CN111610126B - Method and system for identifying and evaluating anti-compaction effect of dolomite reservoir pores - Google Patents

Method and system for identifying and evaluating anti-compaction effect of dolomite reservoir pores Download PDF

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CN111610126B
CN111610126B CN202010355627.4A CN202010355627A CN111610126B CN 111610126 B CN111610126 B CN 111610126B CN 202010355627 A CN202010355627 A CN 202010355627A CN 111610126 B CN111610126 B CN 111610126B
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佘敏
沈安江
蒋义敏
吕玉珍
陈薇
王莹
胡圆圆
韦东晓
王永生
李娴静
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Petrochina Co Ltd
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Abstract

The invention discloses a method and a system for identifying and evaluating a dolomite reservoir pore anti-compaction effect, wherein the method comprises the following steps: setting a pressure parameter in the simulated mechanical compaction; respectively preparing the selected dolomite sample into a plunger sample, a microscope slice and a powder sample; analyzing the porosity and the permeability of the plunger sample; performing X-ray diffraction analysis on the powder sample; analyzing the microscope slice sample by using a microscope; carrying out lithologic naming on the dolomite sample; performing CT scanning on the plunger sample; performing mechanical compaction simulation on the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure actions; obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, the porosity and the permeability under different pressures of the dolomite sample; quantitatively evaluating the compression resistance effect of the dolomite in the mechanical compaction process.

Description

Method and system for identifying and evaluating anti-compaction effect of dolomite reservoir pores
Technical Field
The invention relates to the field of petroleum geological analysis, in particular to a method and a system for identifying and evaluating the anti-compaction effect of dolomite reservoir pores.
Background
According to the statistics of C & C company on 342 carbonate oil and gas fields in the world, in 46 carbonate oil and gas fields with burial depth of more than 4500m or times earlier than the aspiration period, except 4 carbonate oil and gas fields with limestone as reservoir layers, the rest all use the dolomite as reservoir layers.
In recent years, china has made a breakthrough in oil and gas exploration in marine carbonate rocks, and particularly, a number of large (oil) gas fields, such as the Mixi-Gaoshita gas field in the Sichuan basin, the Tarim basin and the river gas field, the Su-Li-Ge gas field in the Eldos basin, the ultra-large plain gas field in the Sichuan basin, and the like, are found in the dolomite reservoir. Exploration practices show that the deep carbonate rock can still develop a good solution pore (cave) -type reservoir under specific conditions, and mainly contains dolomite. However, finding the dolomite does not mean finding a reservoir, and the understanding of the cause and the storage rule of the dolomite reservoir is very important for obtaining a greater breakthrough of oil and gas exploration in a carbonate rock development area of more than 300 square kilometers in China.
According to the research on the formation cause of the dolomite reservoir, the pores are mainly inherited to the existing pores, and the corrosion modification under the condition of low temperature near the earth surface is very important, but after long-term deep-buried compaction, the thickness of the dolomite is reduced, the porosity and the permeability are reduced, so that the pore in any type of dolomite can be stored, how to identify the type of the dolomite with higher compaction resistance, and how to quantitatively evaluate the compaction resistance efficiency are the research focus of the current deep dolomite oil-gas exploration.
At present, in the prior art, research work of tight sandstone diagenesis physical simulation under the constraint of geological process has been carried out by relying on a sandstone compaction effect simulation device (patent number: ZL 201120530914.0) and an analysis method (ZL 201310076357.3) of sandstone diagenesis process and pore evolution; specifically, a sandstone particle sample is subjected to compaction and cementation simulation, and a simulation product is subjected to slice and scanning electron microscope analysis to obtain physical parameters such as micro-zone pore content, pore diameter, throat diameter and the like.
Similar to the sandstone compaction simulation method, zboku reported in 1995 a compaction simulation of limestone powder particles (particle size less than 120 mesh) confirming the presence of mechanical compaction during the carbonate burial phase. Because the sample adopts particles, the compaction simulation method is relatively suitable for sandstone mainly comprising inter-granular pores, and the types of pores in the dolomite sample are complex and various and comprise inter-granular pores, intra-granular (solution) pores, intra-granular pores, solution pores (holes), cast mold pores, cracks and the like, and the actual dolomite pore characteristics can be represented only by adopting the rock sample. In addition, the particle sample compaction method cannot carry out rock porosity and permeability evolution quantitative analysis, and cannot realize quantitative evaluation of compression resistance effect of dolomite.
At present, the dolomite compaction analysis method is mainly characterized in that whether compaction exists or not and the strength of the compaction is qualitatively deduced according to the contact relation and the deformation degree of particles in rocks through core slice microscope analysis, but the dolomite anti-compaction effects of different pore types cannot be quantitatively analyzed. In addition, a carbonate rock compaction analysis method is also provided, which collects core plunger samples from shallow to deep buried strata, measures the porosity and permeability parameters of the samples, establishes a carbonate rock-depth relation curve, and carries out quantitative research on the compaction characteristics of carbonate rocks in a basin of south florida in 1982 by Schpoker, so that the qualitative understanding that dolomite is more compaction-resistant than limestone and is beneficial to pore preservation is obtained, and the exploration practice that a deep carbonate rock reservoir mostly takes dolomite as a main part is proved to a certain extent, but the exploration practice that the type of dolomite is more compaction-resistant still cannot be answered.
Therefore, a technical scheme for providing anti-compaction identification and evaluation for dolomite with different pore types in the process of buried diagenesis is needed.
