A pre-stack seismic method for identifying the oil-water interface

Abstract

The present invention relates to the technical field of oilfield development, and particularly relates to a method for identifying the oil-water interface by pre-stack seismic. The method includes: obtaining core data through actual drilled well coring, obtaining spontaneous potential and resistivity logging curves through logging, and obtaining pre-stack seismic trace gather data through seismic acquisition; based on the oil-water layer interpretation charts of spontaneous potential and resistivity curves, obtaining the oil-water layer interpretation results of wells without core data; respectively performing well-seismic calibration on the seismic data and the wells to obtain far seismic wavelets, medium seismic wavelets, and near seismic wavelets; adopting a synchronous inversion method to obtain longitudinal wave velocity data volume, shear wave velocity data volume, and density data volume; calculating to obtain a KC data volume; using the KC data volume as spatial constraint and taking the oil-water layer interpretation results of well points as control to obtain an oil layer spatial distribution probability model and obtain the distribution of the oil-water interface. The method for identifying the oil-water interface by pre-stack seismic provided by the present invention guides the precise development of oil resources and improves the oilfield development effect.

Description

Technical Field

[0001] The invention relates to the technical field of oilfield development, and in particular to a method for identifying an oil-water interface through prestack seismic. Background Art

[0002] Generally, accurate identification of the oil-water interface in oil and gas basins is of great significance for improving oil field recovery and precise development.

[0003] At present, the common method is to identify the oil-water interface points based on core data or logging curves, and then interpolate the oil-water interface points of multiple wells to obtain a surface, which is considered to be the oil-water interface; however, for sparse well network areas with fewer drillings, the accuracy of the oil-water interface obtained by interpolation is low and does not match the actual oil-water interface position. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] The invention provides a method for identifying oil-water interface by prestack seismic, so as to overcome the defect that the prior art cannot accurately identify the oil-water interface in a sparse well network area.

[0006] (II) Technical solution

[0007] To solve the above problems, the present invention provides a method for identifying oil-water interface by prestack seismic, comprising: step S1: obtaining core data by coring in real well drilling, obtaining natural potential and resistivity logging curves by logging, and obtaining prestack seismic gather data by seismic acquisition;

[0008] Step 2: Establish an interpretation chart of oil and water layers based on the natural potential curve and resistivity curve, and use the chart to obtain the interpretation results of oil and water layers in wells without core data;

[0009] Step 3: Stack the pre-stack seismic gather data according to the offset distance to obtain far stack seismic data, medium stack seismic data, and near stack seismic data;

[0010] The far stack seismic data, the medium stack seismic data, the near stack seismic data and the well are calibrated with the wells to obtain the far seismic wavelet, the medium seismic wavelet and the near seismic wavelet;

[0011] Step 4: Use synchronous inversion to obtain the P-wave velocity data volume, S-wave velocity data volume and density data volume;

[0012] Step 5: Using the P-wave velocity data volume, S-wave velocity data volume and density data volume, a joint operation is performed to obtain the KC data volume;

[0013] Step 6: Using the KC data volume as a spatial constraint and the oil-water layer interpretation results of the well point as a control, the BP neural network algorithm is used to obtain the oil layer spatial distribution probability model, and the oil-water interface distribution is obtained using this model.

[0014] Preferably, the step S2 comprises:

[0015] Based on the core data obtained in step S1, the interpretation results of the oil and water layers are obtained through measured analysis. By utilizing the natural potential, resistivity curve and the interpretation results of the oil and water layers, a quantitative interpretation chart of the oil and water layers based on the natural potential curve and the resistivity curve is established. Based on the interpretation chart, the natural potential and resistivity curves of the wells without core data are used to obtain the interpretation results of the oil and water layers of the wells without core data.

[0016] Preferably, step S4 comprises: using the far stack seismic data, medium stack seismic data, near stack seismic data and far seismic wavelets, medium seismic wavelets and near seismic wavelets obtained in step 3, and adopting a synchronous inversion method, the specific formula is:

[0017]

[0018] v 2P ,v 1P ,v 2S ,v 1S ,ρ 2 ,ρ 1 They represent the longitudinal wave, shear wave velocity and density of the media above and below the interface respectively, θ is the incident angle, R(θ) is the reflection coefficient, K is a constant term, and the longitudinal wave velocity, shear wave velocity data volume and density data volume are obtained through calculation.

