CN108590601B - Experimental method for optimizing water injection expansion construction parameters - Google Patents
Experimental method for optimizing water injection expansion construction parameters Download PDFInfo
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
- E21B43/20—Displacing by water
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/25—Methods for stimulating production
- E21B43/26—Methods for stimulating production by forming crevices or fractures
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
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Abstract
The invention discloses an experimental method for optimizing water injection expansion construction parameters, which comprises the following steps of S1: testing physical property and mechanical property parameters of reservoir rock; s2: preparing and testing an artificial rock sample; s3: preparing an artificial rock sample conforming to a simulated mining scene; s4: reducing the stratum condition of the rock sample; s5: simulation of a rock sample pollution zone and a small expansion test; s6: analyzing the expansion test result and establishing an expansion equation; s7: micro morphological test of fracture surface (micro crack) after expansion; s8: and establishing a loose sandstone reservoir dilatation expansion mathematical model and a numerical model. The invention simulates the stress-strain and permeability change of different stratums under different injection conditions by a method of combining an indoor simulation experiment of stratum conditions with numerical simulation of temperature-seepage-stress coupling. And establishing a mathematical model among injection parameters, rock strain, porosity and permeability, and conveniently, quickly and accurately providing an optimal optimization scheme and a theoretical basis for water injection capacity expansion construction of the loose sandstone.
Description
Technical Field
The invention relates to the field of oil and gas resource development, in particular to an experimental method for optimizing water injection expansion construction parameters.
Technical Field
Oil and gas resources in the world are distributed in sandstone strata by about 70 percent, the strata have wide distribution range on the sea and land in China, the oil reservoir reserves are large, and the yield index plays an important role in oil and gas field development. Sandstone reservoirs have unique geological and physical characteristics, and sand blocking often occurs, so that the permeability near a shaft is reduced, and the yield of an oil well is influenced. Particularly, for offshore sandstone oil reservoirs in China, sand blocking is easy to occur in the exploitation process of most oil wells, the damage to oil and gas wells is great, and the production reduction or production stop operation of the oil wells is caused, even the oil wells are scrapped. Sand plugging has become one of the outstanding problems affecting reservoir productivity.
The water injection dilatation construction is a solution for relieving sand blockage, can achieve the aim of relieving sand silt blockage pollution around a well, and can generate micro cracks near a stratum during water injection dilatation so as to improve the physical properties of a reservoir layer and prevent the pollution of a sand prevention layer, thereby improving the productivity. However, in the prior art, the exploration of the water injection expansion experiment is insufficient, the optimal water injection parameters under different formation conditions cannot be accurately predicted, and the optimization analysis aiming at the determination of the expansion parameters is not available, so that a scientific and practical model and result cannot be obtained to guide the water injection expansion construction.
Disclosure of Invention
In order to solve the above problems, the present invention is implemented by the following technical solutions, and an experimental method for optimizing water injection expansion construction parameters includes the following steps: s1: testing mechanical properties and physical parameters of reservoir rock to obtain a particle size composition distribution curve, porosity, permeability, a stress-strain curve and elastic parameters of the rock; s2: preparing an artificial rock sample which is most consistent with the reservoir rock properties; s3: preparing a plurality of artificial rock samples obtained in S2, dividing the artificial rock samples into a plurality of groups, wherein each group comprises two artificial rock samples, drilling a borehole in the center of the cross section of each artificial rock sample, and putting a simulation casing for simulating an exploitation scene; s4: performing a simulation test of the formation conditions and the pollution zones on the artificial rock sample obtained in the step S3; s5: performing a water injection expansion indoor simulation test on the artificial rock sample obtained in the step S4 to obtain an optimal water injection parameter for expansion; s6: analyzing the result of the simulation test in the water injection expansion chamber and establishing an expansion equation; s7: performing microscopic morphology observation test and analysis on a fracture surface formed after the simulation test in the water injection expansion chamber; s8: and establishing a set of mathematical model according to the rock expansion equation and the fracture surface microscopic morphology observation test analysis result, and using the mathematical model as a theoretical guidance for establishing a numerical model.
