A fine geological modeling method under offshore irregular mixed sparse well pattern conditions

Abstract

The present invention relates to the technical field of three-dimensional geological modeling for petroleum development, and specifically to a fine geological modeling method under the conditions of irregular mixed sparse well networks at sea. The method of the present invention deeply mines horizontal well data, optimizes structural levels using drilling profiles and seismic inversion data bodies, identifies configuration interfaces through well vibration data fusion and equivalently embeds models, optimizes variogram values ​​through inversion body constraints and multi-well type control, and finally obtains a fine geological model, breaking through the problem of little offshore marginal oil reservoir data and low model accuracy; finally, a high-precision three-dimensional geological model is established for marginal oil reservoirs developed in irregular mixed sparse well networks at sea. The established model can effectively guide the development and deployment of marginal oil reservoirs.

Description

Technical Field

[0001] The invention relates to the technical field of three-dimensional geological modeling for petroleum development, and in particular to a fine geological modeling method under offshore irregular mixed sparse well network conditions. Background Art

[0002] Three-dimensional reservoir geological modeling is the core link in reservoir description technology, which provides geological basis for reservoir numerical simulation and development deployment. With the continuous deepening of reservoir development, reservoir dynamics continue to change, and the distribution of remaining oil becomes more complex. At the same time, basic data is constantly enriched, geological understanding is constantly deepened, and the accuracy of the established three-dimensional geological model is getting higher and higher.

[0003] Due to the limitations of marine engineering conditions, offshore oil fields are often developed with a sparse well network with large well spacing. As the development of oil fields continues to deepen, the development adjustment and deployment countermeasures are more targeted. For example, in narrow channel single sand body reservoirs in marginal oil reservoirs, the selection of new well types has changed from highly deviated directional wells to horizontal wells. The characteristics of horizontal wells with large oil leakage area, high reserve utilization and high single well production are used to further improve the production efficiency. Therefore, some marginal oil reservoirs in offshore oil fields have gradually formed an irregular mixed sparse well network with large well spacing, which is produced by vertical wells, highly deviated wells and horizontal wells. In this case, the basic data is limited, which brings difficulties to the establishment of high-precision three-dimensional geological models.

[0004] Usually, in the late development modeling area, the well network is dense and the number of wells is large. Without considering the horizontal well data, the model can meet the development deployment needs only based on the vertical and inclined well data and using conventional methods. However, under the conditions of irregular mixed sparse well network at sea, the conventional method only uses seismic interpretation data and vertical and inclined well data interpolation when establishing the structural layer, resulting in insufficient structural accuracy in the horizontal well control area and large errors; the number of wells is small, the interlayer information on the wells is limited, and it is not fully represented in the model; and the vertical and inclined well data do not converge to the small-variance function, and the uncertainty of attribute simulation is large.

[0005] Chinese patent application CN110687603A discloses a geological modeling method for seepage barriers inside offshore oilfield reservoirs, which includes the following steps: collecting sensitive seismic attributes of the reservoir to be tested to predict the distribution of seepage barriers inside the reservoir, and dividing the seepage barriers into three categories: non-permeable, semi-permeable and permeable; according to the horizontal well data of the seepage barriers drilled in the reservoir to be tested, respectively statistically analyzing the basic data used to characterize the three types of seepage barriers; respectively establishing lithofacies models of the three types of seepage barriers: non-permeable, semi-permeable and permeable; setting up virtual wells in the lithofacies model according to the attribute characteristics of the seepage barriers, respectively simulating the attribute characteristics of the three types of seepage barriers, and obtaining the geological model of the seepage barriers inside the reservoir. This method effectively depicts the real distribution of seepage barriers inside the reservoir, making up for the shortcomings of traditional utilization theory. By replicating the actual drilled horizontal wells to set up virtual wells, the basic data of geological modeling is enriched, and the characterization accuracy of the seepage barriers in the geological model is improved.

