A rule analysis method and system for water aggregation interference phenomenon

Abstract

The application discloses a rule analysis method for water-polymer interference, which comprises the following steps: establishing a three-dimensional fine geological model about an oilfield region to be researched; converting the three-dimensional fine geological model into a corresponding flow line numerical model according to fluid characteristics, temperature and pressure change conditions and dynamic production parameters of the current oilfield region; reducing the flow line numerical model into a multi-stage flow line field including a water flooding stage, a polymer flooding stage and different polymer injection PV numbers under water-polymer co-flooding; and comprehensively analyzing the multi-stage flow line field. The application can intuitively observe and analyze the water-polymer interference rule, provides guidance for reducing the water-polymer interference degree, and provides a reference for the development of similar oilfields.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and system for analyzing the regularity of water accumulation interference phenomena. Background Technology

[0002] For the same time, the same block, and the same reservoir, when both water-drive wells (water injection wells) and polymer-drive wells (polymer injection wells) exist (referred to as co-flooding), mutual interference between water-drive and polymer-drive inevitably occurs. The Bohai Bay oilfields are currently key offshore oilfields under development. During their development, these fields underwent a transition from water-drive to polymer-drive, followed by densification based on the original nine-spot well network, and the conversion of some production wells to water injection, resulting in the current row-shaped well network. While this process improved oil recovery to some extent, it also inevitably led to interference between polymers and water. This is mainly due to the significant difference in flow capacity between polymers and water, and the molecular diffusion and mechanical dispersion processes that occur between polymer and water molecules during displacement. This results in an uncoordinated injection-production relationship at the interface between polymer-drive and water-drive, limiting the polymer-driven oil recovery capacity at this boundary. Taking an oilfield in the Bohai Bay as an example, the original well network of the oilfield was a reverse nine-point well network with one injection and eight production wells. Eight water injection wells in the basic network were put into operation between 2000 and 2006, and were gradually converted to polymer injection around 2008. Between 2015 and 2016, the well network in this block was adjusted, with 12 infill water wells drilled and some production wells converted to water injection. The well network was changed from a reverse nine-point network to a row-shaped network. The development effect improved significantly after the adjustment, but the oil production of the affected wells subsequently declined rapidly, showing obvious water-polymerization interference.

[0003] To address the potential interference issues in water-polymer co-flooding, existing technologies have proposed several solutions: First, suitable blocks were selected, their production dynamics were analyzed, and the development technology limits of these blocks were studied, leading to the optimal development method for water-polymer co-flooding in Class II reservoirs, ultimately maximizing oilfield recovery. Second, it is argued that when both water injection wells and polymer injection wells exist in the same block, unless the wells are far apart, mutual interference between water molecules and polymer molecules is inevitable, which can reduce the oil displacement efficiency of polymers to some extent. Third, by employing a combination of numerical and physical models, the distribution patterns of the water-polymer contact zone, the distribution patterns of horizontal and vertical oil saturation, the recovery rate during the water-polymer co-flooding stage, and the water cut variation patterns of production wells at different locations were studied and analyzed under different injection intensities.

[0004] However, existing technologies lack a clear scheme for analyzing the patterns of water accumulation interference, so as to provide a basis for reducing the degree of water accumulation interference and for the development and adjustment of other similar oil fields. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for analyzing the patterns of water-polymerization interference phenomena, comprising: establishing a three-dimensional fine geological model of the oilfield area under study; converting the three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure variations, and dynamic production parameters of the current oilfield area; restoring the streamline numerical model into a multi-stage streamline field including the water-drive stage, the polymer-drive stage, and different polymer injection PV numbers under water-polymerization co-drive; and performing a comprehensive analysis of the multi-stage streamline field.

[0006] Preferably, the step of establishing a three-dimensional fine geological model of the oilfield area to be studied includes: using the reservoir characteristic information, physical property parameters and sedimentary facies characteristic information of each single well in the current oilfield area as quality control data, and using a stochastic simulation algorithm to model the geological model, thereby constructing the three-dimensional fine geological model including lithology model, porosity attribute model, permeability attribute model and oil saturation.

[0007] Preferably, the dynamic production parameters include time-based well completion and workover data, production data, and pressure data. The well completion and workover data includes, but is not limited to, well diameter, perforation filling thickness, perforation filling time, workover layer location, production injection time, fracturing parameters, and water shut-off parameters. The production data includes, but is not limited to, oil production, fluid production, water injection, oil-gas ratio, and oil-water ratio for each individual well. The pressure data includes, but is not limited to, bottom hole pressure, shut-in static pressure, and formation pressure for each individual well.

