A method for predicting oil well productivity considering fracture interference and its microscopic physical model device

Abstract

The present invention provides a method for predicting the production capacity of an oil well taking into account the interference of fractures and a microscopic physical model device thereof, comprising the following steps: S1) obtaining image data of water-driven oil flow phenomena in double fractures of different models, different crude oil viscosities and different levels through microscopic visualization experiments; S2) quantitatively characterizing the interference degree between fractures; S3) respectively confirming the relationship between fracture grade difference, crude oil viscosity, fracture length and relative interference coefficient RIF to obtain the expression of relative interference coefficient RIF; S4) establishing the coefficients in the calculation formula of relative interference coefficient RIF; S5) obtaining the ratio nK of equivalent permeability of fracture parts according to the predicted crude oil parameters, formation parameters and production parameters of the oil well at the initial stage of production, and obtaining the recovery rate of dominant fractures; S6) obtaining the recovery rate of inferior fractures. The present invention can be applied to the prediction of production capacity of fractured oil reservoirs after water plugging, and is particularly applicable to fractured oil reservoirs with strong heterogeneity and complex oil-water relationship, and due to serious interference between formation fractures.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas field development, and in particular to an oil well productivity prediction method considering crack interference and a microscopic physical model device thereof. Background Art

[0002] Fractured reservoirs have become an important type of reservoir in my country, accounting for a certain proportion of reserves and production. The development of fractured reservoirs is more complicated than that of non-fractured reservoirs due to their complex structure. Such reservoirs have strong heterogeneity and complex oil-water relationship. In order to improve the development effect, it is necessary to conduct in-depth research on the development of fractured reservoirs and optimize the plan to increase production.

[0003] Patent CN 104196503 A reports a physical model of visualized water-driven oil in fractured oil reservoirs and a physical simulation experimental device, wherein the physical model of visualized water-driven oil in fractured oil reservoirs comprises a matrix, and the surface of the matrix is ​​provided with three levels of fractures, namely large-level fractures, medium-level fractures and small-level fractures. The physical model of visualized water-driven oil in fractured oil reservoirs and the physical simulation experimental device can be used for visualized water-driven oil physical simulation experiments in complex fractured oil reservoirs, to study the movement of oil and water in fracture systems, the degree of recovery and water content at different stages, and to study the confluence interference and flooding laws of complex structure wells in complex fractured oil reservoirs, so as to provide theoretical basis and technical support for water injection development of complex fractured oil reservoirs.

[0004] Patent CN 105913155A reports a method and system for predicting tight oil production capacity taking into account stress interference and fracturing fluid loss, including: obtaining basic parameters; calculating the impact data of the induced stress generated by each stage of the fracturing on the ground stress in the multi-stage fracturing of tight oil horizontal wells; after the fracturing construction, calculating the impact data of the fracturing fluid in the reservoir matrix on the pore pressure of the reservoir matrix; calculating the impact data of stress interference and loss on the size of artificial fractures; calculating the impact data of stress interference and loss on the permeability of artificial fractures; constructing a tight oil production capacity prediction model to obtain tight oil production capacity prediction results.

[0005] However, the development of fractured reservoirs is more complicated than that of non-fractured reservoirs due to their complex structure. Such reservoirs have strong heterogeneity and complex oil-water relationships. In addition, due to the serious interference between formation fractures, the commonly used production capacity prediction models often have a large deviation from the actual production capacity, thus losing their guiding and reference value. Summary of the invention

[0006] In order to solve the problem that the prediction model of the prior art has a large deviation from the actual production capacity, the present invention provides an oil well production capacity prediction method considering fracture interference and a microscopic physical model device thereof.

[0007] The technical solution of the present invention is as follows:

[0008] A method for predicting oil well productivity considering fracture interference specifically comprises the following steps:

[0009] S1) obtaining image data of water-to-oil flow phenomena in different models, different crude oil viscosities and / or different grade differences through microscopic visualization experiments;

[0010] S2) quantitatively identify the collected image data and obtain the small fracture recovery curve of the 100:100um to 100:600um model, quantitatively characterize the interference degree between fractures, and include parameters of different models, different scales, and different crude oil viscosities into the relative interference factor RIF system for comparison;

[0011] S3) respectively confirming the relationship between the fracture difference, crude oil viscosity, fracture length and the relative interference coefficient RIF, and using orthogonal test to analyze the influence of the fracture difference, crude oil viscosity and fracture length on the relative interference coefficient RIF, and obtaining the expression of the relative interference coefficient RIF;

[0012] S4) establishing the coefficients in the relative interference factor RIF calculation formula through the CT online displacement test, and obtaining the RIF calculation formula;

[0013] S5) obtaining the ratio nK of the equivalent permeability of the fracture components according to the predicted crude oil parameters, formation parameters and production parameters of the oil well at the initial stage of production, and bringing it into the calculation formula of the relative interference coefficient RIF to obtain the value of the relative interference coefficient RIF, and obtaining the recovery degree of the dominant fracture according to the production profile;

[0014] S6) obtaining the recovery degree of the disadvantaged fractures according to the recovery degree of the dominant fractures.

