A method for predicting longitudinal breakthrough of CO2 flooding in deep fault block reservoirs

Abstract

The application provides a CO2 injection displacement longitudinal breakthrough prediction method for deep fault block reservoirs, relates to the technical field of unconventional oil and gas reservoir development, and aims at solving the problem that in the existing simulation research, the physical mechanism of longitudinal sealing failure is ignored, and it is difficult to truly reflect the longitudinal fluid migration behavior of fault block reservoirs under high-pressure gas injection conditions. In the numerical simulation, the capillary force of the longitudinal breakthrough between adjacent interface layers, the gravity and buoyancy of supercritical CO2, and the influence of the formation pressure between the two layers are considered. The driving force and resistance difference of CO2 longitudinal breakthrough, that is, the effective driving force ΔΦ eff , is used to determine whether there is longitudinal breakthrough. The longitudinal breakthrough risk index Fv is obtained by combining the effective driving force ΔΦ eff and the interface vertical conductivity Tv. Different longitudinal breakthrough risk zones are divided according to the distribution of the full model longitudinal breakthrough risk index Fv, and the production parameters of injection and production wells are dynamically adjusted, so as to provide reliable basis for timely adjustment of injection and production parameters, implementation of avoidance and selective plugging, and effective reduction of invalid circulation and recovery loss caused by gas channeling.

Description

Technical Field

[0001] This invention relates to a method for predicting vertical breakthrough of CO2 flooding in deep fault-block reservoirs, belonging to the field of unconventional oil and gas reservoir development technology. Background Technology

[0002] The development of deep oil reservoirs (typically referring to those buried at depths exceeding 3500 meters) faces numerous technical challenges. Firstly, due to high formation pressure and temperature, conventional water injection is ineffective, resulting in low water drive efficiency and a high risk of reservoir damage. Secondly, deep oil reservoirs exhibit strong heterogeneity and varying degrees of fracture development, which can easily lead to injected fluid surges, affecting displacement efficiency. Therefore, improving the recovery rate of deep oil reservoirs has become a crucial research direction in the petroleum industry.

[0003] CO2 injection for oil recovery (CO2-EOR) is considered one of the effective methods to enhance oil recovery in deep reservoirs. Under high temperature and pressure conditions, CO2 easily reaches a supercritical state (ScCO2), possessing both high gas diffusivity and high liquid solubility. This effectively reduces crude oil viscosity, improves fluidity, and promotes crude oil expansion, thereby increasing oil displacement efficiency. Furthermore, the miscibility pressure between CO2 and crude oil is more easily achieved in the high-pressure environment of deep reservoirs, which is conducive to the formation of miscible flooding and further improves oil recovery. However, CO2 injection in deep reservoirs still faces many challenges, such as the tendency for supercritical CO2 to rapidly penetrate along high-permeability channels, leading to a decrease in displacement efficiency. Simultaneously, the heterogeneity of deep reservoirs may exacerbate CO2 fingering, affecting the swept volume. Extensive research has focused on the simulation and prediction of lateral breakthroughs in response to the fingering or breakthrough behavior of injected fluids in reservoirs. For example, existing technologies include a risk assessment method for water breakthrough in aquifer gas reservoirs based on fuzzy comprehensive evaluation (GB2535581A), a dynamic characterization method for CO2 flooding breakthrough based on a combination of experiments and numerical simulations (CN119125508B), a method for predicting water flooding breakthrough time in carbonate oil reservoirs based on surrogate models (CN115526086B), and a gas or water breakthrough detection method based on production data analysis (US12359543B2). These methods mainly focus on the lateral movement and breakthrough behavior of injected fluids in the reservoir through high-permeability channels, fractures, or dominant seepage paths towards the production well.

[0004] However, the above methods generally assume that the reservoir is vertically sealed, meaning the caprock has sufficient sealing capacity and the injected fluid will not experience vertical breakthrough or escape. But in the actual development of deep fault-block reservoirs, the situation is more complex. Fault-block reservoirs typically feature well-developed faults, complex geostress, and strong reservoir heterogeneity. As water or gas injection continues, reservoir pressure rises, potentially leading to the following risks of vertical breakthrough:

[0005] Capillary pressure limit of caprock is breached: When the reservoir pressure exceeds the capillary sealing capacity of the caprock, the injected fluid (such as CO2) may overcome the capillary resistance of the caprock, resulting in longitudinal leakage or even penetration of the caprock.

[0006] Fault reactivation: Long-term high-pressure injection may reactivate originally closed faults, forming longitudinal escape channels. The injected fluid leaks along the fault to the upper strata and even the surface, bringing serious safety and environmental risks.

