A method and system for identifying carbonate reservoirs in a well-free field area

Abstract

The application discloses a method and system for identifying carbonate reservoirs in a well-free work area, comprising the following steps: determining a target interval according to well logging and seismic data of a conjugate basin of a basin where the well-free work area is located; establishing a model for representing the relationship between acoustic velocity and density according to acoustic velocity and density of a well work area in the conjugate basin; obtaining a layer velocity body according to the depth domain seismic velocity of the well-free work area; establishing a pseudo-well density curve and a density body of the well-free work area by using the model for representing the relationship between acoustic velocity and density, and based on this, performing wave impedance inversion calculation of the well-free work area by using the layer velocity body; and identifying favorable carbonate reservoirs in the target interval based on the wave impedance body of the well-free work area.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, and in particular to a method and system for identifying carbonate reservoirs in un-welled work areas. Background Technology

[0002] With the deepening of oil and gas exploration and development, carbonate reservoirs in the South Atlantic Basin have become one of the research hotspots. The basins on both sides of the South Atlantic are conjugate passive continental margin basins formed by the Atlantic rift, with similar evolutionary processes and hydrocarbon accumulation characteristics, and the same source rocks.

[0003] Numerous conjugate sedimentary basins have developed along the passive continental margin of the South Atlantic. New oil and gas discoveries are mainly concentrated in the deep-water areas of these basins, all exhibiting three significant tectonic evolution phases. Most basins experienced a brief period of subsidence following the rifting phase. Corresponding to this tectonic evolution, most basins exhibit three important strata: rifting-phase continental clastic rocks (with widespread igneous rocks in most basins), transitional marine shallow-marine sediments (with widespread salt rocks in some basins), and drift-phase shallow-marine and deep-sea carbonate rocks. The study area consists of lacustrine carbonate deposits with uniform organic matter types, high organic carbon content, and well-developed dissolution pores, making it a high-quality source rock reservoir. However, exploration and research in the basins of this study area are relatively limited, and subsalt reservoirs have not yet been drilled.

[0004] Density data is frequently used in forward and inverse seismic data. Currently, the South Atlantic A Basin in the study area is in the early stages of exploration and there is no drilling data available, so this parameter cannot be directly obtained. It is generally taken as a constant or the density is calculated by converting the P-wave velocity. Previous researchers often used the Gardner empirical formula to estimate rock density. This formula is an average conversion formula between velocity and density under different lithologies, and it is generally a power function. However, when the strata and lithofacies are highly heterogeneous, significant errors may occur due to the representativeness of the selected sonic transit time value. Therefore, the Gardner empirical formula urgently needs improvement.

[0005] Previous studies have typically identified favorable carbonate reservoirs based on well logging response characteristics to identify lithofacies, combined with interpretation of key reservoir parameters. This process evaluates favorable intervals in individual wells, and then clarifies the reflection characteristics of different lithofacies combinations through petrophysical and seismic response analysis. Multi-attribute principal component analysis is then used to fuse attributes and determine the spatial distribution of sweet spot reservoirs. However, Basin A in the study area is undeveloped, with limited well data, making it impossible to determine favorable reservoir intervals using conventional methods.

[0006] Therefore, existing technologies need to provide a solution for identifying carbonate reservoirs in basin areas with few wells and limited data. Summary of the Invention

[0007] The purpose of this invention is to provide a scheme for identifying carbonate reservoirs in basin areas with few or no wells and limited data.

[0008] To address the aforementioned technical problems, embodiments of the present invention provide a method for identifying carbonate reservoirs in wellless work areas, comprising: determining the target interval based on well logging and seismic data from conjugate basins within the basin where the wellless work area is located; establishing a model characterizing the relationship between acoustic velocity and density based on the acoustic velocity and density of well-worked areas within the conjugate basins; obtaining the layer velocity volume based on the depth-domain seismic velocity of the wellless work area; establishing a pseudo-well density curve and density volume for the wellless work area using the acoustic velocity-density relationship model, and performing acoustic impedance inversion calculations for the wellless work area based on the layer velocity volume; and identifying favorable carbonate reservoirs in the target interval based on the acoustic impedance volume of the wellless work area.

[0009] Preferably, the step of obtaining the layer velocity volume based on the depth-domain seismic velocity of the wellless work area includes: converting the seismic velocity and layer interpretation data of the wellless work area in the depth domain to the time domain; and obtaining the layer velocity volume based on the seismic velocity data in the time domain using the root mean square calculation method.