[0008] Preferably, the step of converting the three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure variation conditions, and dynamic production parameters of the current oilfield area includes: coarsening the three-dimensional fine geological model; and performing historical fitting on the coarsened model to form the streamline numerical model based on the fluid characteristics, temperature and pressure variation conditions, and dynamic production parameters of the current oilfield area.

[0009] Preferably, during the historical data fitting process, using reserves, pressure, oil production, liquid production, and water cut as indicators, a constant liquid volume control method is adopted to first fit the indicators of the entire oilfield area, and then fit the indicators of each individual well within the area.

[0010] Preferably, the comprehensive analysis step of the multi-stage streamline field includes: determining the distribution of the number of lines and the degree of aggregation of the number of lines in the multi-stage streamline field, and analyzing the injection volume distribution characteristics and fluid velocity distribution characteristics of different stages.

[0011] On the other hand, the present invention also provides a system for analyzing the regularity of water-polymerization interference phenomena, comprising: a geological model generation module configured to establish a three-dimensional fine geological model of the oilfield area to be studied; a numerical model generation module configured to convert the three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure variation conditions, and dynamic production parameters of the current oilfield area; a streamline field generation module configured to restore the streamline numerical model into a multi-stage streamline field including the water-drive stage, polymer-drive stage, and different polymer injection PV numbers under water-polymerization co-drive; and a regularity analysis module configured to perform comprehensive analysis on the multi-stage streamline field.

[0012] Preferably, the geological model generation module is further used to use the reservoir characteristic information, physical property parameters and sedimentary facies characteristic information of each single well in the current oilfield area as quality control data, and to use a stochastic simulation algorithm to build a geological model, thereby constructing the three-dimensional fine geological model including lithology model, porosity attribute model, permeability attribute model and oil saturation.

[0013] Preferably, the numerical model generation module includes: an initialization processing unit configured to coarsen the three-dimensional fine geological model; and a model fitting unit configured to perform historical fitting on the coarsened model to form the streamline numerical model based on the fluid characteristics of the current oilfield area, the temperature and pressure change conditions, and the dynamic production parameters.

[0014] Preferably, the pattern analysis module is further configured to determine the distribution of the number of lines and the degree of aggregation of the number of lines in the multi-stage streamline field, and to analyze the injection volume distribution characteristics and fluid velocity distribution characteristics of different stages.

[0015] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0016] This invention discloses a method and system for analyzing the patterns of water-polymerization interference. This method and system address the problem of unclear patterns in water-polymerization interference in oil and gas fields developed using a water-polymerization co-drive approach or in transitional zones between water-drive and polymer-drive. Specifically, it employs the streamline method to derive a scheme for analyzing the patterns of water-polymerization interference. During water-polymerization co-drive development, by analyzing the streamline fields of water injection and polymer injection wells, the patterns of water-polymerization interference can be directly observed and analyzed, providing guidance for reducing the degree of water-polymerization interference and serving as a reference for the development of similar oil fields.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0019] Figure 1 This is a flowchart illustrating the steps of the method for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application.

[0020] Figure 2 This is a schematic diagram illustrating the construction effect of the multi-stage streamline field model in the method for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application.

[0021] Figure 3 This is a schematic diagram illustrating the construction effect of a multi-stage streamline field model for a specific oilfield region in the method for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application.

[0022] Figure 4 This is a schematic diagram of the structure of the system for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0024] Furthermore, the steps illustrated in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than that shown here.

[0025] For the same time, the same block, and the same reservoir, when both water-drive wells (water injection wells) and polymer-drive wells (polymer injection wells) exist (referred to as co-flooding), mutual interference between water-drive and polymer-drive inevitably occurs. The Bohai Bay oilfields are currently key offshore oilfields under development. During their development, these fields underwent a transition from water-drive to polymer-drive, followed by densification based on the original nine-spot well network, and the conversion of some production wells to water injection, resulting in the current row-shaped well network. While this process improved oil recovery to some extent, it also inevitably led to interference between polymers and water. This is mainly due to the significant difference in flow capacity between polymers and water, and the molecular diffusion and mechanical dispersion processes that occur between polymer and water molecules during displacement. This results in an uncoordinated injection-production relationship at the interface between polymer-drive and water-drive, limiting the polymer-driven oil recovery capacity at this boundary. Taking an oilfield in the Bohai Bay as an example, the original well network of the oilfield was a reverse nine-point well network with one injection and eight production wells. Eight water injection wells in the basic network were put into operation between 2000 and 2006, and were gradually converted to polymer injection around 2008. Between 2015 and 2016, the well network in this block was adjusted, with 12 infill water wells drilled and some production wells converted to water injection. The well network was changed from a reverse nine-point network to a row-shaped network. The development effect improved significantly after the adjustment, but the oil production of the affected wells subsequently declined rapidly, showing obvious water-polymerization interference.