[0007] Formation of vertically dominant channels: Vertical fractures or high-permeability bands developed inside the fault block may become channels for the injected fluid to rapidly penetrate vertically, leading to a decrease in injection efficiency and a reduction in the sweep coefficient.

[0008] In actual production processes, due to the inherent properties of fault-block reservoirs, continuous CO2 injection may lead to problems such as excessively high reservoir pressure exceeding the capillary force limit of the caprock and fault reactivation. Currently, there is a lack of systematic, quantitative, and engineering-applicable prediction methods for the vertical breakthrough risk during CO2 injection in deep fault-block reservoirs. Existing simulation studies mostly ignore or simplify the physical mechanisms of vertical sealing failure, making it difficult to accurately reflect the vertical fluid migration behavior under high-pressure gas injection conditions in fault-block reservoirs. Therefore, in order to formulate safe and reliable CO2 injection enhanced oil recovery development schemes for deep fault-block reservoirs, it is necessary to develop a method for predicting vertical breakthrough during CO2 injection in deep fault-block reservoirs, reduce production risks, and guide the formulation of field production plans.

[0009] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0010] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0011] To address the aforementioned technical issues, this method employs numerical simulation to consider the capillary force, gravity and buoyancy of supercritical CO2, and formation pressure between the two layers that determine whether CO2 will undergo vertical breakthrough between adjacent interface layers. The effective driving force ΔΦ is calculated as the difference between the driving force and resistance of CO2 vertical breakthrough. eff To determine whether a vertical breakthrough exists, the vertical conductivity Tv of the interface is obtained based on reservoir physical parameters, combined with the effective driving force ΔΦ. effThe vertical breakthrough risk index Fv is obtained from the vertical conductivity Tv of the interface. Different vertical breakthrough risk zones are divided according to the distribution of the vertical breakthrough risk index Fv in the model grid. Finally, the production parameters of injection and production wells are dynamically adjusted based on the distribution of vertical breakthrough risk zones to ensure that the injection well with the highest breakthrough risk is surrounded by medium and low vertical breakthrough risk zones, so as to ensure the safety of the gas injection production plan.

[0012] Specifically, this invention provides a method for predicting the vertical breakthrough of CO2 flooding in deep fault-block reservoirs, comprising the following steps:

[0013] Step S1: Obtain seismic, logging, fluid parameters, and reservoir production data for the fault-block reservoir, and establish a numerical simulation model;

[0014] Step S2: Based on the reservoir production data in Step S1, perform historical fitting to obtain the simulated parameters;

[0015] Step S3: Obtain the breakthrough pressure P of any two adjacent capillary layers within the study area. c-entry ;

[0016] Step S4: Calculate the vertical pressure difference ΔΦ between any lower grid K and the upper grid K-1 within the study area;

[0017] Step S5: Calculate the effective driving force ΔΦ at adjacent interface layers. eff When the vertical pressure difference ΔΦ > 0, compare the vertical pressure difference ΔΦ and capillary breakthrough pressure P at adjacent interface layers. c-entry The magnitude of the pressure difference, when the vertical pressure difference ΔΦ is greater than the capillary breakthrough pressure P of the upper grid, is determined by... c-entry At that time, the pressure difference between the two pressures is the effective driving force ΔΦ. eff Only then can CO2 be driven into the upper grid;

[0018] Step S6: Calculate the vertical conductivity Tv of adjacent interfaces. The driving force for CO2 longitudinal breakthrough is the effective driving force ΔΦ. eff However, the ease of breakthrough is also affected by reservoir properties, namely the interfacial conductivity Tv between the upper and lower grid layers, and the vertical permeability PERMK of adjacent grids K and K-1. K and PERMK K-1 The vertical conductivity Tv between the two grids, considering the vertical spacing, is obtained by using the harmonic average calculation method.

[0019] Step S7: Calculate the vertical breakout risk index, taking into account the effective driving force ΔΦ. eff Calculate the vertical breakthrough risk index Fv using the vertical conductivity Tv of the interface:

[0020] Step S8: Obtain the distribution of the CO2 vertical breakthrough risk zone, statistically analyze all calculated grid Fv values, and take the 90th percentile of the full model Fv distribution as the threshold Fv. threshold , Fv > Fv threshold The grid markings are high-risk areas for vertical breakthroughs; the full model F is taken. v The 50th percentile of the distribution is used as the threshold Fv threshold2 , will Fv threshold1 > Fv > Fv threshold2 The grid is marked as a medium-risk area for vertical breakthrough, with Fv < Fv threshold2 The grid markings indicate vertical breakthroughs in low-risk areas.

