Method for judging real favorable reservoir of super-thick bioclastic limestone reservoir

Abstract

The application discloses a method for judging a real favorable reservoir of a super-thick bioclastic limestone reservoir, and the method comprises the following steps: based on core granularity, seismic data and gamma logging curves, the reservoir is divided into multiple third-order sequences, and a favorable development layer section in the reservoir is determined in each third-order sequence; based on rock structure and rock particle types in the favorable development layer section, a favorable sedimentary facies is determined in the favorable development layer section; based on dissolution strength and cementation strength of the favorable sedimentary facies, a favorable diagenetic facies is determined in the favorable sedimentary facies; based on pore throat structure, pore throat types and pore types of the favorable diagenetic facies, a favorable rock physical facies is determined in the favorable diagenetic facies; based on deep lateral resistivity curves of production wells of the reservoir, a theoretical favorable reservoir is determined in the favorable rock physical facies; and based on production logging data, whether the theoretical favorable reservoir is a real favorable reservoir is judged. The technical scheme provided by the application can improve the accuracy of real favorable reservoir judgment.

Description

Technical Field

[0001] This application belongs to the technical field of reservoir research in thick bioclastic limestone reservoirs, and particularly relates to a method for determining the true favorable reservoirs in thick bioclastic limestone reservoirs. Background Technology

[0002] The massive bioclastic limestone reservoirs have complex geological origins and exhibit strong heterogeneity, meaning that the lithology and microstructure of the rocks within the reservoirs are complex. Furthermore, the porosity and permeability of the rocks in these reservoirs show a low correlation; permeability can vary by one to four orders of magnitude depending on the porosity of rocks in different regions. Therefore, current technologies have limited accuracy in characterizing the favorable oil and gas-bearing reservoirs within these massive bioclastic limestone reservoirs, making it difficult to provide sufficient data support for subsequent development. Improving the accuracy of identifying the true favorable reservoirs within these massive bioclastic limestone reservoirs is an urgent technical problem to be solved. Summary of the Invention

[0003] The embodiments of this application provide a method for identifying the true favorable reservoirs in thick bioclastic limestone reservoirs, thereby improving the accuracy of identifying true interlayers.

[0004] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0005] According to a first aspect of the embodiments of this application, a method for determining the true favorable reservoir in a thick bioclastic limestone oil reservoir is provided. The method comprises: acquiring core grain size and seismic data of the oil reservoir, as well as gamma-ray logging curves of the oil reservoir's production wells; dividing the oil reservoir into multiple third-order sequences based on the core grain size, the seismic data, and the gamma-ray logging curves; determining favorable development intervals in the oil reservoir within each third-order sequence; determining favorable sedimentary facies within the favorable development intervals based on the rock structure and rock grain type; determining favorable diagenetic facies within the favorable sedimentary facies based on the dissolution and cementation intensity of the favorable sedimentary facies; determining favorable petrophysical facies within the favorable diagenetic facies based on the pore-throat structure, pore-throat type, and pore type of the favorable diagenetic facies; determining theoretically favorable reservoirs within the favorable petrophysical facies based on the deep lateral resistivity curves of the oil reservoir's production wells; acquiring production logging data of the oil reservoir's production wells; and determining whether the theoretically favorable reservoir is a true favorable reservoir based on the production logging data.

[0006] In some embodiments of this application, based on the aforementioned scheme, the step of dividing the reservoir into multiple third-order sequences based on the core grain size, the seismic data, and the gamma-ray logging curve, and determining favorable development intervals in the reservoir within each third-order sequence, includes: determining key interfaces in the reservoir based on the seismic data, and dividing the reservoir into multiple third-order sequences according to the key interfaces; determining the interval with the smallest core grain size and the highest gamma-ray logging curve in each third-order sequence as the maximum flooding surface of each third-order sequence; dividing each third-order sequence into transgressive semi-cyclic intervals and regressive semi-cyclic intervals according to the location of the corresponding maximum flooding surface, and designating the regressive semi-cyclic intervals as favorable development intervals.

[0007] In some embodiments of this application, based on the foregoing scheme, the key interface includes at least an unconformity, a leaching and dissolution surface, a sedimentary facies abrupt change surface, and a carbonaceous mudstone layer.