[0015] Preferably, the step S1) comprises the following steps:

[0016] S11) adding fuels of different colors to the water phase and the oil phase, respectively, and measuring the viscosity of the oil phase and the water phase;

[0017] S12) constructing a plurality of microscopic models with different permeabilities and different cracks, and starting the controller, data collector and monitor in the microscopic physical model device;

[0018] S13) introducing saturated oil into different microscopic models respectively, and after the microscopic models are saturated with oil, water flooding is performed, and water flooding data is recorded;

[0019] S14) analyzing and processing the acquired water drive data;

[0020] S15) cleaning and drying the model, and repeating steps S13) and S14) with different crude oil viscosities.

[0021] Preferably, the different models refer to a double-slit model or a slit network model.

[0022] The relationship between the crack level difference and the relative interference coefficient RIF is:

[0023] q R (nK) = 1-1.5693 (nK) (-1.77076) .

[0024] The relationship between the crude oil viscosity and the relative interference coefficient RIF is:

[0025] h R (μ)=0.76525μ 0.02863 .

[0026] The relationship between the crack length and the relative interference coefficient RIF is:

[0027] g R (L)=0.84886L (-0.03948) .

[0028] Preferably, the CT online displacement test comprises the following steps:

[0029] S41) Design 3 fracture-cavity carbonate resin-cemented cores;

[0030] S42) injecting saturated oil into the core and then performing water flooding, and obtaining the variation law of the recovery degree of large and small fractures through the digital core;

[0031] S43) According to the variation law of the recovery degree, the coefficient in the calculation formula of the relative interference coefficient RIF is determined.

[0032] The calculation formula of the relative interference coefficient RIF is specifically:

[0033] RIF=0.855·[1-1.5693(nK) (-1.77076) ].

[0034] The relationship between the recovery degree n1 of the dominant fracture and the recovery degree n2 of the inferior fracture is:

[0035] n2=(1-RIF)×n1.

[0036] A microscopic physical model device used in the above method is characterized in that it includes a micro-fracture core model, a microscope, a microfluidic pump, a data collector, and an image collector. The image collector is connected to the microscope to collect image data observed by the eyepiece of the microscope; the micro-fracture core model is installed on the stage of the microscope and connected to the microfluidic pump; the microfluidic pump injects oil phase or water phase through a controller and an external liquid storage tank; the data collector is connected to the microfluidic pump and the image collector.

[0037] The technical effects of the present invention are as follows:

[0038] The present invention discloses an oil well productivity prediction method considering fracture interference and a microscopic physical model device thereof. The microscopic physical model device is used. In different models, a certain level difference is fixed, the crude oil viscosity is adjusted, and the influence of viscosity on shielding is measured, or a certain viscosity is fixed and the influence on shielding at different level differences is measured. The flow phenomena and differences of water-driven oil in large and small fractures under different models and crude oil viscosities are simulated, and a productivity prediction model introducing an interference coefficient is constructed to provide valuable reference data for subsequent water plugging and oil production. The method can be applied to productivity prediction of fractured oil reservoirs after water plugging, and is particularly applicable to fractured oil reservoirs with strong heterogeneity and complex oil-water relationship and severe interference between formation fractures. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a schematic diagram of the microscopic object model device of the present invention,

[0040] Figure 2 It is a schematic diagram of the application process of the present invention. DETAILED DESCRIPTION

[0041] In order to better understand the present invention, the present invention is further explained below in conjunction with specific embodiments.

[0042] Example

[0043] This embodiment provides a method for predicting oil well productivity taking into account fracture interference, using the following microscopic physical model device, such as Figure 1 It includes a micro-fracture core model, a microscope, a microfluidic pump, a data collector, and an image collector. The image collector is connected to the microscope to collect image data observed by the eyepiece of the microscope; the micro-fracture core model is installed on the stage of the microscope and connected to the microfluidic pump; the microfluidic pump injects oil phase or water phase through a controller and an external liquid storage tank; the data collector is connected to the microfluidic pump and the image collector.