Disclosure of Invention
In order to overcome the technical problems, the invention provides a method and a system for identifying and evaluating the compaction resistance effect of the dolomite reservoir pores, which can be used for identifying and evaluating the compaction resistance of dolomite samples with different pore types in the process of the buried diagenesis, and the method and the system can realize the simulation of the process of the buried mechanical compaction on the dolomite samples with different pore types and quantitatively calculate the porosity and permeability storage rate of the dolomite samples, thereby identifying the compaction resistance effect of the dolomite samples with corresponding pore types; based on the method and the system, the control effect of the pore type on compaction resistance in the dolomite reservoir formation process and the corresponding mechanism problem can be solved, the pore type and lithology conditions beneficial to the storage of the dolomite reservoir pores are finally determined, and an analysis basis is provided for large-scale and efficient dolomite reservoir distribution and prediction.
In an embodiment of the invention, a method for identifying and evaluating a dolomite reservoir pore anti-compaction effect is provided, and the method comprises the following steps:
acquiring a pressure background parameter of a dolomite reservoir research area according to the geological background of the research area, and setting a pressure parameter in a simulated mechanical compaction action according to the background parameter;
selecting a dolomite sample according to a target layer of a research area, and respectively preparing the selected dolomite sample into a plunger sample, a microscope slice and a powder sample;
analyzing the porosity and the permeability of the plunger sample to obtain the initial porosity and the initial permeability of the dolomite sample;
performing X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample;
analyzing the microscope slice sample by using a microscope to determine the pore type and the particle type of the dolomite sample;
according to the mineral components, the component content and the particle types of the dolomite sample, carrying out lithologic naming on the dolomite sample;
performing CT scanning on the plunger sample to obtain three-dimensional space distribution characteristics of the pore structure in the dolomite sample;
performing mechanical compaction simulation on the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure effects;
obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under different pressures of the dolomite sample;
and quantitatively evaluating the compression resistance actual effect of the dolomite in the mechanical compaction process according to the lithology named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
In another embodiment of the present invention, a system for identifying and evaluating the anti-compaction effect of dolomite reservoir pores is further provided, the system comprising:
the pressure parameter setting module is used for acquiring a pressure background parameter of a research area of the dolomite reservoir according to the geological background of the research area and setting a pressure parameter in the simulated mechanical compaction action according to the background parameter;
the dolostone sample preparation device is used for selecting a dolostone sample according to a target layer of a research area, and respectively preparing the selected dolostone sample into a plunger sample, a microscope slice and a powder sample;
the porosity and permeability analysis device is used for analyzing the porosity and permeability of the plunger sample to obtain the initial porosity and the initial permeability of the dolomite sample;
the X-ray diffraction analysis device is used for carrying out X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample;
the microscope is used for analyzing the microscope slice sample and determining the pore type and the particle type of the dolomite sample;
the lithology naming module is used for conducting lithology naming on the dolomite samples according to the mineral components, the component contents and the particle types of the dolomite samples;
the CT scanning device is used for carrying out CT scanning on the plunger sample to obtain the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample;
the mechanical compaction simulation device is used for simulating the mechanical compaction action of the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure actions;
the storage rate calculation module is used for obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under different pressures of the dolomite sample;
and the quantitative evaluation module is used for quantitatively evaluating the compression resistance effect of the dolomite in the mechanical compaction process according to the lithology-named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
In another embodiment of the present invention, a computer device is further provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the computer program implements a method for identifying and evaluating a dolomite reservoir pore anti-compaction effect.
In another embodiment of the present invention, a computer-readable storage medium is further proposed, which stores a computer program, which when executed by a processor, implements a method for identifying and evaluating a dolostone reservoir pore anti-compaction effect.
By utilizing the method and the system for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores, provided by the invention, the anti-compaction of the dolomite of different pore types in the process of the buried diagenesis can be identified and evaluated, and compared with the prior art, the method and the system have at least the following effects:
1. the identification of the pore and structural components of the dolomite sample is emphasized, the anti-compaction differences of different types of dolomite are further refined, and the identification of the rock types in the dolomite reservoir, which are more favorable for pore storage, is facilitated.
2. The sample adopts a dolostone plunger sample, and can fully represent the actual texture and pore characteristics of the dolostone in the nature.
3. A dolomite compression resistance effect calculation formula is established, and the dolomite compression resistance effect is quantitatively evaluated;
4. by utilizing the compaction effect simulation under the geological process constraint, the simulation experiment condition is more in line with the geological reality, and the obtained compression resistance effect evaluation result of the dolomite in the mechanical compaction process is more accurate.
5. The method effectively solves the control effect of the pore type on compaction resistance in the dolomite reservoir formation process and the corresponding mechanism problem, defines the pore type and lithology conditions beneficial to dolomite reservoir pore preservation, provides analysis basis for scale and high-efficiency dolomite reservoir distribution and prediction, and has higher practicability, reliability and scientificity compared with the prior art.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for identifying and evaluating a dolomite reservoir pore anti-compaction effect according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of the pressure-depth distribution in the middle of a river according to an embodiment of the present invention.
Fig. 3A to 3H are slice views of the cast body of each dolomite sample according to an embodiment of the present invention.
Fig. 4A to 4H are CT images of respective dolomitic rock samples according to an embodiment of the present invention.
FIG. 5 is a graph illustrating porosity retention data versus effective stress according to an embodiment of the present invention.
FIG. 6 is a graph illustrating permeability retention data versus effective stress according to an embodiment of the present invention.
Fig. 7 is a schematic diagram of a system architecture for identifying and evaluating the anti-compaction effect of the dolomite reservoir pore space according to an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The principles and spirit of the present invention will be described with reference to a number of exemplary embodiments. It is understood that these embodiments are given only to enable those skilled in the art to better understand and to implement the present invention, and do not limit the scope of the present invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
One skilled in the art will appreciate that embodiments of the present invention can be implemented as a system, apparatus, device, or method. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
According to the embodiment of the invention, the method and the system for identifying and evaluating the anti-compaction effect of the pore of the dolomite reservoir are provided, and the method and the system mainly comprise four parts of identifying the pore characteristic and the texture characteristic of the dolomite sample, determining the lithology naming of the dolomite sample, carrying out the mechanical compaction simulation of the dolomite sample and quantitatively evaluating the anti-compaction effect of the dolomite sample, and are mainly used for identifying the rock type in the dolomite reservoir, which is more favorable for pore storage, and finally solving the problems of deep dolomite scale and efficient reservoir prediction.