[0021] Step S9: Optimize injection and production parameters. Based on the obtained distribution of the CO2 vertical breakthrough risk zone, dynamically adjust and optimize the injection and production parameters of injection and production wells near the risk zone.

[0022] As a further preferred embodiment of the present invention, the fluid parameters in step S1 mainly include the composition of the fluid in the well, the phase characteristics of the fluid under certain temperature and pressure conditions, and the relative permeability of oil-water and oil-gas.

[0023] As a further preferred embodiment of the present invention, the simulated parameters in step S2 include: Depth, reflecting the vertical depth at the center of the grid, in meters (m); PRES, pore pressure, in megapascals (MPa); Sg, gas saturation, dimensionless; PERMK, vertical permeability, in millidarcy (mD); and VSH, dimensionless.

[0024] As a further preferred embodiment of the present invention, the formula for calculating the mud content in step S2 is as follows:

[0025]

[0026] Where POR is the porosity of the current grid, and PHI is... sand and PHI shale These represent the average porosity values ​​of pure sandstone and pure mudstone in the study area, respectively.

[0027] As a further preferred embodiment of the present invention, in step S3, the capillary breakthrough pressure P c-entry Specific steps to obtain:

[0028] Step S3.1: Assume that the grid index K increases from top to bottom, and K=1 is the top layer of the model. Then, for any non-top layer grid coordinate (I, J, K), K≥2, the coordinates of the adjacent grid above it are (I, J, K-1).

[0029] Step S3.2: Define the mesh center depth of coordinates (I, J, K) as D. KThe center depth of the upper grid is D. K-1 Vertical grid center spacing ΔZ=D K –D K-1 ;

[0030] Step S3.3: Perform calculations for each interface from K=2 to K=N (N is the total number of grids in the vertical direction) within each (I, J) column.

[0031] Step S3.4: For each upper grid (I, J, K-1), based on the reservoir's clay content VSH, calculate the capillary breakthrough pressure P that CO2 must overcome to enter grid K-1 using an empirical formula applicable to sandstone reservoirs. c-entry (K-1):

[0032]

[0033] Among them, P c-entry The unit is MPa; the empirical coefficients are a=10 and b=2, that is:

[0034]

[0035] As a further preferred embodiment of the present invention, in step S4, the formula for calculating the vertical pressure difference ΔΦ is:

[0036]

[0037] In the formula, ρ g The average density of CO2 in the supercritical state, in kg / m³ 3 g is the acceleration due to gravity, in m / s²; PRES K PRES represents the pore pressure of the grid with K as the vertical axis, in MPa. K-1 The vertical axis represents the pore pressure of the grid at K-1, in MPa; ΔZ represents the vertical grid center-to-center spacing, in meters.

[0038] If ΔΦ > 0, it indicates that there is an upward driving force for CO2 within the grid. If ΔΦ ≤ 0, it indicates that the pressure difference between the upper and lower grid layers is small, CO2 lacks an upward driving force, and the risk of CO2 vertical breakthrough is zero.

[0039] As a further preferred embodiment of the present invention, in step S5, the effective driving force ΔΦ eff The calculation formula is given, and the unit is MPa.

[0040]

[0041] As a further preferred embodiment of the present invention, the harmonic average calculation method in step S6 is as follows:

[0042]

[0043] Vertical conductivity Tv, measured in mD / m, reflects the ability of an interface to conduct fluid; the larger the Tv, the stronger the conductivity.

[0044] As a further preferred embodiment of the present invention, in step S7, the formula for calculating the vertical breakthrough risk index is:

[0045]

[0046] The larger the Fv value, the greater the risk of CO2 breaking through the vertical seepage channel upwards under the existing pressure field.

[0047] As a further preferred embodiment of the present invention, the optimization of injection and production parameters in step S9 specifically includes: obtaining the CO2 vertical breakthrough risk distribution based on the basic calculation example; appropriately reducing the gas injection rate and upper limit of the gas injection pressure for gas injection wells with high vertical breakthrough risk; appropriately increasing the production allocation for oil production wells with high vertical breakthrough risk; appropriately increasing the gas injection rate and upper limit of the gas injection pressure for gas injection wells with low vertical breakthrough risk; and appropriately decreasing the production allocation for oil production wells with low vertical breakthrough risk.

[0048] In summary, this application includes at least one of the following beneficial technical effects:

[0049] (1) It takes into account both capillary closure and driving potential difference, and has high prediction accuracy. By introducing an empirical formula for capillary breakthrough pressure based on clay content, the capillary closure capacity of the caprock and interlayer is coupled with the vertical pressure potential difference, avoiding the misjudgment caused by traditional methods that only consider permeability or pressure as a single factor. It is especially suitable for oil reservoirs with strong heterogeneity of interlayers, such as sandstone reservoirs.

