parameters, the reservoir structure of each well is comprehensively identified, and the parameters for dividing each well are as follows: Well point: acid fracturing identification results, liquid production / water injection curve, water content curve, energy indication curve; Well periphery: unit pressure rise water injection volume, energy indication curve, production curve, water content curve; Interwell: energy indicator curve, injection-production effect, tracer.

17. Use of the method according to any one of claims 1 to 16 in semi-quantitatively identifying fracture-cavity structures in fracture-cavity oil reservoirs.

18. A dynamic parameter reservoir structure discrimination chart and / or a dynamic parameter reservoir structure identification model established by the method according to any one of claims 1 to 16.

19. Application of the state parameter reservoir structure discrimination chart and / or the dynamic parameter reservoir structure identification model as claimed in claim 18 in identifying the reservoir structure of a complex oil reservoir.

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