The principles and spirit of the present invention are explained in detail below with reference to several exemplary embodiments of the present invention.
Fig. 1 is a schematic flow chart of a method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pore space according to an embodiment of the invention. As shown in fig. 1, the method includes:
and S101, acquiring a pressure background parameter of the research area of the dolomite reservoir according to the geological background of the research area, and setting a pressure parameter in the simulated mechanical compaction action according to the background parameter.
S102, selecting a dolomite sample according to a target layer of a research area, and respectively preparing the selected dolomite sample into a plunger sample, a microscope slice and a powder sample;
in one embodiment, the plunger sample is a cylinder sample with a diameter of 2cm-3cm and a length of more than 3 cm; in particular, the diameter of the plunger sample may be about 2.5cm. The powder sample was a 100 mesh powder sample.
Step S103, analyzing the porosity and the permeability of the plunger sample to obtain the initial porosity and the initial permeability of the dolomite sample; in this step, the porosity and permeability of the plunger sample can be analyzed by a pore-permeation analyzer.
Step S104, carrying out X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample; wherein the mineral composition of the dolomitic sample comprises at least one or more of:
dolomite, quartz, potassium feldspar, albite, calcite, pyrite, hematite, anhydrite and siderite.
The mineral component and content data of the dolomite sample can provide a basis for the lithology designation of the dolomite.
Step S105, analyzing the microscope slice sample by using a microscope, and determining the pore type and the particle type of the dolomite sample;
here, the dolomite pore classification method may be based on the pore classification method of Choquette and Pray, and the determined pore types of the dolomite sample are mainly: a texture-selective type or a non-texture-selective type; wherein the content of the first and second substances,
the texture selectivity types are: inter-grain holes, intra-grain holes, window lattice holes, shielding holes, lattice frame holes, inter-grain holes and casting mold holes;
the non-fabric selectivity types are: cracks, pores, cavities, or combinations thereof.
The particle type is mainly used for providing a basis for lithology nomenclature.
Step S106, carrying out lithologic naming on the dolomite sample according to the mineral components, the component content and the particle type of the dolomite sample;
in one embodiment, dolomite sheet identification and lithology nomenclature can utilize the Folk classification method, based primarily on four major particle types and the relative abundance of particles (catabolic particles), matrix, and cement or pores;
specifically, the lithology of the dolomite sample may be named according to the mineral component whose component content is greater than a set threshold and the type of the particle with the highest content in the dolomite sample, for example, sandy dolomite, oolitic dolomite, and calcite-containing green dolomite (with a high calcite content).
And S107, performing CT scanning on the plunger sample to obtain the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample.
And S108, performing mechanical compaction simulation on the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure effects.
And step S109, obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under the action of different pressures of the dolomite sample.
The specific calculation process is as follows:
calculating the porosity storage rate of the dolomite sample by using the formula (1):
Figure BDA0002473337080000071
wherein phi s For porosity retention,. Phi 0 Is the initial porosity, phi i Porosity under different pressures;
and (3) calculating the permeability storage rate of the dolomite sample by using the formula (2):
Figure BDA0002473337080000072
wherein, K s For permeability retention, K 0 To an initial degree of penetration, K i Permeability under different pressures.
And S110, quantitatively evaluating the compression resistance actual effect of the dolomite in the mechanical compaction process according to the lithology-named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
In the process of step S110, the porosity retention rate and the permeability retention rate of the dolomite sample are evaluated by using a preset compression-resistant implementation evaluation index to obtain evaluation results, such as high compression-resistant implementation, general compression-resistant implementation, poor compression-resistant implementation, and the like; and further, combining the evaluation result with the lithology name, the pore type and the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample to obtain the evaluation result of the anti-compaction effect of the dolomite in the mechanical compaction process.
It should be noted that although the operations of the method of the present invention have been described in the above embodiments and the accompanying drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the operations shown must be performed, to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
For a clearer explanation of the method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores, a specific example is described below, but it should be noted that the example is only for better illustration of the present invention and does not constitute an undue limitation on the present invention.
Taking the Chuanzhong region as an example, a schematic diagram of pressure-depth distribution in the Chuanzhong region is shown in FIG. 2. In the figure, the abscissa is pressure (MPa), and the ordinate is depth (m); t3x is the Huffman river group, T2l is the Leikou slope group, T1j is the Jialin river group, T1f is the Feixian river group, P is the binary system,
Figure BDA0002473337080000081
is the upper system of the frigid-martial system (a field group and a rear dam group),
Figure BDA0002473337080000082
qiongzhuesi group, zdn is a lamp shade group.
The marine carbonate rock occupies an extremely important position in natural gas production in the Sichuan basin, the resource amount of the marine carbonate rock stratum system accounts for 85% of the total amount of the conventional gas resource of the Sichuan basin, and the exploration that the reserve ratio is 70% is a main stratum system for realizing the natural gas benefit exploration and development of the Sichuan basin.