[0010] Preferably, the step of establishing a pseudo-well density curve and density volume of the wellless work area using the acoustic velocity-density relationship model, and then performing wave impedance inversion calculation of the wellless work area using the layer velocity volume, includes: obtaining the pseudo-well density curve and density volume based on the acoustic velocity of the wellless work area using the acoustic velocity-density relationship model; multiplying the pseudo-well density curve and density volume simultaneously with the layer velocity volume to obtain the initial inversion model; creating a synthetic seismic record of the wellless work area by extracting a proportional wavelet based on the seismic interpretation data of the wellless work area and the pseudo-well density curve; and performing wave impedance inversion calculation of the wellless work area based on the seismic velocity data in the time domain, the layer interpretation data in the time domain, the synthetic seismic record, and the initial inversion model to obtain the wave impedance volume of the wellless work area.

[0011] Preferably, the step of establishing the pseudo-well density curve and density volume of the wellless work area using the acoustic velocity-density relationship model, and then using the layer velocity volume to perform wave impedance inversion calculation of the wellless work area, further includes: verifying the synthetic seismic record, including: judging whether the current synthetic seismic record is qualified by comparing the degree of conformity between the current synthetic seismic record and the actual seismic velocity and pseudo-well density of the wellless work area, so as to use the qualified synthetic seismic record to carry out wave impedance volume inversion.

[0012] Preferably, the step of establishing a model characterizing the relationship between acoustic velocity and density based on the acoustic velocity and density of a well-drilled area in the conjugate basin includes: fitting the acoustic velocity and density data obtained from logging at a carbonate reservoir using the first target well in the well-drilled area to obtain an initial relationship between acoustic velocity and density; selecting a second target well in the well-drilled area that simultaneously possesses carbonate and mudstone lithologies, and using the initial relationship between acoustic velocity and density, converting the acoustic velocity data of the second target well into density data, denoted as the density data for calculation; fitting the relationship between the density data for calculation and the measured density data of the second target well to obtain an optimized density relationship for eliminating the influence of lithology; and using the initial relationship between acoustic velocity and density and the optimized density relationship to form the acoustic velocity and density relationship model.

[0013] Preferably, the step of determining the target layer based on well logging and seismic data from the conjugate basin of the basin where the wellless work area is located includes: determining the preliminary depth of the target layer by analyzing the lithology, fluid composition, and oil content at different depths based on the natural gamma value of the conjugate basin of the basin where the wellless work area is located; and optimizing and adjusting the preliminary depth of the target layer based on the density value and sonic transit time value of the conjugate basin to obtain the final depth of the target layer.

[0014] Preferably, the step of identifying favorable carbonate reservoirs in the target section based on the impedance volume of the wellless work area includes: taking data points in the impedance volume whose impedance values ​​exceed a preset threshold as favorable carbonate locations, thereby forming favorable carbonate reservoirs based on all favorable carbonate locations.

[0015] On the other hand, embodiments of the present invention provide a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the method described above.

[0016] In addition, this invention also provides a system for identifying carbonate reservoirs in wellless work areas, comprising: a target interval identification module configured to determine the target interval based on well logging and seismic data from conjugate basins of the basin where the wellless work area is located; a velocity-density relationship model generation module configured to establish a model characterizing the relationship between acoustic velocity and density based on acoustic velocity and density from well-drilled work areas in the conjugate basin; a layer velocity volume conversion module configured to obtain a layer velocity volume based on the depth-domain seismic velocity of the wellless work area; a wave impedance inversion module configured to establish a pseudo-well density curve and density volume of the wellless work area using the acoustic velocity-density relationship model, and based on this, perform wave impedance inversion calculations of the wellless work area using the layer velocity volume; and a carbonate reservoir identification module configured to identify favorable carbonate reservoirs in the target interval based on the wave impedance volume of the wellless work area.

[0017] Preferably, the carbonate reservoir identification module is further configured to identify data points in the impedance volume whose impedance values ​​exceed a preset threshold as favorable carbonate locations, thereby forming favorable carbonate reservoirs based on all favorable carbonate locations.

[0018] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0019] This invention proposes a method and system for identifying carbonate reservoirs in well-free exploration areas. This method and system are designed for study areas still in the early stages of exploration, lacking drilling data and not meeting the requirements for conventional seismic logging interpretation. It directly utilizes conjugate basin logging information as constrained seismic velocities to conduct well-free inversion for carbonate reservoir identification. This effectively solves the technical challenges of obtaining logging response characteristics, calculating synthetic seismic records, extracting wavelets, and performing seismic absolute impedance inversion under unconventional conditions when drilling logging data is unavailable. The method is highly practical and reliable.