[0026] To address the potential interference issues in water-polymer co-flooding, existing technologies have proposed several solutions: First, suitable blocks were selected, their production dynamics were analyzed, and the development technology limits of these blocks were studied, leading to the optimal development method for water-polymer co-flooding in Class II reservoirs, ultimately maximizing oilfield recovery. Second, it is argued that when both water injection wells and polymer injection wells exist in the same block, unless the wells are far apart, mutual interference between water molecules and polymer molecules is inevitable, which can reduce the oil displacement efficiency of polymers to some extent. Third, by employing a combination of numerical and physical models, the distribution patterns of the water-polymer contact zone, the distribution patterns of horizontal and vertical oil saturation, the recovery rate during the water-polymer co-flooding stage, and the water cut variation patterns of production wells at different locations were studied and analyzed under different injection intensities.

[0027] To address the lack of a clear scheme for analyzing the patterns of water-accumulation interference in existing technologies, this application proposes a method and system for analyzing the patterns of water-accumulation interference. The method and system include: steps for establishing a three-dimensional fine geological model of the oilfield area under study; steps for converting the constructed three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure variations, and dynamic production parameters of the current oilfield area; steps for restoring the constructed streamline numerical model into a multi-stage streamline field including the water-drive stage, the polymer-drive stage, and different polymer injection PV numbers; and steps for comprehensively analyzing the water-accumulation patterns of the current multi-stage streamline field.

[0028] Thus, the present invention provides an implementable analysis scheme for water accumulation interference phenomena in specific oilfield areas, thereby providing a basis for reducing the degree of water accumulation interference and also providing a basis for the development and adjustment of other similar oilfields.

[0029] It should be noted that the application of the following method for analyzing the regularity of water-polymerization interference phenomenon described in the embodiments of the present invention is for oilfield areas that adopt water-polymerization co-drive extraction methods, or for oilfield areas with a transition zone between water-drive and polymer-drive.

[0030] Figure 1 This is a flowchart illustrating the steps of a method for analyzing the patterns of water accumulation interference phenomena according to an embodiment of this application. See below for reference. Figure 1 The implementation process of the method for analyzing the regularity of water accumulation interference phenomenon (hereinafter referred to as the "regularity analysis method") described in the embodiments of the present invention will be explained in detail.

[0031] Step S110 establishes a three-dimensional fine geological model of the oilfield area to be studied. In step S110, the reservoir condition characteristics, physical property parameters, sedimentary facies characteristics, and other single-well information corresponding to each single well in the current oilfield area are used as the basic data for quality control. Geological understanding is used as the inter-well trend control method, and a stochastic simulation algorithm is used for modeling, thereby constructing a three-dimensional fine geological model including lithology model, porosity attribute model, permeability attribute model, and oil saturation.

[0032] The actual modeling process includes: loading basic data; preprocessing the basic data to achieve data quality control; using the preprocessed basic data as the quality control conditions and foundation for constructing the model, thereby completing the construction of the initial geological model; performing grid design and rationalization analysis on the initial model; and establishing different types of models, such as lithology models and attribute models (porosity, permeability, saturation), based on the gridded initial model, thus forming a three-dimensional fine geological model for the current oilfield area under study. During the construction of the fine geological model, it is necessary to continuously control the quality of the following model parameters and gradually determine the optimal parameters: model area, grid step size, total number of grids, oil-water-dissolved gas three-phase flow characteristics, distribution characteristics of homogeneous single reservoirs, effective reservoir thickness, porosity, permeability, initial oil saturation, bound water saturation, and residual oil saturation.

[0033] In one embodiment, a conceptual refined geological model (three-dimensional refined geological model) of oilfield X can be established based on information such as reservoir conditions, physical properties, and sedimentary facies characteristics. The model parameters of the current conceptual refined geological model are: model area 0.875 km × 0.875 km = 0.766 km². 2 The grid size is 5m×5m×1m, with a total of 21.5×10⁴ grids. The flow is three-phase: oil-water-dissolved gas. The reservoir is homogeneous and single-phase, with a top depth of 1660m. The effective thickness is 7m. The porosity is 0.27. The permeability is 1162.3×10³μm². The initial oil saturation is 0.64. The bound water saturation is 0.34. The residual oil saturation is 0.21.