[0006] However, there is currently no good method for constructing geological models for marginal reservoirs developed under offshore irregular mixed sparse well pattern conditions. Summary of the invention

[0007] The main purpose of the present invention is to provide a method for establishing a high-precision three-dimensional geological model for marginal oil reservoirs developed in offshore irregular mixed sparse well networks. The method of the present invention provides a good geological basis for numerical simulation of oil reservoirs and can ultimately guide the development and deployment of oil reservoirs.

[0008] To achieve the above object, the present invention adopts the following technical solutions:

[0009] The present invention provides a fine geological modeling method under the condition of irregular mixed sparse well pattern at sea, which comprises the following steps:

[0010] 1) Using the interpolation of seismic interpretation data and the control of single well layer data, the top surface of the model structure is preliminarily established; the reservoir thickness data of the vertical and inclined wells is interpolated to establish a single-layer sand body thickness map, and the top surface of the structure plus the sand body thickness is obtained to obtain the bottom surface of the model structure;

[0011] 2) Optimize the top and bottom surfaces of the structure in the horizontal well control area;

[0012] 3) Extract multiple seismic attributes and perform cluster analysis to identify reservoir configuration interfaces;

[0013] 4) Establish a spatial model of lateral accumulation body;

[0014] 5) Carry out variogram analysis by combining well-seismic data to obtain reasonable variogram results;

[0015] 6) Using sequential Gaussian simulation to establish attribute model;

[0016] 7) According to the interlayer properties, the interface conductivity of the lateral accumulation body is set differently to reasonably simulate the influence of the lateral accumulation body on the fluid seepage inside the reservoir.

[0017] Furthermore, in step 2), according to the positional relationship between the structural top and bottom surfaces and the horizontal well trajectory established in step 1), the horizontal well trajectory, geological steering information and seismic inversion results are applied to optimize the structural top and bottom surfaces of the horizontal well control area.

[0018] Furthermore, in step 3), multiple seismic attributes are extracted and cluster analysis is performed to preliminarily divide the internal connected units of the sand body; at the same time, the point-bar scale is calculated using modern sedimentary empirical formulas; combined with dynamic development data, the injection-production correspondence is identified, and the reservoir configuration interface is identified.

[0019] Furthermore, the seismic attributes include amplitude, frequency, arc length, and phase.

[0020] Furthermore, in step 4), the method for establishing the spatial model of the lateral accumulation body comprises the following steps: analyzing the horizontal well section data, identifying the physical and lithological interlayers in the horizontal section according to the judgment criteria, and calculating the dip angle of the lateral accumulation layer; determining the position of the third-level configuration interface by fitting the inter-well distribution pattern of the lateral accumulation layer; and embedding the interlayer into the model using the method of equivalent configuration interface to deterministically establish the spatial model of the lateral accumulation body.

[0021] Furthermore, in step 5), the seismic inversion data volume is subjected to variogram analysis, and the well point data, including the data of the horizontal section of the horizontal well, are used to analyze the variogram, and the two are compared and analyzed to obtain a reasonable variogram result.

[0022] Furthermore, in step 6), under the constraints of the configuration model and using the variogram control obtained in the previous step, sequential Gaussian simulation is used to establish the attribute model.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The method of the present invention deeply mines horizontal well data, optimizes structural layers using drilling profiles and seismic inversion data, identifies configuration interfaces by fusing well vibration data and embeds them into the model equivalently, optimizes the variogram value by inversion volume constraints and multi-well type control, and finally obtains a fine geological model, breaking through the problem of little offshore marginal reservoir data and low model accuracy; finally, a high-precision three-dimensional geological model is established for marginal reservoirs developed in irregular mixed sparse well networks at sea. The established model can be effectively used to guide development deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0026] Figure 1 It is a flow chart of a fine geological modeling method under offshore irregular mixed sparse well pattern conditions according to a specific embodiment of the present invention;

[0027] Figure 2 The upper section 5 of the pavilion is described in a specific embodiment of the present invention. 5 Structural diagram of the top surface of a single sand layer;

[0028] Figure 3 This is the geosteering profile of the 42HP well described in a specific embodiment of the present invention;