Further, the steps specifically include the following:
s1: and (5) testing the mechanical property and physical property parameter of the reservoir rock. And testing the granularity of the rock sample of the target layer to obtain a granularity composition distribution curve. The test measures the porosity and permeability of the rock sample, and the single/triaxial compression strength test and the uniaxial tensile strength test are carried out on the rock sample of the target layer. Analyzing and obtaining elastic parameters (including elastic modulus, Poisson's ratio, compressive strength, residual strength, volume strain, expansion rate, shear expansion angle, internal friction angle, cohesion, shear strength and the like) of the reservoir rock through a stress-strain curve obtained by a test;
s2: and preparing an artificial rock sample which is most consistent with the properties of the reservoir rock. And preparing a plurality of groups of rock samples with different proportions of the quartz sand with various particle sizes according to the particle size composition distribution curve obtained in the S1. And (4) performing test tests on the physical parameters and the mechanical property parameters of the prepared rock sample, including the porosity, the permeability, the stress-strain curve and the elasticity parameters of the rock sample, and comparing the physical parameters and the mechanical property parameters of the reservoir rock measured in S1 respectively. And analyzing to obtain a group of quartz sand particle size ratio conditions which are most consistent with the physical properties of reservoir rocks.
S3: and preparing the artificial rock sample according with the mining scene. And preparing a plurality of groups of rock samples with the same properties by using the optimal particle size ratio of the quartz sand particles determined in the step S2. Drilling a micro borehole in the center of the cross section of the rock sample, putting a simulation casing pipe, and uniformly drilling holes at the bottom of the simulation casing pipe to simulate real stratum perforation holes.
S4: and (3) simulating the stratum condition and the pollution zone of the rock sample. And injecting clear water from the top section of the rock sample, wherein the injection pressure is the pore pressure of the target layer, and keeping the pore pressure until the test is finished. Meanwhile, the formation temperature is set for the rock sample. The rock sample pollution zone simulation is to simulate the condition that two rock samples in each group of four groups of rock samples with the same properties are polluted to different degrees by using silt mixture fluid marked by radioactive isotope tracer.
S5: and carrying out a water injection dilatation expansion indoor simulation test. Respectively carrying out low-flow-rate capacity-expansion indoor simulation test of constant pressure, low-flow-rate capacity-expansion indoor simulation test of constant flow and circulating water pressure capacity-expansion indoor simulation test under different frequencies, and the steps are as follows: s51: performing water injection tests on the simulated borehole of the artificial rock sample obtained in the step S4, wherein the tests are respectively performed under different water injection parameters, and the water injection parameters comprise water injection pressure, water injection flow and water injection frequency; s52: and analyzing the optimal water injection pressure, the optimal water injection flow and the optimal injection-production time ratio according to the stress strain and permeability of the artificial rock sample. And the circulating water pressure expansion indoor simulation test under different frequencies is respectively carried out under the conditions of the optimal water injection pressure and the optimal water injection flow.
S6: and (4) analyzing the expansion and expansion test result and establishing an expansion equation. And continuously recording three types of expansion test results, analyzing the expansion test results, determining the matching relation between water injection parameters and rock stress-strain and permeability, establishing an equation under the expansion condition of rock expansion, and providing basic theoretical guidance for establishing a mathematical model.
S7: and (3) performing a fracture surface (microcrack) microscopic morphology test after expansion, observing the internal structure of the rock sample after the three types of expansion tests and the size of an expansion area after the rock sample tests with different pollution degrees by using a computer-controlled X-ray tomography technology to obtain a series of observation results such as visual description of the form and the position of the microcrack, and comparing and analyzing the test results.
S8: and establishing a water injection expansion mathematical model and a numerical model of the unconsolidated sandstone reservoir. And establishing a set of mathematical model according to a rock expansion equation and a fracture surface micro-morphology observation test analysis result, and using the mathematical model as a theoretical guide for establishing a numerical model. And establishing a temperature-seepage-stress coupled hydraulic expansion numerical model, comparing the test result with the numerical model result, and mutually verifying. And finally, determining hydraulic parameters of different target layers by using the model, and calculating and analyzing by changing water injection parameters to obtain the optimal water injection expansion scheme.