[0008] In some embodiments of this application, based on the foregoing scheme, determining the favorable sedimentary facies in the favorable development strata based on the rock structure and rock grain type in the favorable development strata includes: obtaining the grain content and grain size of the rocks in the favorable development strata, and determining the rock structure based on the grain content and grain size; when the grain size is less than or equal to 2 mm, if the grain content is less than 10%, the rock structure is a micritic structure; if the grain content is greater than or equal to 10% and less than 50%, the rock structure is a grain-mud structure; if the grain content is greater than or equal to 50% and less than 90%, the rock structure is a mud-grain structure; and if the grain content is greater than or equal to 90%, the rock structure is a grain-grain structure. Structure; if the particle size is greater than 2 mm, and the particle content is greater than or equal to 10% and less than 50%, the rock structure is a floating structure; if the particle content is greater than or equal to 50%, the rock structure is a clastic structure; obtain the rock particle type in the favorable development interval, the rock particle type includes at least biological shell fragments of clams, bivalves, benthic foraminifera, algae, echinoderms, gastropods, sponges, corals and ostracods, as well as spheroids, sand particles and internal fragments; the rock structure is mudstone structure, granular structure, and clastic structure, and the rock particle type is a favorable development interval dominated by one or more of clams, corals, bivalves, echinoderms, spheroids and sand particles, as a favorable sedimentary facies.

[0009] In some embodiments of this application, based on the foregoing scheme, determining the favorable diagenetic facies within the favorable sedimentary facies based on the dissolution intensity and cementation intensity of the favorable sedimentary facies includes: obtaining a first rock sample of the favorable sedimentary facies, and determining the dissolution intensity and cementation intensity of the first rock sample based on the cement content of the first rock sample; if the cement content is less than 10%, the dissolution intensity of the first rock sample is considered strong dissolution; if the cement content is greater than or equal to 10% and less than 30%, the dissolution intensity and cementation intensity of the first rock sample are considered strong dissolution. For a rock sample exhibiting strong dissolution and weak cementation, if the cement content is greater than or equal to 30% and less than 50%, the dissolution and cementation intensity of the first rock sample is considered moderate dissolution-moderate cementation. If the cement content is greater than or equal to 50% and less than 90%, the dissolution and cementation intensity of the first rock sample is considered weak dissolution-strong cementation. If the cement content is greater than or equal to 90%, the cementation intensity of the first rock sample is considered strong cementation. The favorable sedimentary facies corresponding to the first rock sample exhibiting strong dissolution and the first rock sample exhibiting strong dissolution-weak cementation are respectively regarded as favorable diagenetic facies.

[0010] In some embodiments of this application, based on the foregoing scheme, determining the favorable petrophysical phase in the favorable diagenetic facies based on the pore throat structure, pore throat type, and pore type of the favorable diagenetic facies includes: obtaining a second rock sample of the favorable diagenetic facies; performing mercury intrusion porosimetry on the second rock sample to determine the pore throat structure and pore throat particle size of the second rock sample, wherein the pore throat structure includes at least single-mode, dual-mode, and multi-mode pore throats; determining the pore throat type based on the size of the pore throat particle size; if the pore throat particle size is less than 0.075 μm, the pore throat type is nano-throat; if the pore throat particle size is greater than or equal to 0.075 μm and less than 0.5 μm, the pore throat type is micro-throat; if the pore throat particle size is greater than or equal to 0.075 μm and less than 0.5 μm, the pore throat type is micro-throat. If the pore size is between 0.5 μm and 2.5 μm, the pore throat type is medium throat; if the pore throat particle size is greater than or equal to 2.5 μm and less than 10 μm, the pore throat type is large throat; if the pore throat particle size is greater than or equal to 10 μm, the pore throat type is giant throat. The second rock sample is prepared into a cast thin section, and the cast thin section is identified to determine the pore type of the second rock sample. The pore type includes at least intergranular pores, intergranular dissolution pores, casting pores, cavity pores, intragranular pores, micropores, intercrystalline pores, and fractures. The favorable diagenetic facies corresponding to the second rock sample with pore types of intergranular pores and intergranular dissolution pores, pore throat structure of bimodal or multimodal, and pore throat types of large throat and giant throat are taken as favorable petrophysical facies.

[0011] In some embodiments of this application, based on the foregoing scheme, determining the theoretically favorable reservoir in the favorable petrophysical phase based on the deep lateral resistivity curve of the oil reservoir production well includes: determining the resistivity of the favorable petrophysical phase based on the deep lateral resistivity curve; if the resistivity is greater than a preset resistivity threshold, then the favorable petrophysical phase is regarded as a theoretically favorable reservoir.

[0012] In some embodiments of this application, based on the foregoing scheme, determining whether the theoretically favorable reservoir is a truly favorable reservoir based on the production logging data includes: determining the daily production of the theoretically favorable reservoir per unit length, the cumulative production of the theoretically favorable reservoir, and the total production of the reservoir production well based on the production logging data; if the reservoir production well includes only one perforated section and the daily production is greater than a preset daily production, then the theoretically favorable reservoir is determined to be a truly favorable reservoir; if the reservoir production well includes multiple perforated sections and the ratio of the cumulative production to the total production is greater than a preset ratio, then the theoretically favorable reservoir is determined to be a truly favorable reservoir.

[0013] In some embodiments of this application, based on the foregoing scheme, the preset ratio is 80%.

[0014] In some embodiments of this application, based on the foregoing scheme, the method further includes: determining characteristic seismic data of the true favorable reservoir based on the seismic data; and determining the distribution of the true favorable reservoir in the oil reservoir based on the characteristic seismic data.