[0020] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0021] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0022] Figure 1 This is a schematic diagram illustrating the steps of a method for identifying carbonate reservoirs in wellless work areas according to an embodiment of this application.

[0023] Figure 2 This is a graph showing the density curve calculated using the improved Gardner formula in the method for identifying carbonate reservoirs in wellless work areas according to an embodiment of this application.

[0024] Figure 3 This is an example diagram of the seismic profile-level wellless inversion impedance results for the unwell-taught area in the method for identifying carbonate reservoirs in unwell-taught areas according to an embodiment of this application.

[0025] Figure 4 This is a block diagram of a system module for identifying carbonate reservoirs in wellless work areas, according to an embodiment of this application. Detailed Implementation

[0026] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0027] Furthermore, the steps illustrated in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than that presented here.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0029] To address the problems mentioned above, this application of the present invention provides a method and system for identifying carbonate reservoirs in well-free exploration areas. This method and system utilizes well logging and seismic data from conjugate basins, employs a modified Gardner formula to establish a velocity-density relationship, and eliminates errors caused by lithology influencing the calculation results of the Gardner formula, thus reducing prediction accuracy. Based on the calculated density, wave impedance is obtained through well logging-constrained seismic velocity inversion, enabling favorable reservoir prediction in the study area. This invention effectively solves the technical challenges of obtaining well logging response characteristics, calculating synthetic seismic records, extracting wavelets, and performing seismic absolute wave impedance inversion under unconventional conditions when no drilling logging data is available. It aims to guide the reserve development of basins still in the early exploration stages by drawing on the oil and gas exploration and development results of conjugate basins.

[0030] Example 1

[0031] Figure 1 This is a schematic diagram illustrating the steps of a method for identifying carbonate reservoirs in wellless work areas according to an embodiment of this application. See below for reference. Figure 1 The specific steps of the method for identifying carbonate reservoirs in wellless work areas (also known as the "carbonate reservoir identification method") described in the embodiments of the present invention will be explained.

[0032] like Figure 1As shown, in step S110, the target section is determined based on the well logging and seismic data of the conjugate basin of the basin where the wellless work area is located.

[0033] In step S110, firstly, based on the natural gamma data values ​​obtained during well logging from the conjugate basin of the basin where the wellless work area to be evaluated is located, the preliminary depth of the target layer is determined by analyzing the lithology, fluid composition and oil content at different depths. Then, based on the density value and sonic transit time value of the conjugate basin, the preliminary depth of the target layer is optimized and adjusted to obtain the final depth of the target carbonate rock layer.

[0034] Based on well data from conjugate basins, well logging curves (such as natural gamma logging GR) and well logging data (such as the color of carbonate rocks and other lithologies) are obtained. The depth of the target layer is determined by analyzing significant differences in composition and oil content. Well logging curves are the primary means of determination. Since well logging and cuttings logging cover a large area, well logging curves (GR) can be used to determine the depth directly.

[0035] When the lithology is carbonate rock, the natural gamma (GR) value is low, while for other lithologies such as mudstone, the natural gamma (GR) value is high, which can be used to determine the preliminary depth of the target layer.

[0036] Then, based on the petrographic data of the well-drilled areas in the conjugate basin, further analysis was conducted to determine the reservoir criteria in order to optimize and adjust the initial depth of the target layer.

[0037] Carbonate rocks differ significantly from other lithologies in well logging curves. However, if the mineral content within the lithology varies greatly, such as between carbonate rocks and mudstone, the half-amplitude point of the GR logging curve is generally used to distinguish limestone from other lithologies. A high natural gamma ray GR value indicates mudstone, while a low natural gamma ray GR value indicates limestone. However, if the natural gamma ray GR logging curve does not fluctuate significantly, using GR alone is not appropriate. Therefore, in step S110 of this embodiment, the density (DEN) logging curve and sonic transit time (AC) logging curve of the well-drilled area in the conjugate basin are also used to comprehensively determine the true location of the target layer.

[0038] For example, when the lithology is carbonate rock, the GR value is relatively low, which can also be seen from the density DEN being between 2.4 and 2.7 g / cm³. 3 The approximate depth range of the carbonate reservoir (target layer) is determined by considering the acoustic transit time (AC) value within the range of 165-250 μs / ft (which is considered high).