The invention has the advantages that:
(1) the experimental scheme is based on the reduction of real formation conditions: by combining an indoor simulation experiment of stratum conditions with numerical simulation of temperature-seepage-stress coupling, stress-strain and permeability changes of different stratums under different injection conditions are simulated, so that the experimental environment is matched with the actual condition, and the accuracy of the experimental result is ensured;
(2) the experimental scheme adopts a fracture surface observation experiment to verify the established model: establishing a mathematical model among water injection parameters, rock strain, porosity and permeability, searching specific optimal water injection pressure, water injection flow and injection-production time ratio, verifying and optimizing the optimal water injection parameters by adopting an observation experiment of an expansion fracture surface, and further ensuring the accuracy of the model;
(3) the experimental scheme considers the problem of water injection in actual exploitation: the scheme researches the optimal ratio of the injection time to the extraction time under the optimal water injection pressure and the optimal water injection flow, so that the practical situation of the oil field is better met, and the experimental model is more scientific and practical.
In conclusion, the scheme provides the optimal optimization scheme and theoretical basis for water injection capacity expansion construction, and sandstone loosening construction can be performed more conveniently, rapidly and accurately.
Drawings
FIG. 1 is a stress-strain graph in an experiment of the present invention;
FIG. 2 is a schematic diagram of a test core mold in the testing apparatus of the present invention;
FIG. 3 is a model diagram of a phi 100mm X100 mm large rock sample in the test of the present invention;
FIG. 4 is a schematic diagram of a triaxial rock mechanics testing system in the test apparatus of the present invention;
FIG. 5 is a model diagram of silt contamination prior to dilatation in an experiment of the present invention;
FIG. 6 is a graph showing axial stress-strain relationship and core permeability-strain relationship in tests of the present invention;
FIG. 7 is a cross-sectional view of the post-dilation contamination distribution in an experiment of the present invention;
FIG. 8 is a plot of the expanded fracture surface contour in the test of the present invention;
FIG. 9 is a visual depiction of the morphology and location of microcracks in an assay of the invention;
FIGS. 10-11 are graphs respectively representing the degree of particle cementation and pore spacing distribution in the test samples of the present invention;
FIG. 12 is a hydraulic expansion geometric model diagram of a sandstone reservoir built by the invention;
FIG. 13 is a partial screenshot of a model calculation result of the present invention;
FIG. 14 is a graph of porosity as a function of injection time for the results of the experiments of the present invention;
FIG. 15 is a graph showing the variation of effective stress at different angles in the experiment of the present invention;
FIG. 16 is an experimental flow chart of the present invention.
In fig. 2: 21-an upper clamping disc, 22-a core mould body, 23-a lower clamping disc and 24-a core pressing rod;
in fig. 3: 31-simulated casing, 32-simulated borehole; a
In fig. 4: 101-oil storage tank, 102-axial pressure pump, 103-axial pressure control device, 201-air compression pump, 202-air storage tank, 203-constant temperature and constant pressure device, 301-piston, 302-autoclave body, 303-air inlet, 304-air outlet, 305-core holder, 306-self-adhesive sealing tape, 307-first rubber sealing gasket, 308-full diameter core, 309-core middle hole, 310-second rubber sealing gasket, 401-inlet pressure display and sensor, 402-outlet pressure display and sensor, 403-precession vortex gas flowmeter, 404-data acquisition card, 405-data output display, 501-filter, 502-high temperature oven, 503-electronic balance;
in fig. 5: 51-fine silt blocking belt before capacity expansion;
in fig. 6: 61-stress strain curve, 62-permeability strain curve;
in fig. 7: 71-micro cracks, 72-main cracks and 73-expanded fine silt blocking belts;
in fig. 12: p1-Circumferential pore pressure, P2-Overburden pressure.
