Method for information representation of reservoir preferential flow and remaining oil based on CFD theory

Abstract

The present application relates to the oil reservoir advantage flow and the informationization characterization method of remaining oil based on CFD theory, belongs to the technical field of reservoir engineering.The present application discloses the informationization characterization method of oil reservoir advantage flow and remaining oil based on CFD theory, including constructing three-dimensional geological model;Three-dimensional geological model is converted into Python visual model;Through the oil gas water three-phase percolation model of considering interface force source phase and convection adsorption diffusion by combining Python language programming of computational fluid dynamics theory;Screening equation solution, and combining GPU high-efficiency calculation method is solved;Through PythonVedo software package carries out data processing and visualization, obtains the informationization display drawing of oil reservoir large well spacing advantage flow and remaining oil distribution.The present application is based on the simulation method of oil reservoir large well spacing advantage flow and remaining oil distribution of computational fluid dynamics, and can be used for the scheme simulation of the tertiary oil recovery of conventional water drive, chemical drive, polymer drive and other oilfields with physical and chemical reactions.

Description

Technical Field

[0001] This invention relates to an information-based characterization method for dominant flow and residual oil in reservoirs based on CFD theory, belonging to the field of reservoir engineering technology. Background Technology

[0002] With the continuous expansion of global energy supply demand and the continuous depletion of oil reserves, research on the sustainable development and utilization of oil reservoirs is receiving increasing attention. The flow behavior of oil reservoirs has a crucial impact on their production and development.

[0003] Computational fluid dynamics (CFD) is a numerical analysis method that simulates the movement of flowing substances using mathematical models and performs calculations on these models using computing equipment. In CFD simulations, the Navier-Stokes equations, with the Euler and Navier-Stokes equations at their core, are widely used. Therefore, the application of CFD simulations in reservoir flow behavior has received considerable attention. This method can be used to simulate reservoir flow behavior, including two-phase flow (oil-water) and multiphase flow. However, conventional CFD calculations are performed at the core scale and cannot be used for reservoir-scale simulations. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the present invention aims to provide an information-based characterization method for reservoir dominant flow and residual oil based on CFD theory.

[0005] The technical solution provided by this invention to solve the above-mentioned technical problems is: an information-based characterization method for dominant flow and remaining oil in reservoirs based on CFD theory, comprising:

[0006] Step S1: Collect geological parameters of the target reservoir and construct a three-dimensional geological model;

[0007] Step S2: Convert the 3D geological model into a Python visualization model in .CSV format;

[0008] Step S3: Write a three-phase seepage model of oil, gas and water that considers the interfacial force source phase and convection adsorption diffusion by combining computational fluid dynamics theory with Python language.

[0009] Step S4: Select solutions to the equations and solve them using efficient GPU computing methods;

[0010] Step S5: Use the Python Vedo software package to process and visualize the data to obtain an information-based display map of the dominant flow and remaining oil distribution in the reservoir with large well spacing.

[0011] A further technical solution is that the geological parameters include oilfield burial depth, permeability, porosity, crude oil density, crude oil viscosity, and well spacing.

[0012] A further technical solution is that, in step 1, a three-dimensional geological model is constructed based on Petrel, a mainstream geological modeling software in the field of reservoir development.

[0013] A further technical solution is that, in step 1, the three-dimensional geological model is converted into a Python visualization model in .CSV format using Python Pandas.

[0014] A further technical solution is that the specific process of step S3 is as follows:

[0015] Step S31: Use Python software to write the mass conservation equations, energy conservation equations, and phase saturation equations for the three flows of oil, gas, and water based on the Navier-Stokes equations;

[0016] Step S32: Next, write the interfacial force source phase equation and the convection adsorption diffusion equation as auxiliary equations to calculate the interfacial reaction and reaction convection diffusion process in the flow process.

[0017] A further technical solution is that the equation in step S31 includes:

[0018]

[0019]

[0020]

[0021] In the formula: ρ is density; t is time; v is velocity; S w φ represents saturation; k represents permeability; μ represents viscosity; and φ represents porosity.

[0022] A further technical solution is that the equation in step S32 includes:

[0023]

[0024]

[0025] In the formula: D is the depth; S w This represents saturation.

[0026] A further technical solution is that the equation solution method is any one of explicit, implicit, Simple algorithm, or PISO algorithm.

[0027] This invention has the following beneficial effects: This invention uses computational fluid dynamics theory combined with Python language to develop a three-phase seepage model of oil, gas and water that considers the interfacial force source phase and (reaction) convection adsorption diffusion. Combined with the efficient computing method of GPU, the simulation performance is enhanced, forming a simulation method for the dominant flow and remaining oil distribution of large well spacing in oil reservoirs based on computational fluid dynamics. It can be used to simulate tertiary oil recovery schemes in oilfields with physicochemical reactions, such as conventional water drive, chemical drive, and polymer drive. Attached Figure Description

[0028] Figure 1 This is a plan view of the dominant flow channel distribution;

[0029] Figure 2 Planar distribution of injected water (a) and remaining oil (b) during water drive in a reservoir with a well spacing of 1000m;

[0030] Figure 3 This is a vertical distribution diagram of water saturation during water drive in an oil reservoir with a well spacing of 1000m.

[0031] Figure 4 This is a vertical distribution diagram of oil saturation during water drive in an oil reservoir with a well spacing of 1000m.