[0015] Based on the technical solution proposed in this application, a multi-level and multi-angle analysis and screening method is adopted for the reservoir to gain a deeper understanding of its characteristics. First, the reservoir is divided into multiple third-order sequence layers using core grain size, seismic data, and gamma-ray logging curves. This allows for a comprehensive understanding of the reservoir's macroscopic geological characteristics, identifying favorable development intervals and providing a basis for subsequent screening and analysis. Second, favorable sedimentary facies are identified by analyzing the rock structure and grain type within these favorable development intervals, taking into account the influence of the sedimentary environment on favorable reservoir layers. Finally, the intensity of dissolution and cementation in the rocks of these favorable sedimentary facies is analyzed. The process involves several steps: first, determining favorable diagenetic facies; second, narrowing the distribution range of favorable reservoirs through diagenesis; third, identifying favorable petrophysical facies through pore-throat structure, pore-throat type, and pore type; and fourth, evaluating the reservoir properties of rocks through these factors, which effectively improves the accuracy of identifying truly favorable reservoirs. Finally, using deep lateral resistivity curves to determine theoretically favorable reservoirs, the likelihood of oil and gas content in these theoretically favorable reservoirs can be preliminarily assessed. Finally, production logging data is used to verify whether the theoretically favorable reservoirs are truly favorable reservoirs. Combining theoretical evaluation results with actual production performance effectively improves the accuracy of identifying truly favorable reservoirs.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0018] Figure 1 A flowchart illustrating a method for determining the true favorable reservoir in a thick bioclastic limestone reservoir according to one embodiment of this application is shown.

[0019] Figure 2 This illustration shows a schematic diagram of the third-order sequence stratigraphy of a thick bioclastic limestone reservoir in one embodiment of this application;

[0020] Figure 3 A schematic diagram of a favorable depositional phase is shown in one embodiment of this application;

[0021] Figure 4 This invention provides a schematic diagram illustrating the bonding strength and dissolution strength in one embodiment of the present application.

[0022] Figure 5 A schematic diagram of the pore throat type of a favorable diagenetic facies is shown in one embodiment of this application;

[0023] Figure 6 A resistivity diagram of a theoretically advantageous reservoir in one embodiment of this application is shown;

[0024] Figure 7 This illustration shows a schematic diagram of the actual favorable reservoir distribution in a thick bioclastic limestone reservoir according to one embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0027] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0028] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0029] It should also be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.

[0030] To enable those skilled in the art to better understand this application, a brief description of the thick bioclastic limestone reservoir proposed in this application will be given first.

[0031] Thick bioclastic limestone reservoirs have complex geological origins and exhibit strong heterogeneity, meaning the rock types and microstructures within the reservoirs are complex. Furthermore, the porosity and permeability of the rocks in these reservoirs show a low correlation; permeability can vary by one to four orders of magnitude depending on the porosity of rocks in different regions. Therefore, current technologies have limited accuracy in characterizing favorable oil and gas-bearing reservoirs within these thick bioclastic limestone reservoirs, making it difficult to provide sufficient data support for subsequent development. Based on this, the inventors of this application propose a method for identifying truly favorable reservoirs in thick bioclastic limestone reservoirs. This method can be used to determine favorable oil and gas-bearing reservoirs within these reservoirs, thereby improving the accuracy of identifying truly favorable reservoirs.

[0032] Next, we will combine Figure 1 This application elaborates in detail on the method for identifying the true favorable reservoirs in thick bioclastic limestone reservoirs.

[0033] See Figure 1 This document illustrates a flowchart of a method for determining the true favorable reservoir in a thick bioclastic limestone reservoir according to one embodiment of this application. The method can be executed by a device with computational processing capabilities, such as... Figure 1 As shown, the method may include at least steps 110 to 160:

[0034] Step 110: Obtain the core grain size and seismic data of the reservoir, as well as the gamma logging curves of the reservoir's production wells. Based on the core grain size, the seismic data, and the gamma logging curves, divide the reservoir into multiple third-order sequences, and determine the favorable development intervals in the reservoir within each third-order sequence.

[0035] Step 120: Based on the rock structure and rock grain type in the favorable development interval, determine the favorable sedimentary facies in the favorable development interval.

[0036] Step 130: Based on the dissolution intensity and cementation intensity of the favorable sedimentary facies, determine the favorable diagenetic facies within the favorable sedimentary facies.

[0037] Step 140: Based on the pore throat structure, pore throat type and pore type of the favorable diagenetic facies, determine the favorable petrophysical phase in the favorable diagenetic facies.

[0038] Step 150: Based on the deep lateral resistivity curve of the oil reservoir production well, determine the theoretically favorable reservoir in the favorable petrophysical phase.