[0050] (2) The breakthrough judgment is based on objective criteria and does not rely on artificial production layer classification. This invention directly defines the vertical breakthrough risk index Fv based on the static attributes and dynamic pressure field at the grid scale. There is no need to make subjective divisions such as main production layer and non-main production layer in advance. The judgment results are more universal and repeatable and are applicable to all types of oil reservoirs.

[0051] (3) The actual application prediction effect is significant and can effectively avoid the risk of vertical breakthrough. When the present invention was applied to the evaluation of the actual CO2 injection scheme of a sandstone fault block reservoir, the high-risk interface generated and the actual gas saturation vertical breakthrough layer in the later stage of numerical simulation had a consistency rate of more than 90%. The results show that the method can accurately identify the key position of CO2 vertical channeling in advance without relying on re-simulation, providing a reliable basis for timely adjustment of injection and production parameters, implementation of injection avoidance and selective plugging, and effectively reducing the ineffective circulation and recovery rate loss caused by gas channeling.

[0052] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0053] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0054] Figure 1 Flowchart of the method for predicting vertical breakthrough of CO2 flooding in deep fault-block reservoirs provided by the present invention;

[0055] Figure 2 This is a schematic diagram of the X reservoir geological model used in this embodiment of the invention;

[0056] Figure 3 The oil-water permeability curve of the X oil reservoir used in the embodiments of the present invention;

[0057] Figure 4 This is the production history fitting curve of reservoir X in this embodiment of the invention;

[0058] Figure 5 This is the distribution of the vertical breakthrough risk coefficient of reservoir X in this embodiment of the invention;

[0059] Figure 6 This illustrates the distribution of high-risk areas in reservoir X in this embodiment of the invention.

[0060] Figure 7 This illustrates how the extraction rate varies with the gas injection rate in this embodiment of the invention. Detailed Implementation

[0061] The accompanying drawings and descriptions provided herein may have been simplified to illustrate aspects relevant to a clear understanding of the apparatus, systems, and methods described herein, while other aspects that may be found in typical similar devices, systems, and methods have been omitted for clarity. Therefore, those skilled in the art will recognize that other elements and / or operations may be desired and / or necessary for implementing the devices, systems, and methods described herein. However, because such elements and operations are known in the art and do not contribute to a better understanding of this disclosure, a discussion of such elements and operations may not be provided herein for the sake of brevity. Nevertheless, this disclosure is still intended to include all such elements, variations, and modifications to the described aspects that are known to those skilled in the art.

[0062] Implementations are provided throughout this disclosure to make it thorough and fully convey the scope of the disclosed embodiments to those skilled in the art. Numerous specific details, such as embodiments of specific components, apparatuses, and methods, are set forth to provide a thorough understanding of implementations of this disclosure. However, it will be apparent to those skilled in the art that certain specific details disclosed are not required and that implementations may be carried out in different forms. Therefore, implementations should not be construed as limiting the scope of this disclosure. As mentioned above, in some implementations, well-known processes, well-known equipment structures, and well-known technologies may not be described in detail.

[0063] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. For example, the singular forms “a” and “described” as used herein may also be intended to include the plural forms unless the context clearly indicates otherwise. The terms “comprising,” “including,” “containing,” and “having” are inclusive and thus specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Unless specifically determined as a preferred or desired order of execution, the steps, processes, and operations described herein should not be construed as requiring them to be performed in the particular order discussed or shown. It should also be understood that additional or alternative steps may be employed in place of or in combination with the disclosed aspects.

[0064] 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 embodiments of the invention, not all embodiments. 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.

[0065] To address the risk of vertical CO2 breakthrough during CO2 injection development in deep fault-block reservoirs and to optimize production strategies within a safe range, this invention provides a method for predicting vertical breakthrough in CO2 injection for deep fault-block reservoirs, comprising the following steps:

[0066] Step S1: Obtain seismic and well logging data of the fault-block oil reservoir to establish a geological model, obtain fluid parameters, and establish a corresponding numerical simulation model.

[0067] There are many methods for geological modeling. In addition to modeling based on seismic and well logging data, geological models can also be obtained through other methods. Fluid parameters mainly include the composition of the fluid in the well, the phase characteristics of the fluid under certain temperature and pressure conditions, and the relative permeability of oil-water and oil-gas.

[0068] Step S2: Based on production data, perform historical fitting to obtain the following parameters after simulation: Depth (meters, reflecting the vertical depth at the grid center); Pore pressure (Pres, megapascals, MPa); Gas saturation (Sg, dimensionless); Vertical permeability (Permk, millidarcy, mD); and Clay content (VSH, dimensionless).