[0029] Figure 4 This is the seismic inversion profile of the 42HP well described in a specific embodiment of the present invention;

[0030] Figure 5 This is a cross-sectional view of a 42HP well model before the horizontal well is controlled according to a specific embodiment of the present invention;

[0031] Figure 6 This is a cross-sectional view of a 42HP well model after horizontal well control according to a specific embodiment of the present invention;

[0032] Figure 7 This is a diagram of the multi-attribute clustering analysis results described in a specific embodiment of the present invention;

[0033] Figure 8 It is a four-level configuration unit identification diagram according to a specific embodiment of the present invention;

[0034] Fig. 9 It is a horizontal segment interlayer identification diagram described in a specific embodiment of the present invention;

[0035] Fig.10 It is a cross-sectional view of a 4HP configuration mode according to a specific embodiment of the present invention;

[0036] Fig.11 It is a plane position diagram of the three-level configuration unit according to a specific embodiment of the present invention;

[0037] Fig.12 This is a schematic diagram of an equivalent configuration interface according to a specific embodiment of the present invention;

[0038] Fig.13 A seismic inversion attribute map according to a specific embodiment of the present invention;

[0039] Fig.14 A diagram showing the variogram analysis results according to a specific embodiment of the present invention;

[0040] Fig.15 A permeability model diagram according to a specific embodiment of the present invention;

[0041] Fig.16 A conductivity and streamline model diagram according to a specific embodiment of the present invention. DETAILED DESCRIPTION

[0042] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0043] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations and / or combinations thereof.

[0044] In order to enable those skilled in the art to more clearly understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below in conjunction with specific embodiments.

[0045] Example

[0046] like Figure 1 As shown, the fine geological modeling method under the condition of irregular mixed sparse well pattern at sea includes the following steps:

[0047] 1) Using the interpolation of seismic interpretation data, the single well layer data is controlled to preliminarily establish the top surface of the model structure; the reservoir thickness data of the vertical and inclined wells is interpolated to establish a single-layer sand body thickness map, and the top surface of the structure plus the sand body thickness is used to obtain the bottom surface of the model structure, such as Figure 2 shown.

[0048] 2) Check step 1) Generate the positional relationship between the top and bottom surfaces of the structure and the horizontal well trajectory, and apply the horizontal well trajectory, geological steering information and seismic inversion results, such as Figure 3 , Figure 4 , Figure 5 As shown in the figure, the top and bottom surfaces of the structure in the horizontal well control area are optimized. The optimization results are shown in Figure 6 .

[0049] 3) Extract multiple seismic attributes, including amplitude, frequency, arc length, and phase, and perform cluster analysis to preliminarily divide the internal connected units of the sand body, such as Figure 7 As shown; at the same time, using the modern sedimentation empirical formula: w d =3.6319w+40.612(w-full bank width, w d -point-bar span), calculate the point-bar scale. Combined with dynamic development data, identify the injection-production correspondence, and divide the reservoir into four-level configuration units, such as Figure 8shown.

[0050] 4) Analyze the horizontal well data. When the GR value in the horizontal section is greater than 110gAPI and the resistivity value is less than 10ohm.m, it is a lithological interlayer. When the GR value is between 85-110gAPI and the resistivity curve has no large return, it is a physical interlayer. The permeability of the lithological interlayer is generally less than 80md, and the physical interlayer is generally 300-500md. According to the judgment criteria, the physical and lithological interlayers in the horizontal section are identified, such as Fig. 9 shown.

[0051] Using the formula w / h=38.194exp Calculate the inclination angle of the lateral accumulation layer, where w / h: river width-to-depth ratio; : Lateral accumulation layer dip angle, lateral accumulation layer well distribution pattern fitting, determine the position of the third-level configuration interface; Fig.10 , Fig.11 shown.

[0052] According to the interlayer plane distribution position line, it is converted into a simulation fault embedding model, which is equivalent to establishing an equivalent configuration interface and deterministically establishing a lateral accumulation body space model, such as Fig.12 shown.