Detailed Description
An experiment method for optimizing water injection expansion construction parameters comprises the following steps: s1: testing mechanical properties and physical parameters of reservoir rock to obtain a particle size composition distribution curve, porosity, permeability, a stress-strain curve and elastic parameters of the rock; s2: preparing an artificial rock sample which is most consistent with the reservoir rock properties; s3: preparing a plurality of artificial rock samples obtained in S2, dividing the artificial rock samples into a plurality of groups, wherein each group comprises two artificial rock samples, drilling a borehole in the center of the cross section of each artificial rock sample, and putting a simulation casing for simulating an exploitation scene; s4: performing a simulation test of the formation conditions and the pollution zones on the artificial rock sample obtained in the step S3; s5: performing a water injection expansion indoor simulation test on the artificial rock sample obtained in the step S4 to obtain an optimal water injection parameter for expansion; s6: analyzing the result of the simulation test in the water injection expansion chamber and establishing an expansion equation; s7: performing microscopic morphology observation test and analysis on a fracture surface formed after the simulation test in the water injection expansion chamber; s8: and establishing a set of mathematical model according to the rock expansion equation and the fracture surface microscopic morphology observation test analysis result, and using the mathematical model as a theoretical guidance for establishing a numerical model. As shown in fig. 16:
s1: the method comprises the following steps of testing reservoir rock physical property and mechanical property parameters:
s11: and taking out the core of the target layer by using a core drill bit, and processing the core into a plurality of tiny rock samples with the specification of phi 25mm multiplied by 100 mm. It should be noted that the specification of the rock sample only needs to meet the requirements of national standards and experimental equipment, and the invention does not limit the specification of the rock sample.
S12: and (3) processing and grinding the tiny rock sample into a slice with the thickness of about 30 microns, and measuring the long axis dimension of the cross section of each single particle of the two-dimensional slice by using an ultra-long focal length continuous zooming video microscope so as to determine the size of the particle size of the rock sample. And drawing a particle size composition distribution curve, and analyzing and determining the proportion of particles with different particle sizes.
S13: the porosity and permeability of the micro core are measured by using a high-temperature high-pressure rock multi-parameter measuring instrument of the southwest university of petroleum, and the measurement result is recorded by using a computer recorder.
S14: and (3) carrying out a compressive strength test on the micro core, processing the reservoir core of the target block into the micro core with the specification of phi 25mm multiplied by 100mm, and carrying out a test comprising uniaxial compressive strength and triaxial compressive strength under the reservoir temperature pressure condition. And carrying out a compressive strength test on the micro rock core of the target block by adopting an RTR-1000 high-temperature high-pressure triaxial rock mechanical testing system.
S15: and (3) carrying out a tensile strength test on the micro core, processing the target block reservoir core into a flat cylinder with the specification of phi 25mm multiplied by 100mm and two flat ends, and then carrying out a Brazilian disc test on a triaxial testing machine until the sample is damaged.
Through the above two tests of S14 and S15, the stress-strain curve is analyzed, and as shown in fig. 1, rock property parameters such as elastic modulus, poisson' S ratio, compressive strength, residual strength, volume strain, shear expansion angle, internal friction angle, cohesion, shear strength and the like are obtained.
S2: preparing an artificial rock sample most consistent with the reservoir rock property, wherein the specific experimental steps are as follows:
and (5) preparing a rock sample. According to the particle size composition distribution curve obtained in S1, under the condition that the weight ratio of the particles corresponding to each particle diameter interval is not changed, the particle size composition of the particles in each particle size interval is adjusted to form the condition that a plurality of groups of quartz sands with various particle sizes are distributed differently. Then preparing a plurality of groups of rock samples with different proportions of the quartz sand with various granularities. The operation steps for preparing the rock sample are as follows: mixing each group of quartz sand with different proportions, adding a certain amount of aluminum phosphate cementing agent according to the basic proportion of the quartz sand and the cementing agent, uniformly stirring, and then placing into a rock core die with phi 25mm multiplied by 100mm, as shown in figure 2. The material is first compacted manually with a compression bar and then forced at 4.9kN for 5 min. Unloading, taking out the rock sample and drying. After drying, the temperature is raised to 500 ℃ for sintering, and the constant temperature is kept for 8 hours. Finally, stopping the fire, and naturally cooling the furnace.
And (4) determining the particle size ratio of the quartz sand. And testing mechanical property parameters such as porosity, permeability, tensile strength, compressive strength and the like of each group of prepared rock samples in the same manner as S1, and comparing the obtained experimental result with the physical property parameters and the mechanical parameters of the reservoir rock tested in S1. And analyzing to obtain a group of quartz sand preparation rock samples which are most consistent with the physical properties of reservoir rocks, and determining the optimal proportion of quartz sand particles with different particle sizes.