[0039] Step 160: Obtain production logging data from the production well of the reservoir, and based on the production logging data, determine whether the theoretically favorable reservoir is a real favorable reservoir.

[0040] In this application, a multi-level, multi-angle analysis and screening method is employed to gain a deeper understanding of the reservoir's characteristics. First, the reservoir is divided into multiple third-order sequence layers using core grain size analysis, seismic data, and gamma-ray logging curves. This allows for a comprehensive understanding of the reservoir's macroscopic geological features, identifying favorable developmental strata and providing a foundation for subsequent screening and analysis. Second, favorable sedimentary facies are determined by analyzing the rock structure and grain type within these favorable strata, taking into account the influence of the sedimentary environment on favorable reservoir formations. Finally, the intensity of dissolution and cementation in the rocks of these favorable sedimentary facies is analyzed to determine... First, favorable diagenetic facies are identified, and the distribution range of favorable reservoirs is further narrowed through diagenesis. Next, favorable petrophysical facies are determined through pore-throat structure, pore-throat type, and pore type. The reservoir performance of rocks is evaluated through pore-throat structure, pore-throat type, and pore type, which can effectively improve the accuracy of identifying true favorable reservoirs. Then, theoretical favorable reservoirs are determined using deep lateral resistivity curves, which can preliminarily determine the possibility of oil and gas in the theoretical favorable reservoirs. Finally, production logging data is used to verify whether the theoretical favorable reservoirs are true favorable reservoirs. Combining theoretical evaluation results with actual production performance can effectively improve the accuracy of identifying true favorable reservoirs.

[0041] In this application, a multi-step process for screening favorable reservoirs in the reservoir can effectively address the complexity and heterogeneity of thick bioclastic limestone reservoirs. Furthermore, each screening step considers reservoir characteristics at different scales and angles, thereby enabling a comprehensive assessment of reservoir quality and further improving the accuracy of identifying truly favorable reservoirs.

[0042] In step 110 above, the reservoir is divided into multiple third-order sequences based on the core grain size, seismic data, and gamma logging curves, and favorable development intervals in the reservoir are determined within each third-order sequence. Specifically, this can be performed according to steps 111 to 113 below:

[0043] Step 111: Based on the seismic data, determine the key interfaces in the reservoir, and divide the reservoir into multiple third-order sequences according to the key interfaces.

[0044] Step 112: In each third-order sequence, determine the segment with the smallest core grain size and the highest gamma logging curve as the maximum flooding surface of each third-order sequence.

[0045] Step 113: Each third-order sequence is divided into transgressive semi-cycle segments and regressive semi-cycle segments according to the location of the corresponding maximum flooding surface, and the regressive semi-cycle segments are regarded as favorable development segments.

[0046] In this application, the key interfaces include at least unconformities, leaching and dissolution surfaces, sedimentary facies abrupt change surfaces, and carbonaceous mudstone layers. Depending on actual needs, other types of rock layer interfaces may also be included, and this application does not make specific limitations on them.

[0047] In this application, the transgressive semi-cycle segment is the segment below the highest flooding surface in each third-order sequence, and the regressive semi-cycle segment is the segment above the highest flooding surface in each third-order sequence.

[0048] In this application, key interfaces in the reservoir are first determined based on seismic data, and the reservoir is divided into multiple third-order sequence layers, specifically, as follows: Figure 2 The diagram illustrates a third-order sequence stratigraphy of a thick bioclastic limestone reservoir according to one embodiment of this application. The key interfaces reflect changes in the reservoir's sedimentary environment and are crucial for third-order sequence stratigraphy. By identifying these key interfaces and considering the changing sedimentary environment, the accuracy of the third-order sequence stratigraphy can be improved, allowing for a more detailed depiction of the reservoir's internal structure and sedimentary characteristics, thus enhancing the accuracy of identifying the true favorable reservoir. Secondly, the maximum flooding surface is determined using two parameters: the minimum core grain size and the highest gamma-ray logging curve. This fully considers the formation of the maximum flooding surface, thereby improving the accuracy of its identification. Finally, the semi-regression cycle is considered a favorable development zone because during marine regression, sediments tend to form layers with good porosity and permeability, making them more likely to develop into favorable reservoirs. Therefore, the above methods effectively improve the accuracy of identifying the true favorable reservoir.

[0049] In step 120 above, determining favorable sedimentary facies in the favorable development zone based on the rock structure and rock grain type can be specifically performed according to steps 121 to 125 as follows:

[0050] Step 121: Obtain the particle content and particle size of the rock in the favorable development zone, and determine the rock structure based on the particle content and particle size.

[0051] Step 122: If the particle size is less than or equal to 2 mm, and the particle content is less than 10%, the rock structure is a micritic structure; if the particle content is greater than or equal to 10% and less than 50%, the rock structure is a granular mud structure; if the particle content is greater than or equal to 50% and less than 90%, the rock structure is a mud-granular structure; and if the particle content is greater than or equal to 90%, the rock structure is a granular structure.