[0034] Step S120 converts the three-dimensional fine geological model constructed in step S110 into a streamline numerical model for the current oilfield area under study, based on the oilfield fluid characteristics, temperature and pressure variation conditions, and dynamic production parameters of the current oilfield area under study.

[0035] In step S120, the three-dimensional fine geological model constructed in step S110 is first coarsened to form a coarsened geological model. Specifically, the three-dimensional fine geological model is coarsened, and information such as the oilfield fluid characteristics, formation temperature distribution characteristics and variation conditions, formation pressure distribution characteristics and variation conditions, and dynamic production parameters corresponding to the oilfield area are used as verification conditions for the coarsening process. The changes of different types of attributes before and after model coarsening are continuously checked to ensure that the same attribute remains consistent before and after, thereby guaranteeing the quality of coarsening.

[0036] Then, based on the oilfield fluid characteristics, temperature and pressure variation conditions (including at least: formation temperature distribution characteristics and variation conditions and formation pressure distribution characteristics and variation conditions) and dynamic production parameters of the current oilfield area under study, the coarsened model is historically fitted to form a streamline numerical model. In this embodiment of the invention, the streamline numerical model is constructed based on the dynamic production parameters of the current oilfield area under study.

[0037] Furthermore, since dynamic data refers to all data that changes continuously over time, the dynamic production parameters in this embodiment of the invention include, but are not limited to, time-based well completion data, well workover data, production data, temperature data, and pressure data. Well completion and workover data include, but are not limited to, well diameter data, perforation filling thickness, perforation filling time, workover layer location, production injection time, fracturing parameters, and water shut-off parameters for each individual well within the region. Production data includes, but is not limited to, oil production, fluid production, water injection volume, oil-gas ratio, and oil-water ratio for each individual well. Pressure data includes, but is not limited to, bottom hole pressure, shut-in static pressure, and formation pressure for each individual well.

[0038] Furthermore, in the historical fitting process of step S120, using reserves, pressure, oil production, liquid production and water cut as (target) indicators, a constant liquid volume control method is adopted to first fit each target indicator of the entire oilfield area, and then fit each target indicator of each single well in the current oilfield area.

[0039] Specifically, in the process of historical fitting of the streamline numerical model in this embodiment of the invention, it mainly includes two parts: reserve fitting and production history fitting. The fitting indicators include target parameters such as reserves, pressure, oil production, fluid production, and water cut. The basic principles for historical fitting of the coarsened geological model include: ① The model is controlled by a constant fluid volume method; ② First, the indicators of the entire area are fitted, including reserves, pressure, water cut, fluid production, and oil production, etc., among which the fitting of reserves takes priority over the fitting of dynamic indicators; ③ After the indicators of the entire area are well fitted, the indicators of individual wells are then fitted, including pressure, water cut, fluid production, and oil production, etc.; ④ In the process of fitting the entire area, the main basis is the production dynamic trend parameters of the area and each individual well over the past 10 years, and when fitting individual wells, the fitting is mainly based on the production time as the axis, focusing on wells that are still producing and shut-down wells with high cumulative oil production.

[0040] In constructing the streamline numerical model, it is necessary to continuously fit and control the model parameters of the streamline numerical model and gradually determine the optimal parameters: grid step size; total number of grids; original formation pressure; underground crude oil viscosity; normalized relative permeability curve; injection-production well network structure characteristics before well network densification (including: well network structure type, number and location of water injection wells, number and location of oil production wells, well spacing between water injection wells and each oil production well, well spacing between each injection-production well, etc.); injection-production well network structure characteristics after well network densification (including: well network structure type, number and location of water injection wells, number and location of oil production wells, ratio of water injection wells to oil production wells, well spacing between water injection wells and each oil production well, well spacing characteristics between each injection-production well, etc.); characteristic parameters related to injected polymers; characteristic parameters related to injected water; production and development history data (including: water drive stage, polymer drive stage, and different water-polymer co-drive stages).

[0041] In one embodiment, a conceptual streamline numerical model (streamline numerical model) of the current oilfield area under study can be established based on the oilfield fluid characteristics, temperature and pressure conditions, and dynamic development history of the X oilfield. The model parameters of the current conceptual streamline numerical model are: grid step size 10m×10m×1m, total number of grids 5.4×104; original formation pressure 17.1MPa; underground crude oil viscosity 17.1mPa·s; normalized relative permeability curve; before well densification, it was a reverse nine-point well network with one water injection well and eight production wells, with a well spacing of 350m; after well densification, it is a row-shaped well network with a water injection well to production well ratio of 1:2, a well spacing of 175m, and a well row spacing of 350m. The original basic water injection wells were converted to polymer injection wells, and some basic production wells were converted to water injection wells; model development history: water drive 0.45PV + polymer drive 0.4PV + water-polymer co-drive (water injection rate 0.06PV / year, polymer injection rate 0.045PV / year).