The marine carbonate rocks in the Sichuan basin are widely distributed from the new Yuan ancient boundary seismic-denier system to the middle-life boundary triple-fold system, and after multi-period structural cycle, a plurality of large and medium-sized gas fields with different layer systems and different types are found to be distributed in different areas of the basin. Wherein the content of the first and second substances,
the middle-second overlap system couchcut group is a limestone karst fracture cave reservoir stratum; the two sections and the four sections of the vibroseis series lamp shadow set are dune facies karst cracks-hole type algae dolomite reservoir layers; the lower cold Wushu Longwangmiao group, the mud basin system watching Moshan group, the carbo system Huanglong group, the two-fold system perching Xixia group, the three-fold system Feixian group, the Jialing Jiangjiang group and the Leikoupo group are granular beach pores and hole type dolomite reservoirs; the two-fold system Changxing group is a biological reef-beach dolomite reservoir; the reservoir development and distribution of the layers are mainly controlled by sedimentary facies, and the reservoir development and distribution are further improved by overlapping multi-stage karst and tectonic actions at the later stage, so that the reservoir is the main reservoir type of large and medium-sized gas fields of marine facies carbonate rocks in the Sichuan basin.
The marine carbonate reservoir in the Sichuan basin is mainly characterized by sedimentary facies-controlled dolomite reservoir, but finding dolomite does not mean that the reservoir is found. After long-term deep-buried compaction, the dolomite thickness is reduced, the porosity and the permeability are reduced, and then whether the dolomite porosity can be preserved or not is judged, how to identify the porosity type with better compaction resistance is judged, and how to evaluate the compaction resistance efficiency is also judged.
Therefore, the method provided by the invention can be used for carrying out burying compaction simulation on the dolomite of different pore types in the Sichuan basin, quantitatively calculating the porosity and the permeability compaction resistance of the dolomite sample, judging the compaction resistance effect of the dolomite of the corresponding pore type, and finally determining the pore type and lithologic conditions beneficial to storing the pores of the dolomite reservoir.
According to the method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pore space shown in the figure 1, the specific process is as follows:
referring to step S101:
and acquiring a pressure background parameter of the research area of the dolomite reservoir according to the geological background of the research area, and setting a pressure parameter in the simulated mechanical compaction action according to the background parameter.
In this embodiment, the dolomite samples are taken from the east dui-fold longxing group, the san-fold feixian group and the middle longwanggio group of the sichuan basin, and the stratum pressure background refers to the middle longwanggio group of the sichuan basin (refer to fig. 2) because the pore type control dolomite compression resistance effect is the main analysis content.
In the continuous burial depth process, effective stress borne by the rock framework is correspondingly increased, grains and structures in the rock are rearranged and/or changed, the volume and connectivity of rock pores are correspondingly changed, and the effective stress of the rock stratum is the difference between static rock pressure and pore pressure.
As can be seen from FIG. 2, the static rock pressure coefficient of the rock stratum is 23.7MPa/1000m, the pore pressure adopts hydrostatic pressure, namely 10.0MPa/1000m, and the effective stress and the corresponding burial depth are adopted in the experiment: the effective stress is 3.6MPa (the buried depth is 263 meters), the effective stress is 5.2MPa (the buried depth is 380 meters), the effective stress is 10.3MPa (the buried depth is 1109 meters), the effective stress is 20.3MPa (the buried depth is 1482 meters), the effective stress is 30.5MPa (the buried depth is 2226 meters), the effective stress is 40.3MPa (the buried depth is 2942 meters), and the effective stress is 49.8MPa (the buried depth is 3635 meters).
Referring to step S102:
selecting a dolomite sample according to a target layer of a research area, and respectively preparing the selected dolomite sample into a plunger sample, a microscope slice and a powder sample.
In this example, eight dolomite samples were selected, cylindrical samples having a diameter of 2.5cm and a length of more than 3.0cm were prepared using a core drill and a cutter, and the porosity and permeability of the samples were measured using a pore-permeation measuring instrument after drying (refer to step S103). As shown in table 1, the sampling information of dolomite samples is shown.
One end of the cylindrical sample was sliced with a cutter and prepared into a microscope casting sheet.
Selecting a core drilling machine to drill the residual sample of the cylindrical sample, weighing about 2g, and crushing the sample into a 100-mesh powder sample.
TABLE 1 dolomitic sample sampling information
Figure BDA0002473337080000091
Figure BDA0002473337080000101
Referring to steps S103, S104:
the plunger sample (prepared in step S102) was analyzed using a pore-permeability tool to obtain initial porosity and initial permeability data for the dolomitic sample. The initial porosity and initial permeability data are data obtained without mechanical compaction simulation, and are used in calculating the retention in the subsequent step S109.
Performing X-ray diffraction analysis on the 100-mesh powder sample to obtain mineral component and content data of the dolomite sample, and providing a basis for mineral component and content for the lithologic naming of the dolomite;
the 100-mesh powder sample is subjected to X-ray diffraction analysis, and the mineral components and content data of 8 dolomite sample blocks can be referred to table 2.
According to the analysis result, the content of dolomite in the selected samples exceeds 50 percent, so that 8 samples are all dolomite; wherein, the calcite content of the sample No. 8 exceeds 5 percent and the sample is named as calcite-containing dolostone.
TABLE 2 dolomite sample porosity, permeability and mineral content analysis results
Figure BDA0002473337080000102
Referring to steps S105, S106:
analyzing the microscope slice sample by using a microscope to determine the pore type and the particle type of the dolomite sample; in this embodiment, referring to fig. 3A to 3H, a slice of a casting body of each dolomite sample according to an embodiment of the present invention is shown.
The dolomite pore classification method is a pore classification method according to Choquette and Pray, the pore type being mainly based on a texture-selective type and a non-texture-selective type, wherein,
the structure selectivity comprises grain holes, grain inner holes, window lattice holes, shielding holes, lattice frame holes, grain holes and casting mold holes; non-fabric options include cracks, pores, and vugs.
The particle types of the dolomite sample include sand, oolitic, fine powder and green chips.
Further, according to the mineral components, the component content and the particle types of the dolomite samples, performing lithology naming on the dolomite samples.