[0052] Step 123: If the particle size is greater than 2 mm, and the particle content is greater than or equal to 10% and less than 50%, then the rock structure is a floating structure; if the particle content is greater than or equal to 50%, then the rock structure is a gravel structure.

[0053] Step 124: Obtain the rock grain type in the favorable development zone. The rock grain type includes at least biological shell fragments of thick-shelled clams, bivalves, benthic foraminifera, algae, echinoderms, gastropods, sponges, corals, and ostracods, as well as spheroids, sand fragments, and internal fragments.

[0054] Step 125: The rock structure is classified as mudstone structure, grain structure, and gravel structure, and the rock grain type is a favorable developmental layer dominated by one or more of the following: thick-shelled clams, corals, bivalves, echinoderms, spheroids, and sand grains, which is regarded as a favorable sedimentary facies.

[0055] In this application, by analyzing the rock structure and grain type of the rocks in the favorable development zone, sedimentary facies that may contain oil and gas in the favorable development zone can be effectively identified, i.e., favorable sedimentary facies. For details, please refer to... Figure 3 This illustration shows a schematic diagram of favorable sedimentary facies in one embodiment of this application. By considering multiple factors such as rock grain content, grain size, and grain type, the accuracy of identifying favorable reservoirs can be improved. Furthermore, specific criteria for identifying favorable sedimentary facies are proposed, defining favorable sedimentary facies as rock structures of mudstone, grain, and clastic texture, and rock grain types dominated by one or more of the following: thick-shelled clams, corals, bivalves, echinoderms, spheroids, and sand grains. By comprehensively considering rock structure and rock grain type, favorable sedimentary facies with good reservoir space and permeability can be accurately identified, thereby improving the accuracy of identifying true favorable reservoirs.

[0056] In step 130 above, determining the favorable diagenetic facies within the favorable sedimentary facies based on the intensity of dissolution and cementation can be specifically performed according to steps 131 to 133 as follows:

[0057] Step 131: Obtain a first rock sample of the favorable sedimentary facies, and determine the dissolution intensity and cementation intensity of the first rock sample based on the cement content of the first rock sample.

[0058] Step 132: If the cement content is less than 10%, the dissolution intensity of the first rock sample is strong dissolution; if the cement content is greater than or equal to 10% and less than 30%, the dissolution intensity and cementation intensity of the first rock sample are strong dissolution-weak cementation; if the cement content is greater than or equal to 30% and less than 50%, the dissolution intensity and cementation intensity of the first rock sample are moderate dissolution-moderate cementation; if the cement content is greater than or equal to 50% and less than 90%, the dissolution intensity and cementation intensity of the first rock sample are weak dissolution-strong cementation; if the cement content is greater than or equal to 90%, the cementation intensity of the first rock sample is strong cementation.

[0059] Step 133: The favorable sedimentary facies corresponding to the strongly dissolved first rock sample and the strongly dissolved-weakly cemented first rock sample are respectively taken as favorable diagenetic facies.

[0060] In this application, the favorable sedimentary facies corresponding to the first rock sample with strong dissolution and the first rock sample with strong dissolution and weak cementation are identified as favorable diagenetic facies. The reason is that strong dissolution means that the rock has undergone strong dissolution, which can form more dissolution pores, which is conducive to improving the porosity and permeability of the rock and making it easier to develop into a favorable reservoir. On the other hand, the rock with strong dissolution and weak cementation indicates that the rock has undergone strong dissolution but has not been filled with too much cement, which can retain more pores, thus making the rock have good porosity and permeability.

[0061] In this application, the intensity of dissolution and cementation of the first rock sample are classified according to the different ranges of cement content. Specifically, for example... Figure 4 The diagram illustrates the cementation and dissolution strength in one embodiment of this application. This allows for a more comprehensive analysis of the porosity and permeability in the favorable sedimentary facies, thereby enabling the identification of favorable diagenetic facies with good porosity and permeability, and ultimately improving the accuracy of the identification of the true favorable reservoir.

[0062] In step 140 above, determining the favorable petrophysical phase within the favorable diagenetic facies based on the pore throat structure, pore throat type, and pore type can be specifically performed according to steps 141 to 144 below:

[0063] Step 141: Obtain a second rock sample of the favorable diagenetic facies, perform mercury intrusion porosimetry on the second rock sample, and determine the pore throat structure and pore throat grain size of the second rock sample. The pore throat structure includes at least single-mode, dual-mode and multi-mode.

[0064] Step 142: Determine the pore throat type based on the size of the pore throat particle. If the pore throat particle size is less than 0.075 μm, the pore throat type is nano-throat. If the pore throat particle size is greater than or equal to 0.075 μm and less than 0.5 μm, the pore throat type is micro-throat. If the pore throat particle size is greater than or equal to 0.5 μm and less than 2.5 μm, the pore throat type is medium-throat. If the pore throat particle size is greater than or equal to 2.5 μm and less than 10 μm, the pore throat type is large-throat. If the pore throat particle size is greater than or equal to 10 μm, the pore throat type is giant-throat.