[0042] Step S130 restores the streamline numerical model constructed in step S120 into a multi-stage streamline field including the water-drive stage, the polymer-drive stage, and different polymer injection PV numbers under water-polymer co-drive.

[0043] In step S130, it is necessary to establish the streamline field of the oilfield streamline numerical model corresponding to the current oilfield area, specifically including the streamline field of the water drive stage, the streamline field of the polymer drive stage, and the streamline field of different polymer injection PV numbers under water-polymer co-drive.

[0044] Specifically, based on the premise that fluids and rocks are incompressible, and by following the basic principles of mass conservation, energy conservation, and momentum conservation, the three-dimensional streamline numerical model is reduced to a series of one-dimensional linear models based on the stages of water injection, polymer injection, and water-polymer co-drive, thereby establishing the streamline field (i.e., multi-stage streamline field) of the oilfield concept streamline numerical model corresponding to the oilfield area under study.

[0045] Figure 2This is a schematic diagram illustrating the construction effect of the multi-stage streamline field model in the method for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application. Figure 2 This paper presents a streamline numerical model based on the X oilfield, and establishes streamline fields including the water drive stage based on the current three-dimensional streamline numerical model (see [link]). Figure 2 (a)), Streamline field of the polymerization stage (see Figure 2 (b) 0.1PV streamline field of polymer injection under hydropolymerization (see Figure 2 (c) ), 0.2PV streamline field of water-driven polymerization (see...) Figure 2 (d) includes a multi-stage streamline field.

[0046] After establishing the multi-stage streamline field model, proceed to step S140. Step S140 performs a comprehensive analysis of the patterns of water accumulation interference in the multi-stage streamline field constructed in step S130.

[0047] In step S140, based on the distribution of the number of lines and the degree of aggregation of the number of lines in each streamline field model established in step S140, it is necessary to analyze the characteristics of the injection volume distribution and the fluid velocity distribution at different stages. Specifically, based on the streamline field model at each stage, it is necessary to analyze the correlation between the distribution of the number of lines and each time stage, the correlation between the distribution of the degree of aggregation of the number of lines and each time stage, and other information to determine the different types of distribution patterns, such as the distribution patterns of injection volume (water injection volume, polymer injection volume), the distribution patterns of injected fluid velocity, and the distribution patterns of flow direction at different stages. Furthermore, it is necessary to analyze the impact of the aforementioned series of distribution patterns on the production status of each single well (water injection well, polymer injection well, production well, etc.) in the current area under study.

[0048] In a comprehensive analysis of the streamline field of water injection and polymer injection wells (reference) Figure 2 For wells with large injection volumes, the number of streamlines emanating from the surfaces of the grid blocks is greater; for wells with small injection volumes, the number of streamlines emanating from the surfaces of the grid blocks is less. In regions with high flow velocities, a greater number of streamlines can be traced, while in regions with low flow velocities, fewer streamlines can be traced. In this way, the water aggregation and co-drive interference patterns can be directly observed from the constructed multi-stage streamline field model, and the results of the pattern analysis can be recorded and collected.

[0049] The following section uses the T oilfield in the northern part of Liaodong Bay in the Bohai Sea as an example. This oilfield adopts a water-accumulation co-drive development method. The process involved in the analysis of the above-mentioned water-accumulation interference phenomenon in the T oilfield is explained in detail:

[0050] (1) Based on single-well data as the basic control data and geological understanding as the inter-well trend control method, a stochastic simulation algorithm is used to construct a three-dimensional fine geological model. This is combined with reservoir research, and the simulation results are repeatedly adjusted to ultimately determine a more reasonable three-dimensional fine geological model. The specific modeling process includes: data loading and quality control, structural modeling and structural model quality control, model mesh design and rationality analysis, establishment of lithological models, and establishment of attribute models (porosity, permeability, saturation), etc.

[0051] (2) Coarsen the fine geological model, check the changes in properties before and after coarsening, and ensure the quality of coarsening; then initialize the model and establish a streamline numerical model. The establishment of the streamline numerical model relies on the dynamic production parameters of the oilfield. Dynamic data refers to all time-related data, including well completion and workover data, production data, pressure data, etc. Well completion data mainly includes well diameter, perforation and repair thickness, perforation and repair time, formation, production injection time, fracturing, water shut-off, etc.; production data mainly includes single-well oil production, fluid production, water injection, oil-gas ratio, and oil-water ratio, etc.; pressure data mainly includes bottom hole pressure, shut-in static pressure, and formation pressure, etc.