The method of dolomite sheet identification and lithology nomenclature is based on the Folk classification, based primarily on four major particle types and the relative abundance of particles (dissimilatory particles), matrix and cement or pores;
in this embodiment, the prepared 8 dolomite sub-samples are subjected to pore feature analysis, and the pore type classification is based on the pore classification method of Choquette and Pray. Wherein, the pore characteristics and lithology named rock names of 8 subdolomite rock samples under a microscope are shown in table 3:
no. 1 sand debris dolostone, the development pore is mainly karst cave and karst fissure;
no. 2 sand-crumbs dolostone, mainly develops karst pores and karst caves;
3, sand-crumbs dolostone develops a small amount of dissolved pores, and the local part but most of the dissolved pores and intergranular pore asphalt are completely filled;
oolitic dolomite No. 4, mainly developed inter-granular pores are formed, and pores are uniformly distributed in a net shape;
oolitic dolomite No. 5, mainly developed inter-granular pores are formed, and pores are uniformly distributed in a net shape;
no. 6 fine powder crystal cloud rock, wherein the pore development is mainly intercrystalline pores;
oolitic 7, which mainly develops intra-granular dissolving pores;
no. 8 contains calcite, instead of dolomite, which is densely cemented and has no pores.
TABLE 3 Dolomite sample lithology nomenclature and pore characteristics
Sample numbering Block times Depth of Horizon Rock name Characteristic of predominant pore
1 1-6/107 4620.76-4620.93 Longwang temple group Dolomite sand Solution seam and solution cavity
2 / 4607.66-4609.94 Longwang temple group Dolomite sand Solution hole and cavity
3 1-13/39 4642.52-4642.62 Longwang temple group Dolomite with sand bits Dissolving pores and cracks
4 3-213 3483.60-3483.72 Feixian Guangyuan group Oolitic dolomite Inter-granular pores
5 2-110 4362.34-4362.42 Changxing group Oolitic dolomite Inter-granular pores
6 8-13/68 6226.70-6226.91 Changxing group Fine powder crystal cloud rock Intercrystalline pores
7 / / Feixian guan group Oolitic dolomite Intra granular dissolving hole
8 / / Changxing group Dolomite containing calcite and crude debris No obvious hole is seen
Referring to step S107:
and carrying out CT scanning on the plunger sample to obtain the three-dimensional space distribution characteristic of the internal pore structure of the dolomite sample.
In this embodiment, CT analysis is performed on 8 prepared dolomite plug samples, which mainly characterizes the internal pores and pore communication characteristics of the rock:
as shown in fig. 4A to 4H, CT images of 8 sub-dolomitic rock samples are shown; wherein the content of the first and second substances,
no. 1 sand debris dolomite development pores mainly adopt a solution joint and a solution cavity, and corrosion peaks penetrating through two ends of a sample play a role in determining sample connectivity;
no. 2 sand debris dolostone develops a karst cave and a karst cave, and the pores are communicated with a main throat and occasionally form micro cracks;
no. 3 sand shavings dolomite develops a small amount of dissolving holes, and cracks communicate with pores;
the developed intercrystalline holes of the No. 4 oolitic dolomite are mainly, the pores are uniformly distributed in a net shape, and the roar is communicated with the intercrystalline holes;
oolitic dolomite 5 development inter-particle holes are mainly formed, pores are uniformly distributed in a net shape, and a roar is communicated with the inter-particle holes;
no. 6 fine powder crystalline cloud rock pore development takes inter-granular pores as the main part, and the roar is communicated with the inter-granular pores;
the developed granular inner solution pores of No. 7 oolitic dolomite are mainly, and no cracks are generated;
no. 8 dolomite containing calcite and crude chips is compactly cemented by calcite, and no pores or cracks are visible.
Step S108:
and performing mechanical compaction simulation on the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure effects.
In the present example, the analysis of the control effect of the pore type on the anti-compaction effect of dolomite is mainly emphasized; in the compaction simulation process, pressure is not applied to carbonate rock pores, but effective stress of a rock stratum is represented by confining pressure, specifically, a rock sample is placed in a rock core holder of a mechanical compaction simulation experiment device, an outlet of the rock sample is communicated with atmosphere, the pressure of an inlet of the rock is kept unchanged in the experiment process, and the net stress borne by the rock is changed by changing the magnitude of the confining pressure. In the experimental process, the overburden stress of the rock sample is increased from zero to small, and the change rule of the overburden stress is searched on the basis.
According to the effective stress obtained in the step S101, a mechanical compaction effect simulation device is used for simulating the corrosion simulation experiment of each sample under the conditions of effective stress of 3.6MPa (buried depth of 263 m), effective stress of 5.2MPa (buried depth of 380 m), effective stress of 10.3MPa (buried depth of 1109 m), effective stress of 20.3MPa (buried depth of 1482 m), effective stress of 30.5MPa (buried depth of 2226 m), effective stress of 40.3MPa (buried depth of 2942 m) and effective stress of 49.8MPa (buried depth of 3635 m) in sequence.
When an experiment is started, putting a dolomite plug sample into a rock core holder of a mechanical compaction simulation experiment device, keeping for 5 minutes after confining pressure reaches a set effective stress, and measuring the porosity and permeability of the rock; and after the measurement, changing the confining pressure to the next set effective stress condition, circulating the steps until the experiment is finished, and measuring the rock porosity and permeability under each effective stress.
Step S109:
and obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, the porosity and the permeability of the dolomite sample under the action of different pressures.
Calculating the porosity storage rate phi of the dolomite sample by using the formula (1) s
Figure BDA0002473337080000131
Wherein phi s For porosity retention,. Phi 0 Is the initial porosity,. Phi i Porosity under different pressures;
calculating by using the formula (2) to obtain the permeability storage rate K of the dolomite sample s
Figure BDA0002473337080000132
Wherein, K s For permeability retention, K 0 To an initial degree of penetration, K i Permeability under different pressures.