[0044] The method specifically comprises the following steps:

[0045] S1) Through microscopic visualization experiments, image data of water-driven oil flow phenomena in different micro-fracture core models, different crude oil viscosities, and different levels of double fractures are obtained;

[0046] S11) adding fuels of different colors to the water phase and the oil phase, respectively, and measuring the viscosity of the oil phase and the water phase;

[0047] S12) constructing a plurality of microscopic models with different permeabilities and different cracks, and starting the controller, data collector and monitor in the microscopic physical model device;

[0048] S13) introducing saturated oil into different microscopic models respectively, and after the microscopic models are saturated with oil, water flooding is performed, and water flooding data is recorded;

[0049] S14) analyzing and processing the acquired water drive data;

[0050] S15) cleaning and drying the model, and repeating steps S13) and S14) with different crude oil viscosities.

[0051] S2) quantitatively identify the collected image data and obtain the small fracture recovery curve of the 100:100um to 100:600um model, quantitatively characterize the interference degree between fractures, and include the parameters of different models, different scales, and different crude oil viscosities into the relative interference coefficient RIF system for comparison;

[0052] The small fracture recovery degree curve is quantitatively identified by a binarization algorithm.

[0053] The binarization algorithm is specifically as follows: extracting the RGB value of the color in the image data according to the image data obtained in step S1), and optimizing it in combination with the minimum error method to obtain a high-precision image recognition result, and then obtaining a 100:100um to 100:600um model small crack recovery degree curve.

[0054] S3) respectively confirming the relationship between the fracture difference, crude oil viscosity, fracture length and the relative interference coefficient RIF, and using orthogonal test to analyze the influence of the fracture difference, crude oil viscosity and fracture length on the relative interference coefficient RIF, and obtaining the expression of the relative interference coefficient RIF;

[0055] The relationship between the crack level difference and the relative interference coefficient RIF is:

[0056] q R (nK) = 1-1.5693 (nK) (-1.77076)

[0057] The relationship between the crude oil viscosity and the relative interference coefficient RIF is:

[0058] h R (μ)=0.76525μ 0.02863

[0059] The relationship between the crack length and the relative interference coefficient RIF is:

[0060] g R (L)=0.84886L (-0.03948)

[0061] S4) establishing the coefficients in the relative interference factor RIF calculation formula through the CT online displacement test, and obtaining the RIF calculation formula;

[0062] S41) Design 3 fracture-cavity carbonate resin-cemented cores;

[0063] S42) injecting saturated oil into the core and then performing water flooding, and obtaining the variation law of the recovery degree of large and small fractures through the digital core;

[0064] S43) According to the variation law of the recovery degree, the coefficient in the calculation formula of the relative interference coefficient RIF is determined.

[0065] The calculation formula of the relative interference coefficient RIF is specifically:

[0066] RIF=0.855·[1-1.5693(nK) (-1.77076) ]

[0067] S5) obtaining the ratio nK of the equivalent permeability of the fracture components according to the predicted crude oil parameters, formation parameters and production parameters of the oil well at the initial stage of production, and bringing it into the calculation formula of the relative interference coefficient RIF to obtain the value of the relative interference coefficient RIF, and obtaining the recovery degree of the dominant fracture according to the production profile;

[0068] S6) obtaining the recovery degree of the disadvantaged fractures according to the recovery degree of the dominant fractures;

[0069] The relationship between the recovery degree n1 of the dominant fracture and the recovery degree n2 of the inferior fracture is:

[0070] n2=(1-RIF)×n1.

[0071] like Figure 2 As shown in the figure, combined with the initial production profile data, the crude oil, formation and production parameters of different fracture layers are brought into the stratified pressure recovery test data, and the equivalent permeability ratio nK of the dominant fracture layer and the inferior fracture layer can be calculated. The relative interference coefficient RIF of the implementation well can be obtained by bringing it into the formula. Combined with the oil production of the dominant fracture, the recovery degree n1 of the dominant fracture is calculated. The recovery degree n2 of the inferior fracture can be calculated through the relationship between the recovery degree n1 of the dominant fracture and the recovery degree n2 of the inferior fracture. The value of n2 is divided into four levels for judging the water blocking potential.