[0052] (3) Historical fitting of the streamline numerical model mainly includes two parts: reserve fitting and production history fitting. The fitting indicators include: reserves, pressure, oil production, liquid production, water cut, etc. The basic principles of historical fitting of the model are: ① The model control method adopts a constant liquid production method; ② First, fit the indicators of the whole area, including reserves, pressure, water cut, liquid production, oil production, etc., among which the fitting of reserves should take priority over the fitting of dynamic indicators; ③ After the indicators of the whole area are well fitted, then fit the indicators of individual wells, including pressure, water cut, liquid production, oil production, etc.; ④ The overall fitting focuses more on the production dynamic trend of the past 10 years, while the fitting of individual wells takes the production time as the axis and focuses on wells that are still producing and shut-down wells with high cumulative oil production. The streamline numerical model of this oilfield has a good overall fitting effect. From the perspective of individual well fitting, about 92% of the individual well fitting effects are close to the actual effects, and the changing trends are consistent.

[0053] (4) Establish the streamline field of the oilfield streamline numerical model, specifically including the streamline field of the water drive stage, the streamline field of the polymer drive stage, and the streamline field of the water-polymer co-drive with different polymer injection PV numbers. Figure 3 This is a schematic diagram illustrating the construction effect of a multi-stage streamline field model for the T oilfield region in the method for analyzing the regularity of water accumulation interference phenomena according to an embodiment of this application. For example... Figure 3 As shown, Figure 3 (a) Figure 3 (b) Figure 3 (c) and Figure 3(d) The streamline field models for the polymer flooding stage, the polymer injection with a PV number of 0.045, the polymer injection with a PV number of 0.09, and the polymer injection with a PV number of 0.135 are shown respectively for the T oilfield area.

[0054] (5) Comprehensive analysis of the streamline field of water injection and polymer injection wells, taking the W4-4 polymer injection well group as an example (e.g.) Figure 3 (As shown). From the streamline field of the W4-4 well group, it can be seen that when there is no water-polymer co-drive, the injected polymer from W4-4 mainly flows to the surrounding wells W3-2, D08, W4-3, D09, W5-4, C06, E4-5, and D12. When the water-polymer co-drive injection reaches 0.045 PV, due to the influence of water injection from D14 well, the amount of polymer flowing from W4-4 well to D08, W3-2, and C06 wells decreases. When the water-polymer co-drive injection reaches 0.135 PV, D22 well is also put into production. Because W4-4 well is simultaneously affected by the water injection wells D14 and D22 on both the north and south sides, the polymer injected from W4-4 well mainly flows to the surrounding wells W4-3, D08, and E4-5 wells. Wells W5-4, D12, D09, and W3-2 are no longer affected by the polymer injection effect of W4-4 well.

[0055] In summary, in the absence of water-polymer co-drive, the polymer propagates uniformly in all directions; in the water-polymer co-drive stage, the injection well has a significant impact on the polymer's seepage field, and the polymer's sweep range is significantly lower. This seepage law is consistent with the seepage law of the conceptual model.

[0056] On the other hand, based on the above-mentioned method for analyzing the patterns of water-flooding interference, this embodiment of the invention also provides a system for analyzing the patterns of water-flooding interference (hereinafter referred to as the "pattern analysis system"). It should be noted that the application of the pattern analysis system for water-flooding interference described in this embodiment of the invention is for oilfield areas employing both water-flooding and polymer-flooding extraction methods, or for oilfield areas with a transitional zone between water-flooding and polymer-flooding.

[0057] Figure 4 This is a schematic diagram of the system for analyzing the patterns of water accumulation interference phenomena according to an embodiment of this application. Figure 4 As shown, the regularity analysis system described in this embodiment of the invention includes: a geological model generation module 41, a numerical model generation module 42, a streamline field generation module 43, and a regularity analysis module 44.

[0058] Specifically, the geological model generation module 41 is implemented according to the method described in step S110 above, and is configured to establish a three-dimensional fine geological model of the oilfield area to be studied; the numerical model generation module 42 is implemented according to the method described in step S120 above, and is configured to convert the constructed three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure change conditions and dynamic production parameters of the current oilfield area; the streamline field generation module 43 is implemented according to the method described in step S130 above, and is configured to restore the constructed streamline numerical model into a multi-stage streamline field including the water drive stage, the polymer drive stage, and different polymer injection PV numbers under water-polymer co-drive; the regularity analysis module 44 is implemented according to the method described in step S140 above, and is configured to perform a comprehensive analysis of the constructed multi-stage streamline field for water-polymer interference phenomena.