The porosity and permeability data and the retention of porosity and permeability under the corresponding effective stress in 8 dolomite sample mechanical compaction experiments in the examples are shown in table 4.
TABLE 4 Calcite sample porosity and permeability data statistics in mechanical compaction simulation
Figure BDA0002473337080000133
Figure BDA0002473337080000141
Figure BDA0002473337080000151
And S110, quantitatively evaluating the compression resistance actual effect of the dolomite in the mechanical compaction process according to the lithology-named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
According to the theory of rock mechanics, the change from one stress state to another necessarily causes compression or tension, i.e. the rock is elastically or plastically deformed, and at the same time, the deformation of the rock necessarily causes changes in the rock structure and pore volume, such as the reduction of the pore volume, the closure of the pore throat and cracks, and the like.
Through the mechanical compaction in step S109, under the effect of effective stress of 3.5MPa to 50MPa, the particles and structures in 8 dolomite samples are rearranged and/or changed, and the volume and connectivity of rock pores are changed correspondingly, as shown in fig. 5 and 6, which are schematic diagrams of the relationship between the porosity and permeability retention data and the effective stress in an embodiment of the present invention. Wherein, the first and the second end of the pipe are connected with each other,
no. 1 arenaceous dolomite, mainly developed crack-cave, has an initial porosity of 63.09% and a permeability reduced to 1.68% under the mechanical compaction action of 50MPa, and still has a permeability of 1036 × 10 -3 μm 2
The No. 2 sand-crumbed dolomite is mainly developed and cave-dissolving type pores, under the mechanical compaction action of 50MPa, the porosity is about 79.96 percent of the initial porosity, and the permeability is further reduced to 50.3 percent of the initial porosity;
the No. 3 sand-crumbled dolomite is mainly developed into a pore-dissolving structure and a crack, under the mechanical compaction action of 50MPa, the porosity is only 64.58% of the initial porosity, and the permeability is further reduced to 6.85% of the initial permeability;
oolitic dolomite No. 4 is mainly formed by interparticle pores, under the mechanical compaction action of 50MPa, the initial porosity is 82.03%, and the initial permeability is more maintained to be 94.62%;
5, oolitic dolomite, which mainly comprises inter-granular pores, has initial porosity of 79.83 percent and permeability of 90.96 percent under the mechanical compaction action of 50 MPa;
no. 6 fine powder crystalline dolomite, mainly takes intercrystalline pores as raw materials, under the mechanical compaction action of 50MPa, the initial porosity is 88.85 percent, and the initial permeability is more maintained to be 94.52 percent;
the No. 7 oolitic dolomite is mainly provided with inner pores, under the mechanical compaction action of 50MPa, the porosity is only 57.35% of the initial porosity, and the permeability is only 10.74% of the initial permeability;
no. 8 dolomite containing calcite green scraps has no obvious pores, and under the mechanical compaction action of 50MPa, the porosity is 61.92 percent of the initial porosity, and the permeability is only 3.96 percent of the initial permeability.
From the analysis results, the porosity and permeability retention rate of the 8-pore type dolomite are obviously different through the simulation of the same mechanical compaction effect, wherein the compression resistance effect of the ' intergranular pore type ' dolomite is the highest as compared with that of the ' intergranular pore type ' dolomite, the compression resistance effect of the ' dissolved pore-dissolved cave type ' dolomite is the second order, and the compression resistance effect of the ' dissolved pore type ' dolomite, the crack type ' dolomite and the ' invisible pore dense type ' dolomite is the worst.
The method for identifying and evaluating the compaction resistance of the dolomite with different pore types in the process of the buried diagenesis can effectively identify and quantitatively evaluate the rock types in the dolomite reservoir layer which are more beneficial to pore preservation, and is beneficial to solving the problems of a pore preservation mechanism and scale pore distribution prediction of the dolomite reservoir layer in the diagenesis period.
Having described the method of an exemplary embodiment of the present invention, a system for identifying and evaluating the effect of dolomite reservoir pore compaction resistance according to an exemplary embodiment of the present invention will now be described with reference to fig. 7.
The implementation of the system for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores can be referred to the implementation of the method, and repeated details are not repeated. The term "module" or "unit" used hereinafter may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Based on the same inventive concept, the invention also provides a system for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores, as shown in fig. 7, the system comprises:
the pressure parameter setting module 701 is used for acquiring a pressure background parameter of a research area of a dolomite reservoir according to a geological background of the research area, and setting a pressure parameter in a simulated mechanical compaction action according to the background parameter;
the device 702 for preparing the dolomite samples is used for selecting the dolomite samples according to the target layers of the research areas and preparing the selected dolomite samples into plunger samples, microscope slices and powder samples respectively;
a porosity and permeability analysis device 703 for performing porosity and permeability analysis on the plunger sample to obtain an initial porosity and initial permeability of the dolostone sample;
the X-ray diffraction analysis device 704 is used for carrying out X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample;
a microscope 705 for analyzing the microscope slide sample to determine the pore type and particle type of the dolomite sample;
a lithology naming module 706, configured to name lithology of the dolomite sample according to the mineral components, the component content, and the particle type of the dolomite sample;
the CT scanning device 707 is used for performing CT scanning on the plunger sample to obtain three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample;
the mechanical compaction simulation device 708 is used for simulating the mechanical compaction action of the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure actions;
a storage rate calculation module 709, configured to obtain a porosity storage rate and a permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under different pressures of the dolomite sample;
and the quantitative evaluation module 710 is used for quantitatively evaluating the compression resistance effect of the dolomite in the mechanical compaction process according to the lithology-named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
In one embodiment, the plunger sample prepared by the dolomite sample preparation device is a cylinder sample with the diameter of 2cm-3cm and the length of more than 3 cm; the powder sample prepared by the dolomite sample preparation device is a 100-mesh powder sample.