S3: and preparing the artificial rock sample according with the mining scene. And preparing a plurality of groups of rock samples with the same properties by using the optimal particle size ratio of the quartz sand particles determined in the step S2. Drilling a tiny borehole in the center of the cross section of the rock sample, putting a simulation casing pipe, uniformly drilling holes at the bottom of the simulation casing pipe to simulate real stratum perforation holes, and the method comprises the following specific steps:
s31: according to the optimal proportion of the quartz sand with different grain diameters determined by S2, four groups of rock samples with the same ABCD property are prepared by the same method as S2(1), wherein each group comprises two rock samples, and the specifications are phi 100mm multiplied by 100 mm.
S32: drilling a small hole with the diameter of 10mm multiplied by 80mm at the center of the cross section of each group of rock sample, manufacturing a thin-wall steel pipe with the same specification as the small hole to serve as a simulation casing pipe, and drilling a plurality of small hole simulation perforation holes which are uniformly distributed at the bottom of the steel pipe. The simulated casing was rotated into the small simulated borehole, the result being shown in figure 3.
It should be noted that the specification of the rock sample in this step is set according to the improved experimental equipment in this embodiment, as long as the specification meets the requirement of the capacity expansion experimental equipment. The size of the borehole is set according to the ratio of the field well to the reservoir, and no strict standard exists.
S4: the method comprises the following steps of simulating the stratum conditions and the pollution zones of the rock sample:
the four groups of rock samples prepared in S3 were placed in the triaxial cell of the improved triaxial rock mechanics testing system, a schematic diagram of which is shown in fig. 4. And injecting clear water from the top section of the rock sample through a liquid injection system, wherein the injection pressure is the pore pressure of a target reservoir, and the pore pressure is continuously added until the water injection, expansion and expansion test is finished. And simultaneously applying axial pressure and confining pressure to the rock sample so as to realize the saturation of fluid under the confining pressure pore pressure condition and apply the temperature target stratum temperature.
After the pressure of injected clear water reaches the pore pressure, the silt mixture fluid marked by the radioactive isotope tracer is injected from the simulated borehole, and the permeability change of the rock sample is measured at the same time. To simulate different contamination levels, two different permeabilities a, b were set, where a > b. In this embodiment, the permeabilities a and b are set to be 0.4 and 0.2, respectively, and the silt injection is stopped when the permeabilities of each two rock samples in the four rock samples of ABCD respectively reach the set permeabilities. The pollution simulation degrees of the four groups of rock samples are shown in table 1, the rock samples with different pollution degrees are simulated under different permeability, and a pollution zone model diagram is shown in fig. 5.
TABLE 1
S5: and carrying out a water injection dilatation expansion indoor simulation test.
(1) And (3) performing a constant-pressure low-flow-rate water injection expansion indoor simulation test. In the test process, the same radial and axial pressures are continuously and synchronously applied to four groups of rock samples which simulate pollution zones, clean water is injected into simulated boreholes of each group of rock samples with different pollution degrees, and the injection pressures are respectively as follows: the group A is 50% of confining pressure, the group B is 75% of confining pressure, the group C is 95% of confining pressure, the group D is 120% of confining pressure, fluid is injected into the rock core through water injection equipment for a long time (48h) to generate a capacity expansion area, axial and radial stress, strain and rock core permeability are continuously recorded in the test process, and the test result is analyzed to obtain the optimal capacity expansion pressure.
(2) And (3) performing a constant-flow low-flow-speed water injection expansion indoor simulation test. Taking another four groups of rock samples, continuously and synchronously applying the same radial and axial pressure to the four groups of tests, and injecting different flow rates into each group of rock samples with different pollution degrees, wherein the flow rates are respectively as follows: and (3) injecting fluid into the core for a long time (48h) to generate an expansion area, continuously recording axial and radial stress, strain and core permeability in the test process, and analyzing the test result to obtain the optimal expansion flow rate, wherein the injection amount is 0.1mL/min, 0.5mL/min, 2mL/min and 10 mL/min.