[0059] Furthermore, in this embodiment of the invention, the geological model generation module 41 is also used to use the reservoir characteristic information, physical property parameters and sedimentary facies characteristic information of each single well in the current oilfield area as quality control data, and to use a stochastic simulation algorithm to model the geological model, thereby constructing the three-dimensional fine geological model including lithology model, porosity attribute model, permeability attribute model and oil saturation.

[0060] Furthermore, in this embodiment of the invention, the numerical model generation module 42 includes an initialization processing unit 421 and a model fitting unit 422. The initialization processing unit 421 is configured to coarsen the current three-dimensional fine geological model. The model fitting unit 422 is configured to perform historical fitting on the coarsened model based on the fluid characteristics, temperature and pressure variations, and dynamic production parameters of the current oilfield area, thereby forming a corresponding streamline numerical model.

[0061] Furthermore, in this embodiment of the invention, the pattern analysis module 44 is also configured to determine the distribution of the number of lines and the degree of aggregation of the number of lines in the constructed multi-stage streamline field, and to analyze the distribution characteristics of the injection volume and the distribution characteristics of the fluid velocity in different stages.

[0062] This invention discloses a method and system for analyzing the patterns of water-polymerization interference. This method and system address the problem of unclear patterns in water-polymerization interference in oil and gas fields developed using a water-polymerization co-drive approach or in transitional zones between water-drive and polymer-drive. Specifically, it employs the streamline method to derive a scheme for analyzing the patterns of water-polymerization interference. During water-polymerization co-drive development, by analyzing the streamline fields of water injection and polymer injection wells, the patterns of water-polymerization interference can be directly observed and analyzed, providing guidance for reducing the degree of water-polymerization interference and serving as a reference for the development of similar oil fields.

[0063] When analyzing the interference pattern of water-polymer flow, the streamline field of the central polymer injection well is disturbed by the water injection well, causing the polymer streamline field to decrease and the range of the polymer seepage field to decrease accordingly. In the later stage of water-polymer co-drive, due to the influence of the denser water injection wells on both sides, the polymer sweep area of ​​the central polymer injection well is limited to a certain extent, and the polymer cannot reach the corner wells. Water-drive and polymer-drive form obvious and fixed sweep areas. Therefore, the seepage law of the multi-stage streamline field constructed in this invention is consistent with the seepage law of the actual model.

[0064] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0065] It should be understood that the embodiments disclosed herein are not limited to the specific structures, processing steps, or materials disclosed herein, but should be extended to equivalent substitutions of these features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0066] The phrase "an embodiment" or "an embodiment" used in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" or "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0067] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for analyzing the patterns of water accumulation interference, comprising: Establish a detailed three-dimensional geological model of the oilfield area to be studied; Based on the current fluid characteristics, temperature and pressure variations, and dynamic production parameters of the oilfield area, the three-dimensional fine geological model is converted into a corresponding streamline numerical model. The streamline numerical model is reduced to a multi-stage streamline field including the water-drive stage, the polymer-drive stage, and different polymer injection PV numbers under water-polymer co-drive. This includes: based on the premise that fluid and rock are incompressible, and by following the basic principles of mass conservation, energy conservation, and momentum conservation, the three-dimensional streamline numerical model is reduced to a series of one-dimensional linear models based on each stage of water injection, polymer injection, and water-polymer co-drive, thereby establishing the streamline field of the oilfield concept streamline numerical model corresponding to the oilfield area under study, denoted as the multi-stage streamline field; A comprehensive analysis of the multi-stage streamline field is performed, in which... The step of converting the three-dimensional detailed geological model into a corresponding streamline numerical model includes: The three-dimensional fine geological model is coarsened, and the oilfield fluid characteristics, formation temperature distribution characteristics and variation conditions, formation pressure distribution characteristics and variation conditions, and dynamic production parameters corresponding to the oilfield area are used as verification conditions for the coarsening process. The changes of different types of attributes before and after model coarsening are continuously checked to ensure that the same attribute remains consistent before and after, thereby ensuring the quality of coarsening. Based on the fluid characteristics of the current oilfield area, the temperature and pressure variation conditions, and the dynamic production parameters, the coarsened model is historically fitted to form the streamline numerical model. This includes: using reserves, pressure, oil production, liquid production, and water cut as indicators, and employing a constant liquid production control method, first fitting various indicators of the entire oilfield area, and then fitting various indicators of each single well in the area with the production time as the axis. The fitting is mainly performed on wells that are still producing and shut-down wells with high cumulative oil production. In the process of constructing the streamline numerical model, it is necessary to continuously fit and control the model parameters of the streamline numerical model and gradually determine the optimal parameters. The optimal parameters include: the structural characteristics of the injection and production well network before and after well network densification and the production and development history data. The production and development history data includes water drive PV number, polymer drive PV number, and water injection rate and polymer injection rate in water-polymer co-drive.