In one embodiment, the porosity and permeability analysis device is a pore couple meter.
In one embodiment, the X-ray diffraction analysis device performs X-ray diffraction analysis on the powder sample, and the obtained mineral component of the dolomite sample comprises at least one or more of the following: dolomite, quartz, potassium feldspar, albite, calcite, pyrite, hematite, anhydrite and siderite.
In one embodiment, the microscope analyzes the microscope slide sample, and the determining the pore type of the dolomitic sample comprises: a texture-selective type or a non-texture-selective type; wherein, the first and the second end of the pipe are connected with each other,
the texture selectivity types are: inter-granular holes, intra-granular holes, window lattice holes, shielding holes, lattice holes, inter-granular holes or cast mold holes;
the non-fabric selectivity types are: cracks, pores, cavities, or combinations thereof.
In an embodiment, the lithology naming module 706 is specifically configured to:
and (3) carrying out lithologic naming on the dolomite sample by utilizing a Folk classification method according to the mineral components with the component content larger than a set threshold value and the particle type with the highest content in the dolomite sample.
In an embodiment, the saving rate calculating module 709 is specifically configured to:
calculating the porosity preservation rate of the dolomite sample by using the formula (1):
Figure BDA0002473337080000171
wherein phi is s For porosity retention,. Phi 0 Is the initial porosity,. Phi i Porosity under different pressures;
and (3) calculating the permeability storage rate of the dolomite sample by using the formula (2):
Figure BDA0002473337080000181
wherein, K s For permeability retention, K 0 To initial permeability, K i Permeability under different pressures.
In an embodiment, the quantitative evaluation module 710 is specifically configured to:
and evaluating the porosity storage rate and the permeability storage rate of the dolomite sample by using a preset compression-resistant implementation evaluation index, and combining the evaluation result with the lithologic name, the pore type and the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample to obtain the evaluation result of the anti-compaction effect of the dolomite in the mechanical compaction process.
It should be noted that although several modules of the system for identification and evaluation of dolomitic reservoir pore anti-compaction effects are mentioned in the above detailed description, such partitioning is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module according to embodiments of the invention. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.
Based on the aforementioned inventive concept, as shown in fig. 8, the present invention further provides a computer apparatus 800, which includes a memory 810, a processor 820 and a computer program 830 stored in the memory 810 and executable on the processor 820, wherein the processor 820 executes the computer program 830 to implement the aforementioned method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores.
Based on the same inventive concept, the invention further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores is realized.
The method and the system for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores can identify and evaluate the anti-compaction of the dolomite with different pore types in the buried diagenetic action process, and have at least the following effects compared with the prior art:
1. the identification of the pore and structural components of the dolomite sample is emphasized, the anti-compaction differences of different types of dolomite are further refined, and the identification of the rock types in the dolomite reservoir, which are more favorable for pore storage, is facilitated.
2. The sample adopts a dolostone plunger sample, and can fully represent the actual texture and pore characteristics of the dolostone in the nature.
3. A dolomite compression resistance effect calculation formula is established, and the dolomite compression resistance effect is quantitatively evaluated;
4. by utilizing compaction effect simulation under the constraint of geological process, simulation experiment conditions are more in line with geological reality, and the obtained compression resistance effect evaluation result of the dolomite in the mechanical compaction process is more accurate.
5. The method effectively solves the control effect of the pore type on compaction resistance in the dolomite reservoir formation process and the corresponding mechanism problem, defines the pore type and lithology conditions beneficial to dolomite reservoir pore preservation, provides analysis basis for scale and high-efficiency dolomite reservoir distribution and prediction, and has higher practicability, reliability and scientificity compared with the prior art.
While the spirit and principles of the invention have been described with reference to several particular embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, nor is the division of aspects, which is for convenience only as the features in such aspects may not be combined to benefit. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims (14)

1. A method for identifying and evaluating the compaction resistance effect of dolomite reservoir pores is characterized by comprising the following steps:
acquiring a pressure background parameter of a dolomite reservoir research area according to the geological background of the research area, and setting a pressure parameter in a simulated mechanical compaction action according to the background parameter;
selecting a dolomite sample according to a target layer of a research area, and respectively preparing the selected dolomite sample into a plunger sample, a microscope slice and a powder sample;
analyzing the porosity and the permeability of the plunger sample to obtain the initial porosity and the initial permeability of the dolomite sample;
performing X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample;
analyzing the microscope slice sample by using a microscope to determine the pore type and the particle type of the dolomite sample;
according to the mineral components, the component content and the particle types of the dolomite sample, carrying out lithologic naming on the dolomite sample;
performing CT scanning on the plunger sample to obtain three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample;
performing mechanical compaction simulation on the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure effects;
obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under different pressures of the dolomite sample; wherein the content of the first and second substances,
calculating the porosity preservation rate of the dolomite sample by using the formula (1):
Figure FDA0003853609070000011
wherein phi s For porosity retention,. Phi 0 Is the initial porosity,. Phi i Porosity under different pressures;
and (3) calculating the permeability storage rate of the dolomite sample by using the formula (2):
Figure FDA0003853609070000012
wherein, K s For permeability retention, K 0 To initial permeability, K i Permeability under different pressures;
and quantitatively evaluating the compression resistance actual effect of the dolomite in the mechanical compaction process according to the lithology named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample.
2. The method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores as claimed in claim 1, wherein the porosity and permeability analysis is performed on the plunger sample to obtain the initial porosity and initial permeability of the dolomite sample, comprising:
and analyzing the porosity and the permeability of the plunger sample by using a pore-seepage joint measuring instrument to obtain the initial porosity and the initial permeability of the dolomite sample.
3. A method for identification and evaluation of dolomitic reservoir pore anti-compaction effects according to claim 1, characterized in that the powder sample is subjected to X-ray diffraction analysis, the mineral composition of the obtained dolomitic sample comprising at least one or more of the following: dolomite, quartz, potassium feldspar, albite, calcite, pyrite, hematite, anhydrite and siderite.