[0065] Step 143: Prepare the second rock sample into a cast thin section and identify the cast thin section to determine the pore type of the second rock sample. The pore type includes at least intergranular pores, intergranular dissolution pores, casting pores, cavity pores, intragranular pores, micropores, intercrystalline pores, and cracks.

[0066] Step 144: The favorable diagenetic facies corresponding to the second rock sample with pore types of intergranular pores and intergranular dissolution pores, pore throat structures of bimodal or multimodal, and pore throat types of large throats and giant throats are taken as favorable petrophysical facies.

[0067] In this application, by conducting mercury intrusion porosimetry on the second rock sample to determine its pore throat structure and pore throat particle size, the accuracy of permeability assessment of the second rock sample can be improved. By determining the size of the pore throat particle size, different pore throat types can be identified, allowing for a more accurate depiction of the microstructure of the second rock sample. Furthermore, based on different pore throat types, the impact of the pore throat type on oil and gas storage and flow can be determined. In addition, by determining the pore type of the second rock sample through cast thin sections, the accuracy of identifying favorable rock physical phases with good oil and gas storage capacity can be effectively improved, thereby enhancing the accuracy of identifying true favorable reservoirs in thick bioclastic limestone reservoirs.

[0068] In this application, by comprehensively considering multiple microstructural features (pore type, pore throat structure, and pore throat type), specifically, such as... Figure 5 The diagram shows a schematic of the pore throat type of a favorable diagenetic facies in one embodiment of this application. This can effectively identify rock strata with good oil and gas storage capacity and good oil and gas flow properties in the favorable diagenetic facies, thereby improving the accuracy of judging the true favorable reservoirs in thick bioclastic limestone reservoirs.

[0069] In step 150 above, the determination of theoretically favorable reservoirs in the favorable petrophysical facies based on the deep lateral resistivity curve of the oil reservoir production well can be specifically performed according to steps 151 to 152 as follows:

[0070] Step 151: Determine the resistivity of the favorable rock physical phase based on the deep lateral resistivity curve.

[0071] Step 152: If the resistivity is greater than a preset resistivity threshold, then the favorable rock physical phase is regarded as a theoretically favorable reservoir.

[0072] In this application, the preset resistivity threshold can specifically be 100 Ω·m. Depending on actual needs, the preset resistivity threshold can also be 80 Ω·m or 120 Ω·m. This application does not make any specific limitation on this.

[0073] In this application, in favorable reservoirs rich in oil and gas, the resistivity of the favorable reservoir is also relatively high due to the poor electrical conductivity of the oil and gas. Therefore, the theoretical favorable reservoir in the favorable petrophysical phase can be determined by measuring the deep lateral resistivity curve. Specifically, for example... Figure 6 As shown, a resistivity diagram of a theoretically favorable reservoir is illustrated in one embodiment of this application. By incorporating the resistivity parameter, the accuracy of determining favorable reservoirs in the oil reservoir can be effectively improved.

[0074] In step 160 above, determining whether the theoretically favorable reservoir is a truly favorable reservoir based on the production logging data can be performed according to steps 161 to 163 as follows:

[0075] Step 161: Based on the production logging data, determine the daily production of the theoretically favorable reservoir per unit length, the cumulative production of the theoretically favorable reservoir, and the total production of the reservoir production wells.

[0076] Step 162: If the oil reservoir production well includes only one perforated section and the daily production is greater than the preset daily production, then the theoretically favorable reservoir is determined to be a real favorable reservoir.

[0077] Step 163: If the oil reservoir production well includes multiple perforated sections, and the ratio of the cumulative production to the total production is greater than a preset ratio, then the theoretically favorable reservoir is determined to be a real favorable reservoir.

[0078] In this application, the preset ratio can specifically be 80%, and the preset daily output can specifically be 200 barrels / day. Depending on actual needs, the preset daily output and the preset ratio can also be other parameters, and this application does not make specific limitations on them.

[0079] In this application, the daily production of the theoretically favorable reservoir per unit length, the cumulative production of the theoretically favorable reservoir, and the total production of the reservoir's production wells are determined using production logging data. Based on the daily production, the cumulative production, and the total production, it is determined whether the theoretically favorable reservoir is a truly favorable reservoir. The advantage is that verifying the theoretically favorable reservoir using actual production data can improve the accuracy of the verification results, i.e., improve the accuracy of the judgment of truly favorable reservoirs. In addition, different judgment criteria are established according to the different number of perforations in the reservoir's production wells, which can further improve the accuracy of the verification results, thereby improving the accuracy of the judgment of truly favorable reservoirs.