(3) And (3) performing a circulating water pressure expansion indoor simulation test under different frequencies. The method comprises a low-flow-rate capacity-expansion indoor simulation test of circulation constant pressure under different frequencies and a low-flow-rate capacity-expansion indoor simulation test of circulation constant flow under different frequencies.
(a) For the low-flow-rate expansion chamber simulation test of the circulating constant pressure under different frequencies, the same radial and axial pressures are continuously and synchronously applied to the four groups of tests in the test process. The water injection pressure with the best expansion effect obtained in the low-flow-rate expansion chamber simulation test with the constant pressure in S5(2) is taken as the radial flow pressure of each group of tests. And (3) changing the injection-production time ratio of each group of rock samples with different pollution degrees (A group, 48h for injection, 12h for production, B group, 48h for injection, 24h for production, C group, 48h for injection, 36h for production, D group, 48h for injection, 48h for production) and injecting fluid into the rock core for a long time (48h) to generate an expansion area.
(b) For the low-flow-rate capacity-expanding blockage-removing indoor simulation test of the circulating constant flow under different frequencies, the same radial and axial pressures are continuously and synchronously applied to four groups of tests in the test process. The water injection flow with the best expansion effect obtained in the low-flow-rate expansion indoor simulation test with the constant flow of S5(3) is used as the radial injection flow of each group of tests, the injection-extraction time proportion (A group, 48h for injection: 12h for extraction; B group, 48h for injection: 24h for extraction; C group, 48h for injection: 36 h; D group, 48h for injection: 48h for extraction) of rock samples with different pollution degrees is changed for each group, and fluid is injected into the rock core for a long time (48h) to generate an expansion area.
S6: and (4) analyzing the expansion and expansion test result and establishing an expansion equation. In the test process, the axial stress-strain, the radial stress-strain and the core permeability of the three types of expansion tests are continuously recorded, and as shown in fig. 6, the matching relationship between the water injection parameters and the rock stress-strain and permeability is established for the expansion test results. And obtaining the optimal expansion pressure, the optimal expansion flow and the optimal injection-production time ratio after analysis, and establishing an equation under the rock expansion condition according to the experimental analysis result to provide theoretical guidance for establishing a mathematical model.
S7: and (4) performing a fracture surface (micro-crack) microscopic morphology test after expansion. And after the water injection expansion test is finished, taking out the rock sample. And observing the rock sample subjected to the circulation water pressure expansion and blockage removal indoor simulation test under different frequencies. Using a three-dimensional reconstruction imaging X-ray microscope, the following observations were made using a computer-controlled tomography technique:
(1) and observing the expansion profile dispersion condition of the rock sample after the low-flow-rate expansion chamber with constant pressure and the simulation test. Calculating the density of the micro-cracks, analyzing the change relation between each test parameter and the porosity, permeability and crack parameters of the rock, and determining the water injection pressure with the best capacity expansion effect.
(2) And observing the change of the fracture expansion surface of the rock sample after the low-flow-rate expansion chamber with constant flow rate is subjected to the simulation test, analyzing the change of the porosity and the permeability of the rock, and determining the injection flow with the best expansion effect.
(3) And observing the fracture expansion surface of the rock sample after the cyclic water pressure expansion indoor simulation test under different frequencies, comparing the fracture surface expansion and blockage removal conditions of the low-flow-rate expansion indoor simulation test rock sample under the cyclic constant pressure with the fracture surface expansion and blockage removal conditions of the low-flow-rate expansion indoor simulation test rock sample under the cyclic constant flow, and providing the optimal cyclic water pressure expansion implementation scheme for the establishment of the following numerical model.
(4) And observing the pollution zone expansion profile of each group of rock samples with different pollution degrees in the expansion test, and comparing the expansion conditions under different pollution degrees.
Calculating the density of the micro-cracks under different expansion conditions through the change of the micro-cracks of the three types of expansion test rock samples, and establishing the change relation of each test parameter with the porosity, permeability and crack parameters of the rock. The experimental observations are as follows: the expansion profile is dispersed (as shown in figure 7), the height contour map of the fracture surface (as shown in figure 8) and the visual description of the form and the position of the microcrack (as shown in figure 9). And (3) representing the particle cementation degree and the pore gap distribution of the sample after the expansion (as shown in figures 10-11).