[0039] After determining the depth of the target layer, proceed to step S120.

[0040] Step S120: Based on the acoustic velocity and density of the well-drilled areas in the conjugate basin, establish a model characterizing the relationship between acoustic velocity and density.

[0041] Specifically, in step S120, firstly, the acoustic velocity and density data obtained from logging the first target well in the well-drilled area at the carbonate reservoir are fitted to obtain an initial relationship between acoustic velocity and density.

[0042] Since the Gardner formula typically fits density using acoustic velocity when density data is lacking, the classic Gardner formula exhibits certain errors when applied to different blocks. Therefore, this embodiment of the invention selects a well with carbonate reservoirs within a well-drilled area in a conjugate basin, designated as the first target well. Based on the acoustic velocity and density data obtained from logging the first target well, the relationship between acoustic velocity and density data is fitted to obtain an improved Gardner formula, denoted as the initial relationship between acoustic velocity and density, which is used to calculate the density curve of the target layer.

[0043] In this way, an improved Gardner formula can be derived by fitting the data relationship between velocity and density in well blocks and carbonate reservoirs.

[0044] Secondly, a second target well with both carbonate and mudstone lithology is selected from the well-drilled area in the current conjugate basin. Using the above-mentioned initial relationship between acoustic velocity and density, the acoustic velocity data of the second target well is converted into density data, which is denoted as the density data for calculation.

[0045] Based on the acoustic velocity data obtained during logging of the second target well, density data under different lithologies is obtained by using the initial relationship between acoustic velocity and density, i.e., the density data for calculation.

[0046] Next, the calculated density data and the measured density data obtained during actual logging of the second target well were fitted together to obtain the density optimization formula for eliminating the influence of lithology. See [link to relevant documentation]. Figure 2 .

[0047] While the improved Gardner formula performs well and accurately in carbonate lithology, its accuracy drops significantly for other lithofacies such as argillaceous limestone due to lithological influences. To improve accuracy, a density optimization formula is obtained by correlating the measured density of other lithofacies with the density calculated using the improved Gardner formula. This is achieved by performing correlation fitting between the measured density and the density calculated using the improved Gardner formula, thus eliminating the lithological error in density calculations for other lithofacies reservoirs and obtaining a new, optimized density curve.

[0048] Finally, using the above-mentioned initial and optimized relationships between sound wave velocity and density, the sound wave velocity and density relationship model required for the embodiments of the present invention is formed.

[0049] Step S130: Obtain the layer velocity volume based on the depth domain seismic velocity of the wellless work area.

[0050] In step S130, the seismic velocity and layer interpretation data of the wellless work area in the depth domain are converted to the time domain. Then, based on the seismic velocity data in the time domain, the root mean square calculation method is used to obtain the layer velocity volume.

[0051] Since the basin where the wellless work area to be studied is located is in the early stage of exploration and there is no drilling data, seismic interpretation can only be completed in the depth domain. It is impossible to calculate the synthetic seismic record or extract the seismic wavelet, and it cannot meet the requirements of the seismic absolute wave impedance inversion operation under conventional conditions. Therefore, the embodiment of the present invention can give full play to the role of seismic velocity in the wellless work area.

[0052] Using existing seismic velocity data in the wellless work area to be studied, the depth-domain seismic data and the layer interpretation data are converted from the depth domain to the time domain, respectively, and the seismic velocity volume is converted from the time domain to the depth domain.

[0053] Then, based on time-domain seismic velocity data, the following expression is used to convert seismic stacking velocity (time-domain seismic velocity data) into a layer velocity model:

[0054]

[0055] Among them, v i Representing time t i The earthquake velocity is given by v, where v represents the layer velocity and n represents the total number of data points required to calculate the velocity data of a specific layer.

[0056] After obtaining the layer velocity volume of the wellless work area, proceed to step S140 to perform wave impedance volume inversion on the wellless work area.

[0057] In step S140, using the acoustic velocity-density relationship model obtained in step S120, a pseudo-well density curve and density volume of the wellless work area are established. Based on the pseudo-well density curve and density volume of the wellless work area, the wave impedance inversion calculation of the wellless work area is performed using the layer velocity volume produced in step S130.

[0058] Specifically, step S140 includes the following steps.

[0059] The first step is to obtain the pseudo-well density curve and density volume based on the acoustic velocity in the un-welled work area and using the acoustic velocity-density relationship model.