[0069] The mud content VSH ， The clay content is usually obtained from well logging interpretation or lithofacies modeling results, but some models may lack corresponding parameters. The clay content can be calculated using the following formula.

[0070]

[0071] Where POR is the porosity of the current grid, and PHI is... sand and PHI shale Typical porosity values ​​for pure sandstone and pure mudstone in the study area, respectively.

[0072] Step S3: Obtain the capillary breakthrough pressure. Assume the grid index K increases from top to bottom (K=1 is the top layer of the model). Then, for any non-top-layer grid coordinate (I, J, K) (K≥2), its adjacent grid coordinate above it is (I, J, K-1). Define the center depth of the grid coordinate (I, J, K) as D. K The center depth of the upper grid is D. K-1 Vertical grid center spacing ΔZ=D K –D K-1 (Positive); The following calculations are performed on each interface from K=2 to K=N (N is the total number of grids in the vertical direction) within each coordinate (I, J) column; For each upper grid coordinate (I, J, K-1), the capillary breakthrough pressure that CO2 must overcome to enter the grid is calculated using an empirical formula applicable to sandstone and conglomerate reservoirs, based on its clay content VSH:

[0073]

[0074] Where Pc-entry is in MPa; the empirical coefficients are a=10 and b=2, i.e.:

[0075]

[0076] Step S4: Calculate the vertical potential difference, taking the average density ρ of CO2 in the supercritical state. g = 300 kg / m³, gravitational acceleration g = 9.8 m / s², then the pressure gradient generated by buoyancy per unit height is approximately 0.003 MPa / m. Calculate the upward displacement potential difference ΔΦ between the lower grid K and the upper grid K-1:

[0077]

[0078] In the formula, all units are in MPa, and ΔZ is the vertical spacing determined in S3. If ΔΦ ≤ 0, there is no upward driving force, and the risk of longitudinal breach of the interface is zero.

[0079] Step S5: Calculate the effective driving force. Only when the vertical potential difference exceeds the capillary breakthrough pressure of the upper grid can the remaining driving force drive CO2 into the upper grid. The effective driving force is defined as:

[0080]

[0081] Step S6: Calculate the vertical conductivity of the interface. Using the vertical permeability of two adjacent grids, calculate the harmonic average conductivity between the centers of the two grids, taking into account the vertical spacing.

[0082]

[0083] Tv is measured in mD / m and reflects the fluid conductivity of the interface.

[0084] Step S7, calculate the vertical breakout risk index. Combining effective driving forces and interface transmission rate, define the vertical breakout risk index Fv:

[0085]

[0086] The larger the Fv value, the easier it is for CO2 to break through the capillary seal and flow upwards along the vertical seepage channel under the existing pressure field.

[0087] Step S8: Calculate all calculated interface Fv values ​​and take the 95th percentile of the Fv distribution of the entire model as the threshold Fv. threshold . Fv > Fv threshold The grid interface is marked as a high-risk interface for vertical breakthrough, and the corresponding upper grid coordinates (I, J, K-1) are determined to be the CO2 vertical breakthrough risk zone.

[0088] Step S9: Based on the obtained distribution of the CO2 vertical breakthrough risk zone, dynamically adjust and optimize the injection and production parameters of injection and production wells near the risk zone.

[0089] Example

[0090] This embodiment takes a deep fault-block reservoir (hereinafter referred to as reservoir X) as an example to illustrate in detail a method for predicting the vertical breakthrough of CO2 flooding in deep fault-block reservoirs provided by the present invention.

[0091] Step S1: Obtain seismic data, well logging data, fluid parameters, and reservoir production data for the fault-block reservoir, and establish the corresponding numerical simulation model.

[0092] First, a geological model of reservoir X was obtained based on well logging data, as shown in the attached figure. Figure 2 As shown, based on the well fluid composition analysis of the target reservoir, the original products can be divided into 60 single-carbon array components. To significantly reduce the computational load while ensuring simulation accuracy, 36 components were merged into 9 pseudo-components, including: CO2, N2, Cl, C 2-6 C 7-16 C 17-21 C 22-27 C 28-34 C 35-60+ The molar composition after merging is shown in Table 1.

[0093] Table 1: Molar composition of fluids in well X reservoir

[0094] mol, % 0.75 0.49 7.94 7.09 17.78 17.21 15.20 16.34 17.19

[0095] The corresponding oil-water permeability and oil-gas permeability are as follows: Figure 3 As shown in Table 2.