S8: and establishing a loose sandstone reservoir dilatation expansion mathematical model and a numerical model. And establishing a mathematical model according to the analysis result of the fracture surface micro-morphology observation test and the rock expansion equation. The proportional relation between the water injection parameters and the rock strain, the porosity and the permeability is described in advance by using the rock expansion equation established in S6, and then the proportional relation is verified by using the microscopic morphology observation experiment result proportional relation in S7, so that a set of water injection expansion mathematical model is established, and a theoretical basis is provided for establishing a water injection expansion numerical model.
According to the field reservoir parameters, the established mathematical model is applied to obtain the optimal water injection dilatation parameters, and a temperature-seepage-stress coupled water injection dilatation expansion numerical model is established from the shaft scale, wherein the specific method comprises the following steps:
(1) establishing a hydraulic capacity-expanding and blockage-removing geometric model of the sandstone reservoir with the wellbore scale by using finite element analysis software, wherein the model is shown in figure 12;
(2) defining the material property of the model according to the rock mechanical parameters measured by the S1 test;
(3) carrying out grid division on the model, defining unit attributes, and carrying out grid encryption on the simulated pollution area;
(4) applying boundary conditions, loads and temperatures to the model according to the field reservoir information;
(5) defining expansion parameters, amplifying the expansion parameters obtained in the test S6 according to the proportion of the borehole section of the geometric model to the borehole section of the rock sample simulation borehole, and then defining the amplified expansion parameters for the model;
(6) submitting model calculations, calculating a result cloud picture, as shown in fig. 13;
(7) and continuously correcting the numerical model by comparing the calculation result of the temperature-seepage-stress coupled hydraulic expansion numerical model with the test result in the water injection expansion chamber until the model can be mutually verified with the test result in the water injection expansion chamber.
The temperature-seepage-stress hydraulic power capacity expansion numerical coupling model verified by test results is applied to different target layers of the oil field respectively. Firstly, geological mechanical parameters (including rock mechanical parameters, stress environment near a stratum shaft and the like) of a target layer are input into a model. And then, by changing the hydraulic expansion water injection parameters, calculating the changes of the parameters such as porosity, permeability, microcrack density and the like (as shown in fig. 14 and 15) corresponding to the parameters, determining expansion water injection construction parameters under different rock mechanical parameter conditions with the aim of optimal porosity and permeability increasing effect on the premise of not leaking the well wall, and optimizing the injection construction parameters by using experimental results to obtain an optimal expansion injection scheme.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed form, but on the contrary, is intended to cover various other combinations, modifications, and environments within the scope of the invention as set forth herein, as may be modified by the teachings or skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
It should be noted that, for simplicity of description, the above-mentioned embodiments of the method are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the order of acts described, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and elements referred to are not necessarily required in this application.
Claims (9)
1. An experiment method for optimizing water injection expansion construction parameters is characterized by comprising the following steps:
s1: testing mechanical properties and physical parameters of reservoir rock to obtain a particle size composition distribution curve, porosity, permeability, a stress-strain curve and elastic parameters of the rock;
s2: preparing an artificial rock sample which is most consistent with the reservoir rock properties;
s3: preparing a plurality of artificial rock samples obtained in S2, dividing the artificial rock samples into a plurality of groups, wherein each group comprises two artificial rock samples, drilling a borehole in the center of the cross section of each artificial rock sample, and putting a simulation casing for simulating an exploitation scene;
s4: performing a simulation test of the formation conditions and the pollution zones on the artificial rock sample obtained in the step S3;
s5: performing a water injection expansion indoor simulation test on the artificial rock sample obtained in the step S4 to obtain an optimal water injection parameter for expansion;
s6: analyzing the result of the simulation test in the water injection expansion chamber and establishing an expansion equation;
s7: performing microscopic morphology observation test and analysis on a fracture surface formed after the simulation test in the water injection expansion chamber;
s8: and establishing a set of mathematical model according to the rock expansion equation and the fracture surface microscopic morphology observation test analysis result, and using the mathematical model as a theoretical guidance for establishing a numerical model.