[0053] 5) For seismic inversion data (such as Fig.13 ) to perform variogram analysis, and at the same time use well point data, including data from horizontal sections of horizontal wells, to perform variogram analysis (as shown in Fig.14 By comparing and analyzing the two, we can obtain the variogram results that are consistent with the understanding of river phases, providing a basis for attribute simulation.

[0054] 6) Under the constraints of the configuration model and using the variogram control obtained in the previous step, sequential Gaussian simulation is used to establish the attribute model, such as Fig.15 .

[0055] 7) According to the interlayer properties, the interface conductivity of the lateral accumulation body is set differently: 0-0.3 for mud interlayer, 0.3-0.4 for physical interlayer, and 1 for sandstone. Fig.16 , reasonably simulate the influence of lateral accumulation body on fluid seepage inside the reservoir.

[0056] The method described in the above embodiment was applied to Chengbei Block 18 of Chengdao Oilfield. The model results were used for numerical simulation to guide development deployment. A total of regulated wells were adjusted, and the cumulative oil production increased by 13,000 tons, and the recovery rate increased by 2.8%. Four new wells were drilled, including three horizontal wells (68HP, 88HP, 89HP) and one high-angle directional well (86HP). The total length of the horizontal section was 1,338.8 meters. All of them have been put into production, with a daily oil production of 196 tons, an average daily oil production of 49 tons per well, and a water content of 2%. It provides technical support for the efficient development of offshore oilfields.

[0057] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A fine geological modeling method under offshore irregular mixed sparse well pattern conditions, characterized in that: It includes the following steps: 1) Using the interpolation of seismic interpretation data and the control of single well layer data, the top surface of the model structure is preliminarily established; the reservoir thickness data of the vertical and inclined wells is interpolated to establish a single-layer sand body thickness map, and the top surface of the structure plus the sand body thickness is used to obtain the bottom surface of the model structure; 2) Optimize the top and bottom surfaces of the structure in the horizontal well control area; 3) Extract multiple seismic attributes and perform cluster analysis to identify reservoir configuration interfaces; 4) Establish a spatial model of lateral accumulation body; 5) Carry out variogram analysis by combining well-seismic data to obtain reasonable variogram results; 6) Use sequential Gaussian simulation to establish attribute model; 7) According to the interlayer properties, the interface conductivity of the lateral accumulation body is set differently to reasonably simulate the influence of the lateral accumulation body on the fluid seepage inside the reservoir; In step 2), according to the positional relationship between the structural top and bottom surfaces and the horizontal well trajectory established in step 1), the horizontal well trajectory, geological steering information and seismic inversion results are used to optimize the structural top and bottom surfaces of the horizontal well control area; The method for establishing the spatial model of the lateral accumulation body in step 4) comprises the following steps: analyzing the horizontal well section data, identifying the physical and lithological interlayers in the horizontal section according to the judgment criteria, and calculating the dip angle of the lateral accumulation layer; determining the position of the third-level configuration interface by fitting the inter-well distribution pattern of the lateral accumulation layer; embedding the interlayer into the model by using the method of equivalent configuration interface, and deterministically establishing the spatial model of the lateral accumulation body; In step 5), the variogram analysis is performed on the seismic inversion data body, and the variogram is analyzed using the well point data, including the data of the horizontal section of the horizontal well. The two are compared and analyzed to obtain a reasonable variogram result.

2. The method according to claim 1, characterized in that: In step 3), multiple seismic attributes are extracted and cluster analysis is performed to preliminarily divide the internal connected units of the sand body; at the same time, the point-bar scale is calculated using modern sedimentary empirical formulas; Combined with dynamic development data, the corresponding relationship between injection and production is identified, and the reservoir configuration interface is identified.

3. The method according to claim 1 or 2, characterized in that: The seismic attributes include amplitude, frequency, arc length, and phase.

4. The method according to claim 1, characterized in that: In step 6), under the constraints of the configuration model and using the variogram control obtained in the previous step, sequential Gaussian simulation is used to establish the attribute model.

Images