[0060] Based on the acoustic velocity volume of the wellless work area, the density volume of the wellless work area is obtained by sequentially using the constructed initial relationship between acoustic velocity and density and the density optimization relationship, and the corresponding pseudo-well density curve is formed.

[0061] The second step involves multiplying the pseudo-well density curve and density volume obtained in the first step based on the wellless work area with the layer velocity volume calculated in step S130 to obtain the initial wave impedance volume, thus obtaining the initial inversion model.

[0062] The third step involves extracting proportional wavelets and creating synthetic seismic records based on the seismic interpretation data of the wellless work area and the pseudo-well density curve obtained in the first step.

[0063] First, spectral analysis is performed on the seismic interpretation data of the wellless work area to obtain the frequency information of the seismic data for setting the wavelet frequency; then, using the pseudo-well density curve, the seismic wavelet in the seismic interpretation data is extracted proportionally according to the wavelet frequency, thereby producing a synthetic seismic record.

[0064] In addition, to ensure the rationality of the synthetic seismic record, the embodiments of the present invention will also verify the synthetic seismic record in the third step.

[0065] In one embodiment, the suitability of the current synthetic seismic record is determined by comparing the degree of agreement between the current synthetic seismic record and the actual seismic traces and pseudo-well density in the wellless work area. The synthetic seismic record that is deemed to be suitable is then used to perform wave impedance volume inversion.

[0066] The current synthetic seismic record is compared with the actual seismic trace. The consistency between the QC seismic velocity and the density data obtained from the pseudo-well density calculation is compared. If they are generally consistent, the current synthetic seismic record is deemed qualified, and then the process proceeds to the fourth step.

[0067] The fourth step involves conducting wave impedance inversion calculations for the wellless work area based on the seismic velocity data in the time domain, the layer interpretation data in the time domain, the qualified synthetic seismic records, and the aforementioned initial inversion model, to obtain the wave impedance volume of the wellless work area.

[0068] Using the transformed time-domain seismic data, interpreted horizons, extracted seismic wavelets, and initial wave impedance model volume, the final well-free wave impedance inversion calculation was achieved through a series of inversion parameter optimizations. The inversion results of the obtained well-free wave impedance volume can be found in [reference missing]. Figure 3 The image below.

[0069] Figure 3 The image above shows a seismic profile of a wellless work area. Figure 3 It can be seen that the comparison between the seismic profiles and the inverted profiles in the same region shows a high degree of consistency, thus reflecting a good inversion effect.

[0070] After obtaining the wave impedance volume of the wellless work area, proceed to step S150.

[0071] Step S150: Based on the wave impedance volume of the wellless work area, identify the favorable carbonate reservoirs in the target section identified in step S110.

[0072] In one embodiment, data points in the impedance volume of the wellless work area that exceed a preset threshold are taken as favorable locations of carbonate rocks, thereby forming favorable carbonate rock reservoirs based on all favorable locations of carbonate rocks.

[0073] Favorable reservoirs in wellless blocks are identified through wellless seismic inversion. The acoustic impedance volume obtained from wellless seismic inversion is used to identify favorable reservoirs. When the acoustic impedance exceeds a preset threshold, it is considered a carbonate reservoir, and thus a favorable carbonate reservoir is determined.

[0074] Example 2

[0075] Based on the above-described carbonate reservoir identification method, the method described in Example 1 is applied to a specific example to illustrate the specific process of the method for identifying carbonate reservoirs without wells based on well-constrained seismic velocities in conjugate basin logging.

[0076] In step 1, the target layer and depth are determined by combining well logging and seismic data from relevant work areas in the South Atlantic oil and gas basin.

[0077] Taking a well in conjugate basin A of the South Atlantic study area as an example, the depth of the target layer can be determined based on logging curves such as natural gamma logging (GR) and logging data such as the significant differences in color, composition, and oil content between carbonate rocks and other lithologies. The depth is mainly determined by logging curves. The range determined by logging and cuttings logging is relatively large, and can be directly determined based on logging curves (GR). When the lithology is carbonate rock, the natural gamma (GR) value is low, while for other lithologies such as mudstone, the natural gamma (GR) value is high. Thus, the depth of the target layer can be determined to be 4924-5171m.

[0078] In step 2, reservoir criteria are determined based on rock physical analysis.

[0079] Carbonate rocks differ significantly from other lithologies in well logging curves. However, if there is a large difference in mineral content within the lithology, such as between carbonate rocks and mudstone, the half-amplitude point of the GR well logging curve is generally used to distinguish limestone from other lithologies. A high natural gamma GR value indicates mudstone, while a low natural gamma GR value indicates limestone.