[0080] In the method for determining the true favorable reservoir of a thick bioclastic limestone reservoir proposed in this application, the method may further perform the following steps 170 to 180:

[0081] Step 170: Based on the seismic data, determine the characteristic seismic data of the true favorable reservoir.

[0082] Step 180: Based on the characteristic seismic data, determine the distribution of the actual favorable reservoir in the oil reservoir.

[0083] In this application, by acquiring seismic data of the reservoir and determining characteristic seismic data of the actual favorable reservoir based on the seismic data, the actual favorable reservoir can be correlated with the characteristic data in the seismic data to obtain characteristic seismic data. Therefore, based on the characteristic seismic data, the distribution of actual favorable reservoirs in non-oil well areas of the reservoir can be determined. Specifically, as shown below... Figure 7 The diagram illustrates the distribution of actual favorable reservoirs in a thick bioclastic limestone reservoir according to one embodiment of this application. This expands the scope of the judgment of the actual favorable reservoirs and provides more comprehensive and accurate information support for reservoir development.

[0084] Based on the technical solution proposed in this application, a multi-level and multi-angle analysis and screening method is adopted for the reservoir to gain a deeper understanding of its characteristics. First, the reservoir is divided into multiple third-order sequence layers using core grain size, seismic data, and gamma-ray logging curves. This allows for a comprehensive understanding of the reservoir's macroscopic geological characteristics, identifying favorable development intervals and providing a basis for subsequent screening and analysis. Second, favorable sedimentary facies are identified by analyzing the rock structure and grain type within these favorable development intervals, taking into account the influence of the sedimentary environment on favorable reservoir layers. Finally, the intensity of dissolution and cementation in the rocks of these favorable sedimentary facies is analyzed. The process involves several steps: first, determining favorable diagenetic facies; second, narrowing the distribution range of favorable reservoirs through diagenesis; third, identifying favorable petrophysical facies through pore-throat structure, pore-throat type, and pore type; and fourth, evaluating the reservoir properties of rocks through these factors, which effectively improves the accuracy of identifying truly favorable reservoirs. Finally, using deep lateral resistivity curves to determine theoretically favorable reservoirs, the likelihood of oil and gas content in these theoretically favorable reservoirs can be preliminarily assessed. Finally, production logging data is used to verify whether the theoretically favorable reservoirs are truly favorable reservoirs. Combining theoretical evaluation results with actual production performance effectively improves the accuracy of identifying truly favorable reservoirs.

[0085] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining the true favorable reservoir in a thick bioclastic limestone oil reservoir, characterized in that, The method includes: The core grain size and seismic data of the reservoir, as well as the gamma logging curves of the reservoir's production wells, are obtained. Based on the core grain size, the seismic data, and the gamma logging curves, the reservoir is divided into multiple third-order sequences, and favorable development intervals in the reservoir are determined in each third-order sequence. Based on the rock structure and rock grain type in the favorable development zone, favorable sedimentary facies are determined in the favorable development zone; Based on the intensity of dissolution and cementation of the favorable sedimentary facies, favorable diagenetic facies are determined within the favorable sedimentary facies; Based on the pore-throat structure, pore-throat type, and pore type of the favorable diagenetic facies, the favorable petrophysical facies are determined within the favorable diagenetic facies; Based on the deep lateral resistivity curves of the oil reservoir production wells, theoretically favorable reservoirs are determined in the favorable petrophysical phases. Obtain production logging data from the production wells in the reservoir, and based on the production logging data, determine whether the theoretically favorable reservoir is a real favorable reservoir.

2. The method according to claim 1, characterized in that, Based on the core grain size, the seismic data, and the gamma-ray logging curves, the reservoir is divided into multiple third-order sequences, and favorable development intervals are identified within each third-order sequence, including: Based on the seismic data, key interfaces in the reservoir are identified, and the reservoir is divided into multiple third-order sequences according to the key interfaces. In each third-order sequence, the section with the smallest core grain size and the highest gamma logging curve is determined as the maximum flooding surface of each third-order sequence. Each third-order sequence is divided into transgressive semi-cycle segments and regressive semi-cycle segments according to the location of the corresponding maximum flooding surface, and the regressive semi-cycle segments are regarded as favorable development segments.

3. The method according to claim 2, characterized in that, The key interfaces include at least unconformities, leaching and dissolution surfaces, sedimentary facies abrupt change surfaces, and carbonaceous mudstone layers.