[0032] Figure 5 This is a diagram showing the concentration distribution of the chemical flooding system via convection and diffusion. Detailed Implementation

[0033] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] The present invention provides an information-based characterization method for reservoir dominant flow and remaining oil based on CFD theory, comprising the following steps:

[0035] Step S1: Collect geological parameters of the target reservoir and construct a three-dimensional geological model based on Petrel, a mainstream geological modeling software in the field of reservoir development;

[0036] Step S2: Convert the 3D geological model created by Petrel into .CSV format using Python Pandas and save it.

[0037] Step S3: Using Python software, write the mass conservation equation, energy conservation equation, and phase saturation equation for the three-phase flow of oil, gas, and water based on the Navier-Stokes equations.

[0038]

[0039]

[0040]

[0041] In the formula: ρ is density; t is time; v is velocity; S w φ represents saturation; k represents permeability; μ represents viscosity; φ represents porosity.

[0042] Step S4: Compile phase equations considering interfacial force sources and (reaction) convection-adsorption-diffusion equations to characterize physicochemical flow characteristics;

[0043]

[0044]

[0045] In the formula: D is the depth; S w Saturation;

[0046] Step S5: Select solutions to the equation (explicit, implicit, Simple algorithm, PISO algorithm, etc.) and solve them by writing code in Python Numpy;

[0047] Step S6: Use the PythonVedo software package to process and visualize the data to obtain an information-based display of the dominant flow and remaining oil distribution in the reservoir with large well spacing.

[0048] Example

[0049] An oil field has a burial depth of approximately 4500m and a permeability distribution of 50×10⁻⁶. -3 μm 2 -1000×10 -3 μm 2 The porosity of this section is mainly distributed between 14% and 20%, with an average permeability of 238.77 × 10⁻⁶. -3 μm 2 The average porosity is 14.09%, classifying it as a medium-porosity, medium-to-high permeability reservoir. The density of the underground crude oil is 0.74 g / cm³. 3 The viscosity of the underground crude oil is about 20 mP·s, and the well spacing is 700 to 1100 m.

[0050] By collecting geological parameters of the target reservoir, a three-dimensional geological model was constructed using Petrel, a mainstream geological modeling software in the field of reservoir development. This model was then converted to a .CSV file using Python Pandas. Based on the Navier-Stokes (NS) equations, Python software was used to write mass conservation equations, energy conservation equations, phase saturation equations, and phase equations considering interfacial force sources, as well as (reaction) convection-adsorption-diffusion equations for the three flows of oil, gas, and water. Explicit solution methods for the equations were selected and solved using Python Numpy code. Data processing and fitting were performed using the Python Vedo package, revealing the existence of distinct dominant flow channels between wells. Figure 1 As shown, further detailed study using a scaled-up well model revealed that in large-well-spacing development, dominant flow channels exhibit an inter-well surge phenomenon on the plane, and multiple dominant flow channels develop, such as... Figure 2 As shown; in the longitudinal direction, the water flow is affected by gravity and density, and as the injection distance increases, a dominant flow channel is formed at the bottom of the reservoir, as shown. Figure 3 As shown, the remaining oil is concentrated in the upper part of the reservoir. Figure 4 As shown. Further chemical flooding simulations were conducted, such as... Figure 5 As shown, during chemical flooding, the formation water and the injection system will undergo convection and diffusion, and the diffusion front is much larger than the water flooding front. Convection and diffusion is an important factor affecting chemical flooding.

[0051] In addition to simulating the dominant flow and remaining oil distribution in reservoirs with large well spacing, this invention can also perform reservoir-scale simulations of physicochemical flooding for tertiary oil recovery methods such as polymer flooding and chemical flooding, thus offering superior advantages.

[0052] The above description is not intended to limit the present invention in any way. Although the present invention has been disclosed through the above embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for informational characterization of reservoir dominant flow and remaining oil based on CFD theory, characterized in that, include: Step S1: Collect geological parameters of the target reservoir and construct a three-dimensional geological model; Step S2: Convert the 3D geological model into a Python visualization model in .CSV format; Step S3: Write a three-phase seepage model of oil, gas and water that considers the interfacial force source phase and convection adsorption diffusion by combining computational fluid dynamics theory with Python language. Step S31: Use Python software to write the mass conservation equations, energy conservation equations, and phase saturation equations for the three flows of oil, gas, and water based on the Navier-Stokes equations; The equations in step S31 include: In the formula: Density; For time; For speed; Saturation; For penetration rate; Viscosity; Porosity; Step S32: Next, write the interfacial force source phase equation and the convection adsorption diffusion equation as auxiliary equations for calculating the interfacial reaction and reaction convection diffusion process in the flow process. The equations in step S32 include: In the formula: For depth; Saturation; Step S4: Select solutions to the equations and solve them using efficient GPU computing methods; Step S5: Use the Python Vedo software package to process and visualize the data to obtain an information-based display map of the dominant flow and remaining oil distribution in the reservoir with large well spacing.

2. The method for informational characterization of reservoir dominant flow and remaining oil based on CFD theory according to claim 1, characterized in that, The geological parameters include oilfield burial depth, permeability, porosity, crude oil density, crude oil viscosity, and well spacing.

3. The method for informational characterization of reservoir dominant flow and remaining oil based on CFD theory according to claim 2, characterized in that, In step 1, a three-dimensional geological model is constructed based on Petrel, a mainstream geological modeling software in the field of reservoir development.

4. The method for informational characterization of reservoir dominant flow and remaining oil based on CFD theory according to claim 1, characterized in that, In step 1, the three-dimensional geological model is converted into a Python visualization model in .CSV format using Python Pandas.

5. The method for informational characterization of reservoir dominant flow and remaining oil based on CFD theory according to claim 1, characterized in that, The solution method for the equation can be any one of the following: explicit, implicit, Simple algorithm, or PISO algorithm.

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