[0080] However, the natural gamma ray GR logging curves in the study area do not fluctuate significantly, making it inappropriate to rely solely on GR for judgment. Therefore, a comprehensive judgment can be made using density (DEN) curves and acoustic transit time (AC) curves. When the lithology is carbonate rock, GR values ​​are low, while DEN (2.4-2.7 g / cm3) and AC (165-250 μs / ft) values ​​are high, at depths of 4924-5004 m and 5061-5133 m, respectively. Meanwhile, in argillaceous limestone, the depth is 5005-5060 m, with low GR values ​​and relatively low density, approximately 2.5 g / cm3.

[0081] In step 3, an improved Gardner formula is given in the carbonate reservoirs of the well blocks in the conjugate basins of the study area, using velocity and density.

[0082] The Gardner formula is typically used to fit density using acoustic velocity when density data is lacking. However, the classic Gardner formula exhibits certain errors when applied to different blocks. Therefore, this patent employs an improved Gardner formula to calculate the density curve of carbonate reservoirs. The improved Gardner formula is as follows:

[0083] DEN = 0.305 * Vel^(0.25)

[0084] Where: DEN is density, g / cm³ 3 Vel represents the speed of sound, in m / s.

[0085] In step 4, for other lithofacies reservoirs, taking a well in conjugate basin A of the study area as an example, in the argillaceous limestone at a depth of 5005-5060m, the calculation using the improved Gardner formula in step 3 has certain errors. Therefore, it is urgent to eliminate the density error calculated by the improved Gardner formula due to lithology and obtain a new density curve.

[0086] Studies have shown that the improved Gardner formula performs well and has high accuracy in carbonate rock lithology. However, for other lithofacies such as argillaceous limestone, the accuracy of the formula is greatly reduced due to the influence of lithology. To improve accuracy, the measured density of the target layer of argillaceous limestone and the density calculated by the improved Gardner formula are correlated and fitted to obtain a relationship, as shown in the following formula:

[0087] DEN Improved Gardner = 0.71 * DEN Actual Measurement + 0.66.

[0088] In step 5, the conversion from seismic stacking velocity to layer velocity model is achieved through the Dix formula. Since the D basin in the study area is in the early stage of exploration and there is no drilling data, the seismic interpretation can only be completed in the depth domain. It is impossible to calculate the synthetic seismic record or extract the wavelet, which does not meet the requirements of the seismic absolute wave impedance inversion operation under conventional conditions. Therefore, the role of seismic velocity (layer velocity) in this area is fully utilized.

[0089] (1) Using existing seismic velocities in Basin D, depth-domain seismic data and layer interpretation data are converted to the time domain, and the velocity volume is converted back and forth between the time and depth domains. The conversion from seismic stacking velocity to layer velocity model is achieved using the Dix formula.

[0090] (2) Then, frequency information of the seismic data is obtained through spectrum analysis, which is used for setting the wavelet frequency in the later stage.

[0091] (3) Calculate the pseudo-well density curve and density volume using the improved Gardner formula mentioned in steps 3 and 4. Multiply the layer velocity volume calculated by the seismic calculation to obtain the wave impedance volume as the initial model for inversion. Use the pseudo-well to extract and scale the wavelet to make a synthetic seismic record. Compare it with the actual seismic trace. After the QC seismic velocity and the calculated density are qualified, use the seismic data converted to the time domain, interpret the layers, extract the seismic wavelet and the initial wave impedance model volume to achieve the final well-free wave impedance inversion calculation through a series of inversion parameters optimization.

[0092] In step 6, favorable reservoirs are identified in well-free blocks through well-free inversion. The wave impedance obtained from seismic inversion is used for judgment; a high wave impedance value indicates a favorable reservoir. For example... Figure 3 Taking Block D of the study area as an example, in seismic analysis without well constraints, the comparison between seismic profiles and inversion profiles shows a relatively good consistency, reflecting a good inversion effect with a wave impedance greater than 12000 g / cm. 3 At a speed of m / s, it is a favorable reservoir.

[0093] Example 3

[0094] Based on the carbonate reservoir identification methods of Embodiments 1 and 2 described above, this invention provides a computer-readable storage medium. This storage medium stores a computer program, which is executed to run a method for identifying carbonate reservoirs in well-free work areas. The computer program is capable of executing computer instructions, which include computer program code. The computer program code can be in the form of source code, object code, executable files, or some intermediate form.