[0096] Table 2 Oil and gas permeability parameters of reservoir X

[0097] 17.130 0.000 1.000 21.407 0.002 0.629 26.466 0.005 0.423 38.787 0.027 0.186 43.004 0.076 0.109 44.609 0.120 0.079 46.769 0.160 0.049 46.933 0.183 0.037 51.537 0.421 0.026 53.000 0.513 0.023

[0098] Step S2: Perform historical data fitting based on reservoir production data to obtain the following parameters after simulation: Depth (m), reflecting the vertical depth at the grid center; Pore pressure PRES (MPa); Gas saturation Sg (dimensionless); Vertical permeability PERMK (mD); and Shale content VSH (dimensionless).

[0099] Historical data and the fitted production curve are as follows Figure 4 As shown, taking the reservoir and caprock properties of the X reservoir model as an example, the average permeability of the reservoir is 20%, the porosity of pure sandstone obtained from core experiments is 30%, and the porosity of pure mudstone is 5%. The mud content is calculated to be 40% using the following formula.

[0100]

[0101] Step S3: Obtain the breakthrough pressure P of any two adjacent capillary layers within the study area. c-entry Assume the grid index K increases from top to bottom (K=1 is the top layer of the model). Then, for any non-top-layer grid coordinate (I, J, K) (K≥2), its adjacent grid coordinate above it is (I, J, K-1). Define the center depth of the grid coordinate (I, J, K) as D. K The center depth of the upper grid is D. K-1 Vertical grid center spacing ΔZ=D K –D K-1(Positive); The following calculations are performed for each interface from K=2 to K=N within each coordinate (I, J) column; For each upper grid coordinate (I, J, K-1), the capillary breakthrough pressure that CO2 must overcome to enter the grid is calculated using an empirical formula applicable to sandstone reservoirs, based on its clay content VSH:

[0102]

[0103] Among them, P c-entry The unit is MPa; the empirical coefficients are a=10 and b=2, that is:

[0104]

[0105] Based on the mud content VSH=0.4 obtained in step S2, therefore P c-entry With a pressure difference of 0.9 MPa, it can be determined that when the pressure difference between grids exceeds 0.9 MPa, there is a risk of CO2 escaping into the upper grid.

[0106] Step S4: Calculate the vertical pressure difference ΔΦ between any two adjacent layers within the study area. Wherein, the average density of CO2 in the supercritical state is ρ. g Unit: kg / m 3 Gravitational acceleration is g, in m / s²; the grid pore pressure, represented by the vertical axis K, is PRES. K The unit is MPa; the grid pore pressure at the ordinate K-1 is PRES. K-1 The unit is MPa; ΔZ is the vertical spacing determined in step S3, in meters. The vertical pressure difference ΔΦ between the lower grid K and the upper grid K-1 is:

[0107]

[0108] If ΔΦ > 0, it indicates that there is an upward driving force for CO2 within the grid. If ΔΦ ≤ 0, it indicates that the pressure difference between the upper and lower grid layers is small, CO2 lacks an upward driving force, and the risk of CO2 vertical breakthrough is zero.

[0109] Taking a grid K at the top of reservoir X as an example, the vertical grid step size is 20m, and the original formation pressure is 57.05MPa. When gas injection scheme 1 is adopted, the pressure after exhaustion production and CO2 injection is 57.5MPa. The pressure of the caprock grid K-1 above this grid is 56.85MPa, therefore ΔΦ is 0.59MPa.

[0110] Step S5: Calculate the effective driving force ΔΦ eff When ΔΦ > 0, it is necessary to compare the vertical pressure difference ΔΦ between adjacent layers and the capillary breakthrough pressure P. c-entryThe magnitude of the pressure difference, when the vertical pressure difference ΔΦ is greater than the capillary breakthrough pressure P of the upper grid, is determined by... c-entry At that time, the pressure difference between the two pressures is the effective driving force ΔΦ. eff Only then can CO2 be driven into the upper grid, effectively driving force ΔΦ eff , unit MPa.

[0111]

[0112] Taking a certain grid K at the top of the X reservoir as an example, its upward displacement potential difference is less than the capillary pressure, therefore the effective driving force is 0.

[0113] Step S6: Calculate the vertical transmissivity Tv of the interface; the driving force for CO2 longitudinal breakthrough is the effective driving force ΔΦ. eff However, the ease of breakthrough is also affected by reservoir properties, namely the interfacial conductivity Tv between the upper and lower grid layers, and the vertical permeability PERMK of adjacent grids K and K-1. K and PERMK K-1 The vertical conductivity Tv between the two grids, considering the vertical spacing, is obtained by using the harmonic average calculation method, in meters.

[0114]

[0115] The unit of Tv is mD / m, which reflects the conductivity of the interface to the fluid. The larger the Tv, the stronger the conductivity.