[0019] Preferably, the step S5 comprises: using the longitudinal wave velocity data volume, the shear wave velocity data volume and the density data volume obtained in step S4, using the formula:

[0020] KC=(ρV p ) 2 -2(ρV S ) 2 ,

[0021] Among them I P is the longitudinal wave velocity, I S is the shear wave velocity, ρ is the density, and the KC data volume is obtained by calculation. The area with a larger value is considered to contain more water and less oil, while the area with a smaller value is considered to contain less water and more oil.

[0022] Preferably, the step S6 comprises: using the KC data volume obtained in step S5 as a spatial constraint, taking the interpretation results of the oil layer and water layer of the well point obtained in step S2 as a control, and adopting a BP neural network algorithm to obtain an oil layer spatial distribution probability model, whose value range is 0 to 100%;

[0023] The area with probability value greater than or equal to 50% in the probability model is interpreted as oil layer; the area with probability value less than 50% is interpreted as water layer, and the boundary between oil layer and water layer is interpreted as oil-water interface.

[0024] (III) Beneficial effects

[0025] The prestack seismic oil-water interface identification method provided by the present invention uses prestack seismic data and well data to accurately identify the oil-water interface, which can guide the precise development of petroleum resources and improve the effect of oil field development. The method can be applied to different types of oil fields, and the calculation results are reasonable and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of a method for identifying oil-water interface in prestack seismic according to an embodiment of the present invention;

[0027] Figure 2 It is the NEX oil and water layer identification chart;

[0028] Figure 3 It is a cross-section of seismic data stacked at different angles (far stack, medium stack, near stack);

[0029] Figure 4 It is the curve diagram of distant earthquake wavelet, medium earthquake wavelet and near earthquake wavelet;

[0030] Figure 5 It is a three-dimensional graph of KC data;

[0031] Figure 6 It is the oil-water interface distribution map. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] like Figure 1 As shown, the present invention provides a method for identifying oil-water interface in prestack seismic, which specifically includes:

[0034] Step S1: obtaining core data by coring the actual well, obtaining natural potential and resistivity logging curves by logging, and obtaining pre-stack seismic gather data by seismic acquisition;

[0035] Step S2: establishing an interpretation chart of oil and water layers based on the natural potential curve and the resistivity curve, and using the chart to obtain the interpretation results of the oil and water layers of the well without core data;

[0036] In this step, based on the wells with core data obtained in step S1, experimental analysis is used to obtain the interpretation results of the oil and water layers, and an interpretation map of the oil and water layers based on the natural potential curve and the resistivity curve is established. Based on the interpretation map, the natural potential and resistivity curves of the wells without core data are used to obtain the interpretation results of the oil and water layers of the wells without core data. Figure 2 The identification plate of oil and water layers in NEX area is given.

[0037] Step S3: stacking the pre-stack seismic gather data according to the offset distance to obtain far stack seismic data, medium stack seismic data, and near stack seismic data;

[0038] The far stack seismic data, the medium stack seismic data, the near stack seismic data and the well are calibrated with the wells to obtain the far seismic wavelet, the medium seismic wavelet and the near seismic wavelet;

[0039] In this step, the pre-stack seismic gather data obtained in step S1 are stacked according to the offset distance to obtain far stacked seismic data, medium stacked seismic data, and near stacked seismic data; the far stacked seismic data, medium stacked seismic data, and near stacked seismic data are calibrated with the wells respectively to obtain far seismic wavelets, medium seismic wavelets, and near seismic wavelets. Figure 3 The superimposed earthquakes at different angles are given. Figure 4 Seismic wavelets at different angles are given.

[0040] Step S4: using synchronous inversion means to obtain a P-wave velocity data volume, a S-wave velocity data volume and a density data volume;

[0041] In this step, the far stack seismic data, medium stack seismic data, near stack seismic data, far seismic wavelets, medium seismic wavelets, and near seismic wavelets obtained in step S3 are used to adopt a synchronous inversion method. The specific formula is:

[0042]

[0043] v 2P ,v 1P ,v 2S ,v 1S ,ρ 2 ,ρ 1 They represent the longitudinal wave, shear wave velocities and density of the media above and below the interface respectively, θ is the incident angle, R(θ) is the reflection coefficient, K is a constant term, and the longitudinal wave velocity data volume, shear wave velocity data volume and density velocity volume are obtained through calculation.