[0095] Computer-readable storage media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0096] It should be noted that the contents of computer-readable storage media may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, the contents may be appropriately increased or decreased according to the requirements of legislation and patent practice. In other jurisdictions, computer-readable storage media may not include electrical carrier signals and telecommunication signals.

[0097] Example 4

[0098] Based on the carbonate reservoir identification methods described in Embodiments 1 to 3 above, this invention also provides a system for identifying carbonate reservoirs in well-free work areas (also referred to as a "carbonate reservoir identification system"). This carbonate reservoir identification system is used to implement the above-described carbonate reservoir identification methods.

[0099] Figure 4 This is a block diagram of a system module for identifying carbonate reservoirs in wellless work areas, as described in an embodiment of this application. Figure 4 As shown, the carbonate reservoir identification system described in this embodiment of the invention includes: a target layer identification module 41, a velocity-density relationship model generation module 42, a layer velocity-volume conversion module 43, a wave impedance inversion module 44, and a carbonate reservoir identification module 45.

[0100] Specifically, the target layer identification module 41 is implemented according to the method described in step S110 above, and is configured to determine the target layer based on the well logging and seismic data of the conjugate basin of the basin where the wellless work area is located; the velocity-density relationship model generation module 42 is implemented according to the method described in step S120 above, and is configured to establish a model characterizing the relationship between acoustic velocity and density based on the acoustic velocity and density of the well-drilled work area in the conjugate basin; the layer velocity volume conversion module 43 is implemented according to the method described in step S130 above, and is configured to obtain the layer velocity volume based on the depth domain seismic velocity of the wellless work area; the acoustic impedance inversion module 44 is implemented according to the method described in step S140 above, and is configured to establish the pseudo-well density curve and density volume of the wellless work area using the acoustic velocity-density relationship model, and based on this, perform acoustic impedance inversion calculation of the wellless work area using the layer velocity volume; the carbonate reservoir identification module 45 is implemented according to the method described in step S150 above, and is configured to identify favorable carbonate reservoirs in the target layer based on the acoustic impedance volume of the wellless work area.

[0101] In one embodiment, the carbonate reservoir identification module 45 is further configured to identify data points in the impedance volume whose impedance values ​​exceed a preset threshold as favorable carbonate locations, thereby forming favorable carbonate reservoirs based on all favorable carbonate locations.

[0102] This invention discloses a method and system for identifying carbonate reservoirs in well-free exploration areas. This method and system are designed for study areas in the early stages of exploration where drilling data is unavailable and conventional seismic logging interpretation is not feasible. It directly utilizes conjugate basin logging information as constrained seismic velocities to perform well-free inversion for carbonate reservoir identification. This effectively solves technical challenges such as the inability to obtain logging response characteristics, calculate synthetic seismic records, extract wavelets, and perform seismic absolute impedance inversion under unconventional conditions when drilling logging data is unavailable. The method is highly practical and reliable.

[0103] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0104] In the description of this invention, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0105] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0106] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0107] The phrase "an embodiment" or "an embodiment" used in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" or "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0108] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for identifying a non-well-worked carbonate reservoir, characterized in that, include: Based on well logging and seismic data from the conjugate basins of the basin where the wellless work area is located, the target interval is determined. Based on the acoustic velocity and density of well-drilled areas in conjugate basins, a model characterizing the relationship between acoustic velocity and density is established. Based on the depth-domain seismic velocity of the well-free work area, the layer velocity volume is obtained; Using the acoustic velocity-density relationship model, a pseudo-well density curve and density volume of the wellless work area are established, and based on this, the wave impedance inversion calculation of the wellless work area is performed using the layer velocity volume. Based on the acoustic impedance of the well-free work area, favorable carbonate reservoirs in the target section are identified. The steps in establishing a model representing the relationship between sound wave velocity and density include: The relationship between acoustic velocity and density data obtained from logging the first target well in the carbonate reservoir in the well-operated area was fitted to obtain the initial relationship between acoustic velocity and density. A second target well with both carbonate rock and mudstone lithology is selected in the well-existing work area. Using the initial relationship between acoustic velocity and density, the acoustic velocity data of the second target well is converted into density data, which is recorded as the density data for calculation. The calculated density data and measured density data of the second target well are fitted to obtain the density optimization formula for eliminating the influence of lithology; The sound wave velocity and density relationship model is formed by using the initial relationship between sound wave velocity and density and the optimized relationship between density.