[0116] Taking a certain grid K at the top of the X reservoir as an example, by substituting the corresponding values, we obtain that Tv is 1.66 mD / m.

[0117] Step S7: Calculate the vertical breakout risk index Fv. Combining effective driving force and interfacial conduction rate, define the vertical breakout risk index Fv, in m·MPa:

[0118]

[0119] Since the effective driving force of a certain grid K at the top of the X reservoir is 0, its vertical breakthrough risk coefficient is 0. Calculations show that the vertical breakthrough risk coefficients of other grids range from 0 to 1.12, as detailed below. Figure 5 As shown.

[0120] Step S8: Obtain the distribution of the CO2 vertical breakthrough risk zone; statistically analyze all calculated grid Fv values, and take the 90th percentile of the full model Fv distribution as the threshold Fvthreshold1; set Fv > Fv threshold1 The grid markings are used to identify high-risk regions that breach the vertical boundary; the 50th percentile of the Fv distribution of the entire model is taken as the threshold Fv. threshold2 ; Fv threshold1> Fv >Fv threshold2 The grid is marked as a medium-risk area for vertical breakthrough, with Fv < Fv threshold2 The grid markings indicate vertical breakthroughs in low-risk areas.

[0121] Statistical analysis and calculations were performed on the grid of the entire X reservoir area, and high-risk areas (such as...) were marked. Figure 6 (As shown).

[0122] Step S9: Based on the obtained distribution of the CO2 vertical breakthrough risk zone, dynamically adjust and optimize the injection and production parameters of injection and production wells near the risk zone.

[0123] Based on the obtained CO2 vertical breakthrough risk zone distribution, the injection and production rates were optimized. When the CO2 vertical breakthrough risk coefficient of the scheme is greater than 1.2, the breakthrough risk of the scheme is considered to be relatively high, and the gas injection rate and the upper limit pressure of the gas injection need to be appropriately reduced. Finally, the curve of the recovery degree as a function of the gas injection rate within the safe range was obtained through simulation, as shown in the figure. Figure 7 As shown, when the gas injection rate exceeds 0.086HCPV / a, there is a risk coefficient of CO2 vertical breakthrough in some grids that is greater than 1.2. Therefore, the optimal gas injection rate for recovery within the safe range is 0.086HCPV / a.

[0124] Through steps S1 to S9 above, this embodiment fully demonstrates how to use the method provided by the present invention to systematically and efficiently obtain the vertical breakthrough risk distribution of CO2 flooding in deep oil reservoirs, and obtain the optimal injection and production parameters within the safe range based on its specific distribution, thus verifying the effectiveness and practicality of the method of the present invention.

[0125] 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 scope of the present invention shall fall within the scope of the present invention.

[0126] The above is the complete patent specification. This specification includes all necessary parts such as the technical field, background art, invention content, description of drawings, and detailed embodiments. It is formatted correctly, complete in content, and meets the relevant requirements of the Patent Law and its Implementing Regulations.

Claims

1. A method for predicting vertical breakthrough of CO2 flooding in deep fault-block oil reservoirs, characterized in that, Includes the following steps: Step S1: Obtain seismic, logging, fluid parameters, and reservoir production data for the fault-block reservoir, and establish a numerical simulation model; Step S2: Based on the reservoir production data in Step S1, perform historical fitting to obtain the simulated parameters; Step S3: Obtain the breakthrough pressure P of any two adjacent capillary layers within the study area. c-entry ; Step S4: Calculate the vertical pressure difference ΔΦ between any lower grid K and the upper grid K-1 within the study area; Step S5: Calculate the effective driving force ΔΦ at adjacent interface layers. eff When the vertical pressure difference ΔΦ > 0, compare the vertical pressure difference ΔΦ and capillary breakthrough pressure P at adjacent interface layers. c-entry The magnitude of the pressure difference, when the vertical pressure difference ΔΦ is greater than the capillary breakthrough pressure P of the upper grid, is determined by... c-entry At that time, the pressure difference between the two pressures is the effective driving force ΔΦ. eff Only then can CO2 be driven into the upper grid; Step S6: Calculate the vertical conductivity Tv of the interface between the upper and lower grid layers, and combine it with the vertical permeability PERMK of the adjacent two grids K and K-1. K and PERMK K-1 The vertical conductivity T between two grids, considering the vertical spacing, is obtained using the harmonic averaging method. v ; Step S7: Combine the effective driving force ΔΦ eff Calculate the vertical breakthrough risk index Fv based on the vertical conductivity Tv of the interface; Step S8: Obtain the vertical risk zone distribution of CO2, calculate the Fv value of the entire model, and take the 90th quantile of the Fv distribution of the entire model as the threshold Fv. threshold , Fv > Fv threshold The grid markings are high-risk areas for vertical breakthroughs; the full model F is taken. v The 50th percentile of the distribution is used as the threshold Fv threshold2 , will Fv threshold1 > Fv > Fv threshold2 The grid is marked as a medium-risk area for vertical breakthrough, with Fv < Fv threshold2 The grid markings indicate vertical breaches of low-risk areas; Step S9: Optimize injection and production parameters. Based on the obtained distribution of CO2 vertical breakthrough risk zone, dynamically adjust and optimize the injection and production parameters of injection and production wells within the risk zone.