4. The method according to claim 1, characterized in that, The determination of favorable sedimentary facies within the favorable development interval based on the rock structure and grain type includes: The particle content and particle size of the rocks in the favorable development strata are obtained, and the rock structure is determined based on the particle content and particle size. When the particle size is less than or equal to 2 mm, if the particle content is less than 10%, the rock structure is a micritic structure; if the particle content is greater than or equal to 10% and less than 50%, the rock structure is a granular mud structure; if the particle content is greater than or equal to 50% and less than 90%, the rock structure is a mud-granular structure; and if the particle content is greater than or equal to 90%, the rock structure is a granular structure. If the particle size is greater than 2 mm, and the particle content is greater than or equal to 10% and less than 50%, the rock structure is a floating structure; if the particle content is greater than or equal to 50%, the rock structure is a gravel structure. Obtain the rock grain types in the favorable development zone, wherein the rock grain types include at least biological shell fragments of thick-shelled clams, bivalves, benthic foraminifera, algae, echinoderms, gastropods, sponges, corals and ostracods, as well as spheroids, sand fragments and internal fragments. The rock structure is classified as mudstone structure, grain structure, and gravel structure, and the rock grain type is a favorable development interval dominated by one or more of the following: thick-shelled clams, corals, bivalves, echinoderms, spheroids, and sand particles, which is considered a favorable sedimentary facies.

5. The method according to claim 1, characterized in that, The determination of favorable diagenetic facies within the favorable sedimentary facies based on the intensity of dissolution and cementation includes: A first rock sample of the favorable sedimentary facies was obtained, and the dissolution intensity and cementation intensity of the first rock sample were determined based on the cement content of the first rock sample. If the cement content is less than 10%, the dissolution intensity of the first rock sample is strong dissolution; if the cement content is greater than or equal to 10% and less than 30%, the dissolution intensity and cementation intensity of the first rock sample are strong dissolution-weak cementation; if the cement content is greater than or equal to 30% and less than 50%, the dissolution intensity and cementation intensity of the first rock sample are moderate dissolution-moderate cementation; if the cement content is greater than or equal to 50% and less than 90%, the dissolution intensity and cementation intensity of the first rock sample are weak dissolution-strong cementation; if the cement content is greater than or equal to 90%, the cementation intensity of the first rock sample is strong cementation. The favorable sedimentary facies corresponding to the first rock sample with strong dissolution and the first rock sample with strong dissolution and weak cementation are respectively regarded as favorable diagenetic facies.

6. The method according to claim 1, characterized in that, The determination of favorable petrophysical phases within the favorable diagenetic facies based on the pore-throat structure, pore-throat type, and pore type includes: A second rock sample of the favorable diagenetic facies was obtained, and a mercury intrusion porosimetry experiment was performed on the second rock sample to determine the pore throat structure and pore throat grain size of the second rock sample. The pore throat structure includes at least single-mode, dual-mode and multi-mode. The pore throat type is determined based on the size of the pore throat particle. If the pore throat particle size is less than 0.075 μm, the pore throat type is nano-throat; if the pore throat particle size is greater than or equal to 0.075 μm and less than 0.5 μm, the pore throat type is micro-throat; if the pore throat particle size is greater than or equal to 0.5 μm and less than 2.5 μm, the pore throat type is medium-throat; if the pore throat particle size is greater than or equal to 2.5 μm and less than 10 μm, the pore throat type is large-throat; and if the pore throat particle size is greater than or equal to 10 μm, the pore throat type is giant-throat. The second rock sample was prepared into a cast thin section, and the cast thin section was identified to determine the pore type of the second rock sample. The pore type includes at least intergranular pores, intergranular dissolution pores, casting pores, cavity pores, intragranular pores, micropores, intergranular pores, and cracks. The favorable diagenetic facies corresponding to the second rock sample with pore types of intergranular pores and intergranular dissolution pores, pore throat structures of bimodal or multimodal, and pore throat types of large throat and giant throat are regarded as favorable petrophysical facies.

7. The method according to claim 1, characterized in that, The determination of theoretically favorable reservoirs in the favorable petrophysical facies based on the deep lateral resistivity curves of the oil reservoir production wells includes: Based on the deep lateral resistivity curve, the resistivity of the favorable rock physical phase is determined; If the resistivity is greater than a preset resistivity threshold, then the favorable rock physical phase is considered a theoretically favorable reservoir.

8. The method according to claim 1, characterized in that, The step of determining whether the theoretically favorable reservoir is a truly favorable reservoir based on the production logging data includes: Based on the production logging data, the daily production of the theoretically favorable reservoir per unit length, the cumulative production of the theoretically favorable reservoir, and the total production of the reservoir's production wells are determined. If the oil reservoir production well includes only one perforated section and the daily production is greater than the preset daily production, then the theoretically favorable reservoir is determined to be a real favorable reservoir. If the oil reservoir production well includes multiple perforated sections, and the ratio of the cumulative production to the total production is greater than a preset ratio, then the theoretically favorable reservoir is determined to be a real favorable reservoir.

9. The method according to claim 8, characterized in that, The preset ratio is 80%.

10. The method according to claim 8, characterized in that, The method further includes: Based on the aforementioned seismic data, the characteristic seismic data of the actual favorable reservoir are determined; Based on the aforementioned characteristic seismic data, the distribution of the actual favorable reservoirs in the oil reservoir is determined.

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