2. The pattern analysis method according to claim 1, characterized in that, The steps in establishing a detailed three-dimensional geological model of the oilfield area under study include: Using reservoir characteristics, physical properties, and sedimentary facies characteristics of each well in the current oilfield area as quality control data, a stochastic simulation algorithm is used to model the geological model, thereby constructing the three-dimensional fine geological model, which includes lithology model, porosity attribute model, permeability attribute model, and oil saturation.

3. The pattern analysis method according to claim 1, characterized in that, The dynamic production parameters include time-based well completion and workover data, production data, and pressure data. The well completion and workover data includes, but is not limited to, well diameter, perforation filling thickness, perforation filling time, workover layer location, production injection time, fracturing parameters, and water shut-off parameters. The production data includes, but is not limited to, oil production, fluid production, water injection, oil-gas ratio, and oil-water ratio for each individual well. The pressure data includes, but is not limited to, bottom hole pressure, shut-in static pressure, and formation pressure for each individual well.

4. The pattern analysis method according to any one of claims 1-3, characterized in that, The comprehensive analysis of the multi-stage streamline field includes: The distribution of the number of streamlines and the degree of aggregation of the number of streamlines in the multi-stage streamline field are determined, and the characteristics of the injection volume distribution and fluid velocity distribution in different stages are analyzed.

5. A system for analyzing the patterns of water accumulation interference, comprising: The geological model generation module is configured to create a detailed three-dimensional geological model of the oilfield area to be studied. The numerical model generation module is configured to convert the three-dimensional fine geological model into a corresponding streamline numerical model based on the fluid characteristics, temperature and pressure variation conditions, and dynamic production parameters of the current oilfield area. The streamline field generation module is configured to restore the streamline numerical model to a multi-stage streamline field, including the water-drive stage, the polymer-drive stage, and different polymer injection PV numbers under water-polymer co-drive. This includes: based on the premise that fluids and rocks are incompressible, and following the basic principles of mass conservation, energy conservation, and momentum conservation, the three-dimensional streamline numerical model is restored to a series of one-dimensional linear models based on each stage of water injection, polymer injection, and water-polymer co-drive, thereby establishing the streamline field of the oilfield concept streamline numerical model corresponding to the current oilfield area under study, denoted as the multi-stage streamline field; The pattern analysis module is configured to perform a comprehensive analysis of the multi-stage streamline field, wherein the numerical model generation module is further configured to: The three-dimensional fine geological model is coarsened, and the oilfield fluid characteristics, formation temperature distribution characteristics and variation conditions, formation pressure distribution characteristics and variation conditions, and dynamic production parameters corresponding to the oilfield area are used as verification conditions for the coarsening process. The changes of different types of attributes before and after model coarsening are continuously checked to ensure that the same attribute remains consistent before and after, thereby ensuring the quality of coarsening. Based on the fluid characteristics of the current oilfield area, the temperature and pressure variation conditions, and the dynamic production parameters, the coarsened model is historically fitted to form the streamline numerical model. This includes: using reserves, pressure, oil production, liquid production, and water cut as indicators, and employing a constant liquid production control method, first fitting various indicators of the entire oilfield area, and then fitting various indicators of each single well in the area with the production time as the axis. The fitting is mainly performed on wells that are still producing and shut-down wells with high cumulative oil production. In the process of constructing the streamline numerical model, it is necessary to continuously fit and control the model parameters of the streamline numerical model and gradually determine the optimal parameters. The optimal parameters include: the structural characteristics of the injection and production well network before and after well network densification and the production and development history data. The production and development history data includes water drive PV number, polymer drive PV number, and water injection rate and polymer injection rate in water-polymer co-drive.

6. The pattern analysis system according to claim 5, characterized in that, The geological model generation module is also used to use the reservoir characteristic information, physical property parameters and sedimentary facies characteristic information of each single well in the current oilfield area as quality control data, and to use a stochastic simulation algorithm to build a geological model, thereby constructing the three-dimensional fine geological model including lithology model, porosity attribute model, permeability attribute model and oil saturation.

7. The pattern analysis system according to claim 5 or 6, characterized in that, The pattern analysis module is further configured to determine the distribution of the number of lines and the degree of aggregation of the number of lines in the multi-stage streamline field, and to analyze the injection volume distribution characteristics and fluid velocity distribution characteristics in different stages.

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