[0072] Degree of disadvantageous seam extraction 0-0.25 0.25-0.5 0..5-0.75 0.75-1.0 Water plugging potential classification big Larger Smaller Small

[0073] The following takes an oil well in a certain oil reservoir as an example. The production profile curve of the well shows layered production, and as production advances, the lower layer is gradually flooded and the upper layer production decreases. Therefore, the lower layer is judged to be a dominant fracture layer and the upper layer is a disadvantageous fracture layer. The equivalent permeability between the layers is calculated based on parameters such as reservoir thickness and production, and the equivalent permeability ratio is 1.69. Substituting it into the calculation formula of the relative interference coefficient, the relative interference coefficient is 0.325. At the same time, based on the cumulative oil production of the dominant fracture layer, the recovery degree of the dominant fracture layer is calculated to be 0.55, and the relative interference coefficient is substituted into n2=(1-RIF)×n1, and the recovery degree of the disadvantageous fracture layer is obtained as 0.37. Therefore, the well has a large water plugging potential.

Claims

1. A method for predicting oil well productivity considering fracture interference, comprising the following steps: S1) obtaining image data of water-to-oil flow phenomena in different models, different crude oil viscosities and / or different grade differences through microscopic visualization experiments; S2) quantitatively identify the collected image data and obtain the small fracture recovery curve of the 100:100um to 100:600um model, quantitatively characterize the interference degree between fractures, and include parameters of different models, different scales, and different crude oil viscosities into the relative interference factor RIF system for comparison; S3) respectively confirming the relationship between the fracture difference, crude oil viscosity, fracture length and the relative interference coefficient RIF, and using orthogonal test to analyze the influence of the fracture difference, crude oil viscosity and fracture length on the relative interference coefficient RIF, and obtaining the expression of the relative interference coefficient RIF; The relationship between the crack level difference and the relative interference coefficient RIF is: q R (nK)=1-1.5693(nK) (-1.77076) ; The relationship between the crude oil viscosity and the relative interference coefficient RIF is: h R (m)=0.76525m 0.02863 ; The relationship between the crack length and the relative interference coefficient RIF is: g R (L)=0.84886L (-0.03948) ; S4) establishing the parameters in the relative interference factor RIF calculation formula through the CT online displacement test, and obtaining the RIF calculation formula; The relative interference coefficient RIF calculation formula is specifically: RIF=0.855·[1-1.5693(nK) (-1.77076) ]; S5) according to the predicted crude oil parameters, formation parameters and production parameters of the oil well at the initial stage of production, the ratio of equivalent permeability of the fracture parts nK is obtained, and the ratio is brought into the relative interference coefficient RIF calculation formula to obtain the value of the relative interference coefficient RIF, and according to the production profile, the recovery degree of the dominant fracture is obtained; S6) according to the recovery degree of the dominant fracture, the recovery degree of the inferior fracture is obtained, The relationship between the recovery degree n1 of the dominant fracture and the recovery degree n2 of the inferior fracture is: n2=(1-RIF)×n1.

2. The method according to claim 1, characterized in that The step S1) comprises the following steps: S11) adding fuels of different colors to the water phase and the oil phase, respectively, and measuring the viscosity of the oil phase and the water phase; S12) constructing a plurality of microscopic models with different permeabilities and different cracks, and starting the controller, data collector and monitor in the microscopic physical model device; S13) introducing saturated oil into different microscopic models respectively, and after the microscopic models are saturated with oil, water flooding is performed, and water flooding data is recorded; S14) analyzing and processing the acquired water drive data; S15) cleaning and drying the model, and repeating steps S13) and S14) with different crude oil viscosities.

3. The method according to claim 1, characterized in that The different models are a double-slit model or a slit network model.

4. The method according to claim 1, characterized in that The CT online displacement test comprises the following steps: S41) Design 3 fracture-cavity carbonate resin-cemented cores; S42) injecting saturated oil into the core and then performing water flooding, and obtaining the variation law of the recovery degree of large and small fractures through the digital core; S43) According to the variation law of the recovery degree, the coefficient in the calculation formula of the relative interference coefficient RIF is determined.

5. A microscopic physical model device used in the method according to any one of claims 1 to 4, characterized in that The invention comprises a micro-fracture core model, a microscope, a microfluidic pump, a data collector and an image collector. The image collector is connected to the microscope to collect image data observed by the eyepiece of the microscope. The micro-fracture core model is installed on the stage of the microscope and connected to the microfluidic pump. The microfluidic pump injects oil phase or water phase through a controller and an external liquid storage tank. The data collector is connected to the microfluidic pump and the image collector.

Images