2. The method of claim 1, wherein, The step of obtaining the layer velocity volume based on the depth-domain seismic velocity of the well-free work area includes: Transform the seismic velocity and stratigraphic interpretation data of the wellless work area in the depth domain to the time domain; Based on seismic velocity data in the time domain, the root mean square calculation method is used to obtain the layer velocity volume.

3. The method of claim 2, wherein, The steps of establishing a pseudo-well density curve and density volume for the wellless work area using a model of acoustic velocity and density relationship, and then performing wave impedance inversion calculation for the wellless work area based on this layer velocity volume, include: Based on the acoustic velocity in the un-well working area, the pseudo-well density curve and density volume are obtained using the acoustic velocity-density relationship model. The pseudo-well density curve and density volume are multiplied simultaneously with the layer velocity volume to obtain the initial inversion model; Based on the seismic interpretation data of the wellless work area and the pseudo-well density curve, a synthetic seismic record of the wellless work area is produced by extracting the proportional wavelet; Based on the seismic velocity data in the time domain, the layer interpretation data in the time domain, the synthetic seismic record, and the initial inversion model, the wave impedance inversion calculation of the wellless work area is carried out to obtain the wave impedance volume of the wellless work area.

4. The method of claim 3, wherein, The steps of establishing the pseudo-well density curve and density volume of the wellless work area using the acoustic velocity-density relationship model, and then performing wave impedance inversion calculation of the wellless work area based on the layer velocity volume, also include: The synthetic seismic record was verified, including: By comparing the degree of agreement between the current synthetic seismic record and the actual seismic traces and pseudo-well density in the wellless work area, it can be determined whether the current synthetic seismic record is qualified, so as to use qualified synthetic seismic records to carry out wave impedance volume inversion.

5. The method according to any one of claims 1 to 4, characterized in that, The steps for determining the target interval based on well logging and seismic data from the conjugate basin of the basin where the wellless work area is located include: Based on the natural gamma value of the conjugate basin of the basin where the wellless work area is located, the preliminary depth of the target layer is determined by analyzing the lithology, fluid composition and oil content at different depths. The initial depth of the target layer is optimized and adjusted based on the density value and sonic transit time value of the conjugate basin to obtain the final depth of the target layer segment.

6. The method of any one of claims 1-4, wherein, The step of identifying favorable carbonate reservoirs in the target section based on the impedance volume of a well-free work area includes: Data points in the impedance volume whose impedance values ​​exceed a preset threshold are taken as favorable locations of carbonate rocks, thereby forming favorable carbonate rock reservoirs based on all favorable locations of carbonate rocks.

7. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 6.

8. A system for identifying a well-free carbonate reservoir, the system comprising: include: The target layer identification module is configured to determine the target layer based on well logging and seismic data from the conjugate basin of the basin where the wellless work area is located. The velocity-density relationship model generation module is configured to establish a model characterizing the relationship between sound wave velocity and density based on the sound wave velocity and density of the well-drilled area in the conjugate basin. The layer velocity volume conversion module is configured to obtain the layer velocity volume based on the depth domain seismic velocity of the wellless work area; The wave impedance inversion module is configured to use the acoustic velocity and density relationship model to establish the pseudo-well density curve and density volume of the wellless work area, and based on this, use the layer velocity volume to perform wave impedance inversion calculation of the wellless work area. A carbonate reservoir identification module, configured to identify favorable carbonate reservoirs in the target section based on the impedance volume of a well-free work area, wherein... The velocity density relationship model generation module is also configured to: The relationship between acoustic velocity and density data obtained from logging the first target well in the carbonate reservoir in the well-operated area was fitted to obtain the initial relationship between acoustic velocity and density. A second target well with both carbonate rock and mudstone lithology is selected in the well-existing work area. Using the initial relationship between acoustic velocity and density, the acoustic velocity data of the second target well is converted into density data, which is recorded as the density data for calculation. The calculated density data and measured density data of the second target well are fitted to obtain the density optimization formula for eliminating the influence of lithology; The sound wave velocity and density relationship model is formed by using the initial relationship between sound wave velocity and density and the optimized relationship between density.

9. The system according to claim 8, characterized in that, The carbonate reservoir identification module is further configured to identify data points in the impedance volume whose impedance values ​​exceed a preset threshold as favorable locations of carbonate rocks, thereby forming favorable carbonate reservoirs based on all favorable locations of carbonate rocks.

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