4. The method for identifying and evaluating the anti-compaction effect of dolomite reservoir pores as claimed in claim 1, wherein the analysis of the microscope slide sample is carried out using a microscope, and the determined pore type of the dolomite sample is: a texture-selective type or a non-texture-selective type; wherein, the first and the second end of the pipe are connected with each other,
the texture selectivity types are: inter-granular holes, intra-granular holes, window lattice holes, shielding holes, lattice frame holes, inter-granular holes or cast mold holes;
the non-fabric selectivity types are: cracks, pores, cavities, or combinations thereof.
5. The method for identifying and evaluating the anti-compaction effect of the dolomite reservoir pores according to claim 1, wherein the lithologic naming of the dolomite samples according to the mineral components, the component content and the pore types of the dolomite samples comprises:
and (3) carrying out lithologic naming on the dolomite sample by utilizing a Folk classification method according to the mineral components with the component content larger than a set threshold value and the particle type with the highest content in the dolomite sample.
6. The method for identifying and evaluating the dolomite reservoir pore anti-compaction effect according to claim 1, wherein the method for quantitatively evaluating the anti-compaction effect of the dolomite in the mechanical compaction process according to the lithology-named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and permeability storage rate of the dolomite sample comprises the following steps:
and evaluating the porosity storage rate and the permeability storage rate of the dolomite sample by using a preset compression resistance effect evaluation index, and combining the evaluation result with the rock name, the pore type and the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample to obtain the anti-compaction effect evaluation result of the dolomite in the mechanical compaction process.
7. A system for identifying and evaluating the compaction resistance effect of dolomite reservoir pores, which is characterized by comprising:
the pressure parameter setting module is used for acquiring a pressure background parameter of a research area of the dolomite reservoir according to the geological background of the research area and setting a pressure parameter in the simulated mechanical compaction action according to the background parameter;
the dolostone sample preparation device is used for selecting a dolostone sample according to a target layer of a research area and respectively preparing the selected dolostone sample into a plunger sample, a microscope slice and a powder sample;
the porosity and permeability analysis device is used for analyzing the porosity and permeability of the plunger sample to obtain the initial porosity and the initial permeability of the dolomite sample;
the X-ray diffraction analysis device is used for carrying out X-ray diffraction analysis on the powder sample to obtain mineral components and component contents of the dolomite sample;
the microscope is used for analyzing the microscope slice sample and determining the pore type and the particle type of the dolomite sample;
the lithology naming module is used for carrying out lithology naming on the dolomite sample according to the mineral components, the component content and the particle type of the dolomite sample;
the CT scanning device is used for carrying out CT scanning on the plunger sample to obtain the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample;
the mechanical compaction simulation device is used for simulating the mechanical compaction action of the plunger sample according to the pressure parameters to obtain the porosity and permeability of the dolomite sample under different pressure actions;
the storage rate calculation module is used for obtaining the porosity storage rate and the permeability storage rate of the dolomite sample according to the initial porosity, the initial permeability, and the porosity and the permeability under different pressures of the dolomite sample; wherein, the first and the second end of the pipe are connected with each other,
calculating the porosity preservation rate of the dolomite sample by using the formula (1):
Figure FDA0003853609070000031
wherein phi is s For porosity retention,. Phi 0 Is the initial porosity,. Phi i Porosity under different pressures;
calculating by using a formula (2) to obtain the permeability storage rate of the dolomite sample:
Figure FDA0003853609070000032
wherein, K s For permeability retention, K 0 To an initial degree of penetration, K i Permeability under different pressures;
and the quantitative evaluation module is used for quantitatively evaluating the compression resistance effect of the dolomite in the mechanical compaction process according to the lithology named rock name, the pore type, the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample and the porosity storage rate and the permeability storage rate of the dolomite sample.
8. The dolomite reservoir pore anti-compaction effect identification and evaluation system according to claim 7, wherein the porosity and permeability analysis device is a pore-permeability measuring instrument.
9. The dolomite reservoir pore space compaction resistance judging and evaluating system according to claim 7, wherein the X-ray diffraction analysis device performs X-ray diffraction analysis on the powder sample, and the obtained dolomite sample mineral components comprise at least one or more of the following: dolomite, quartz, potassium feldspar, albite, calcite, pyrite, hematite, anhydrite and siderite.
10. The system for identification and evaluation of dolostone reservoir pore anti-compaction effects according to claim 7, wherein the microscope analyzes the microscope sheet sample and determines the pore type of the dolostone sample as: a texture-selective type or a non-texture-selective type; wherein the content of the first and second substances,
the texture selectivity types are: inter-granular holes, intra-granular holes, window lattice holes, shielding holes, lattice holes, inter-granular holes or cast mold holes;
the non-fabric selectivity types are: cracks, pores, cavities, or combinations thereof.
11. The dolomite reservoir pore anti-compaction effect identification and evaluation system according to claim 7, wherein the lithology naming module is specifically configured to:
and (3) carrying out lithology naming on the dolomite sample by utilizing a Folk classification method according to the mineral components with the component content larger than a set threshold value and the particle type with the highest content in the dolomite sample.
12. The dolomite reservoir pore anti-compaction effect identification and evaluation system according to claim 7, wherein the quantitative evaluation module is specifically configured to:
and evaluating the porosity storage rate and the permeability storage rate of the dolomite sample by using a preset compression-resistant implementation evaluation index, and combining the evaluation result with the rock name, the pore type and the three-dimensional space distribution characteristics of the internal pore structure of the dolomite sample to obtain the evaluation result of the anti-compaction effect of the dolomite in the mechanical compaction process.
13. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 6 when executing the computer program.
14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 6.
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