2. The experimental method for optimizing water injection expansion construction parameters of claim 1, wherein the experimental method of S2 is characterized in that
The method comprises the following steps:
s21: preparing a plurality of groups of artificial rock samples with different proportions of quartz sand with various particle sizes according to the particle size composition distribution curve of the rock obtained in S1;
s22: testing to obtain the porosity, permeability, stress-strain curve and elastic parameter of each group of artificial rock samples in S21, and comparing the obtained parameters with the mechanical physical parameters of the reservoir rock measured in S1;
s23: and analyzing to obtain a group of artificial rock samples of which the particle size proportion of the quartz sand particles is most consistent with the properties of reservoir rocks.
3. The experimental method for optimizing the construction parameters of water injection expansion and expansion as claimed in claim 1, wherein in S4,
the stratum condition simulation comprises the simulation of the pore pressure and the stratum temperature of the target layer rock, and the concrete operations are as follows:
respectively injecting clear water from the top cross section of each group of artificial rock samples until the injection pressure reaches the pore pressure of the target layer, and keeping the pore pressure until the test is finished;
meanwhile, the formation temperature is set for each group of artificial rock samples.
4. The experimental method for optimizing the construction parameters of water injection expansion and expansion as claimed in claim 3, wherein
In S4, the specific operation of the contamination zone simulation test is as follows:
injecting a silt mixture fluid into the simulated borehole of each group of artificial rock samples bearing the pore pressure, wherein the silt mixture fluid is marked by a radioactive isotope tracer;
and meanwhile, measuring the permeability of each group of artificial rock samples, setting two different permeabilities in advance, and continuously injecting the fluid until the two artificial rock samples of each group respectively reach the preset permeability, so as to simulate the pollution conditions of different degrees of the two artificial rock samples of each group.
5. The experimental method for optimizing water injection expansion construction parameters of claim 1, wherein the experimental method of S5 is characterized in that
The method comprises the following specific steps:
s51: performing a water injection test on the simulated borehole of the artificial rock sample obtained in the step S4, wherein the water injection test is performed under different water injection parameters respectively, and the water injection parameters comprise water injection pressure, water injection flow and water injection frequency;
s52: and analyzing the optimal water injection pressure, the optimal water injection flow and the optimal injection-production time ratio according to the stress strain and permeability of the artificial rock sample.
6. The experimental method for optimizing water injection expansion construction parameters of claim 5, wherein the water injection expansion construction parameters are optimized
And performing water injection expansion tests under the frequency parameters under the conditions of the optimal water injection pressure and the optimal water injection flow respectively.
7. The experimental method for optimizing water injection expansion construction parameters of claim 1, wherein the experimental method of S6 is characterized in that
The method specifically comprises the following steps: and determining the matching relation between the water injection parameters and the stress-strain and permeability of the artificial rock sample, establishing an equation under the condition of rock expansion and dilatation, and providing basic theoretical guidance for establishing a mathematical model.
8. The experimental method for optimizing water injection expansion construction parameters of claim 1, wherein the experimental method of S7 is characterized in that
The method specifically comprises the following steps: and observing the internal structure of the three types of rock samples after the expansion test and the size of the expansion area of the rock samples with different pollution degrees by using a tomography technology to obtain visual observation results including but not limited to the form and the position of the microcrack, and comparing and analyzing the test results.
9. The experimental method for optimizing water injection expansion construction parameters of claim 1, wherein the experimental method of S8 is characterized in that
The method specifically comprises the following steps:
s81: establishing a mathematical model of water injection parameters and rock sample strain, porosity and permeability through finite element software;
s82: calculating an optimal capacity expansion parameter through the mathematical model;
s83: setting and calculating a numerical model through the optimal capacity expansion parameters;
s84: comparing the calculation result of the temperature-seepage-stress coupled hydraulic capacity expansion numerical model with the capacity expansion and blockage removal indoor test result, and correcting the numerical model until the model and the capacity expansion indoor test result can be verified mutually;
s85: and finally, optimizing water injection dilatation expansion parameters to finally determine an optimal construction scheme aiming at increasing porosity, permeability and crack density in the application of the numerical model.
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