2. The method for predicting vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein the fluid parameters in step S1 mainly include the composition of the fluid in the well, the phase characteristics of the fluid under certain temperature and pressure conditions, and the relative permeability of oil-water and oil-gas.

3. The method for predicting vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein the simulated parameters in step S2 include: Reflects the vertical depth at the center of the grid, in meters (m). Pore ​​pressure PRES, in megapascals (MPa); Gas saturation Sg, dimensionless; Vertical permeability PERMK, in millidarcy mD; clay content VSH, dimensionless.

4. The method for predicting vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 3, wherein the formula for calculating the clay content in step S2 is as follows: in, POR represents the porosity of the current mesh, and PHI represents the porosity of the mesh. sand and PHI shale These represent the average porosity of pure sandstone and pure mudstone in the study area, respectively.

5. The method for predicting longitudinal breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein the capillary breakthrough pressure P in step S3... c-entry Specific steps to obtain: Step S3.1: Assume that the grid index K increases from top to bottom, and K=1 is the top layer of the model. Then, for any non-top layer grid coordinate (I, J, K), K≥2, the coordinates of the adjacent grid above it are (I, J, K-1). Step S3.2: Define the mesh center depth of coordinates (I, J, K) as D. K The center depth of the upper grid is D. K-1 Vertical grid center spacing ΔZ=D K –D K-1 ; Step S3.3: Calculate for each interface from K=2 to K=N within each (I, J) column, where N is the total number of grids in the vertical direction; Step S3.4: For each upper grid coordinate (I, J, K-1), based on the reservoir's clay content VSH, calculate the capillary breakthrough pressure P that CO2 must overcome to enter grid K-1 using an empirical formula applicable to sandstone reservoirs. c-entry (K-1): The empirical coefficients are taken as a=10 and b=2, that is: In the formula, P c-entry The unit is MPa.

6. In the method for predicting the vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, the formula for calculating the vertical pressure difference ΔΦ in step S4 is: In the formula, ρ g The average density of CO2 in the supercritical state, in kg / m³ 3 g is the acceleration due to gravity, in m / s²; PRES K The vertical axis represents the pore pressure of the grid, expressed in MPa. PRES K-1 The grid pore pressure is represented by the vertical axis K-1, in MPa. ΔZ is the vertical grid center spacing, in meters; If ΔΦ > 0, it indicates that there is an upward driving force for CO2 within the grid. If ΔΦ ≤ 0, it indicates that the pressure difference between the upper and lower grid layers is small, CO2 lacks an upward driving force, and the risk of CO2 vertical breakthrough is zero.

7. The method for predicting longitudinal breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein in step S5, the effective driving force ΔΦ eff The calculation formula is: Efficient driving force ΔΦ eff The unit is MPa.

8. The method for predicting vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein the harmonic average calculation method in step S6 is as follows: Vertical conductivity Tv, measured in mD / m, reflects the ability of an interface to conduct fluid; the larger the Tv, the stronger the conductivity.

9. The method for predicting vertical breakthrough of CO2 flooding in deep faulted reservoirs according to claim 1, wherein in step S7, the formula for calculating the vertical breakthrough risk index is: The larger the Fv value, the greater the risk of CO2 breaking through the vertical seepage channel upwards under the existing pressure field.

10. The method for predicting vertical breakthrough of CO2 flooding in deep faulted block reservoirs according to claim 1, wherein optimizing injection and production parameters in step S9 specifically includes: Based on the risk distribution of CO2 vertical breakthrough, the gas injection rate and upper limit of gas injection pressure should be appropriately reduced for gas injection wells with high risk of vertical breakthrough, while the production allocation can be appropriately increased for oil production wells with high risk of vertical breakthrough. For gas injection wells with low risk of vertical breakthrough, the gas injection rate and upper limit of gas injection pressure should be appropriately increased; for oil production wells with low risk of vertical breakthrough, the production allocation should be appropriately reduced.

Images