[0044] Step S5: using the longitudinal wave velocity data volume, the shear wave velocity data volume and the density data volume, a joint operation is performed to obtain a KC data volume;

[0045] In this step, the longitudinal wave velocity data volume, the shear wave velocity data volume and the density data volume obtained in step 4 are used, and the formula is: KC = (ρV p ) 2 -2(ρV S ) 2 ,

[0046] Among them I P is the longitudinal wave velocity, I S is the shear wave velocity, ρ is the density, and the KC data volume is obtained by calculation. The area with a larger value is considered to contain more water and less oil, while the area with a smaller value is considered to contain less water and more oil. Figure 5 A three-dimensional plot of the KC data volume is given.

[0047] Step S6: Using the KC data volume as a spatial constraint and the oil-water layer interpretation results of the well point as a control, a BP neural network algorithm is used to obtain a spatial distribution probability model of the oil layer, and the oil-water interface distribution is obtained using the model.

[0048] Using the KC data volume obtained in step 5 as a spatial constraint, and the interpretation results of the oil layer and water layer of the well point obtained in step 2 as a control, the BP neural network algorithm is used to obtain the oil layer spatial distribution probability model, whose value range is 0 to 100%. The area with a probability value greater than or equal to 50% in the probability model is interpreted as an oil layer, the area with a probability value less than 50% is interpreted as a water layer, and the boundary between the oil layer and the water layer is interpreted as the oil-water interface. Figure 6 The oil-water interface distribution diagram is given.

[0049] Through research, it is found that prestack seismic can reflect the changes in oil and water layers and improve the accuracy of oil-water interface identification. The present invention studies a method for identifying the oil-water interface by prestack seismic, which solves the problem that the oil-water interface cannot be accurately identified in sparse well network areas, thereby improving the effect of oilfield development.

[0050] The present invention uses pre-stack seismic data and well data to accurately identify the oil-water interface, which can guide the precise development of oil resources and improve the effect of oil field development. The method can be applied to different types of oil fields, and the calculation results are reasonable and accurate.

[0051] The above implementation modes are only used to illustrate the present invention, but not to limit the present invention. Ordinary technicians in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all equivalent technical solutions also belong to the scope of the present invention. The patent protection scope of the present invention should be defined by the claims.

Claims

1. A prestack seismic method for identifying the oil-water interface, characterized in that, it includes: Step S1: Obtain core data through actual drilled cores, obtain spontaneous potential and resistivity logging curves through logging, and obtain prestack seismic gather data through seismic acquisition; Step S2: Establish an interpretation chart of oil layers and water layers based on the spontaneous potential curve and resistivity curve, and use this chart to obtain the interpretation results of oil and water layers for wells without core data; Step S3: Stack the prestack seismic gather data according to the offset to obtain far-stack seismic data, mid-stack seismic data, and near-stack seismic data; Perform well-seismic calibration on the far-stack seismic data, mid-stack seismic data, near-stack seismic data and wells respectively to obtain far seismic wavelets, mid seismic wavelets, and near seismic wavelets; Step S4: Use the synchronous inversion method to obtain P-wave velocity data volume, S-wave velocity data volume and density data volume, specifically including: using the far-stack seismic data, mid-stack seismic data, near-stack seismic data and far seismic wavelets, mid seismic wavelets, near seismic wavelets obtained in Step 3, and adopting the synchronous inversion method, the specific formula is: ； represent the longitudinal wave, shear wave velocities and densities of the upper and lower media of the interface respectively, is the incident angle, is the reflection coefficient, is the constant term. After calculation, the longitudinal wave velocity, shear wave velocity data volumes and density data volume are obtained; Step S5: Use the P-wave velocity data volume, S-wave velocity data volume and density data volume to jointly calculate the KC data volume, specifically including: using the P-wave velocity data volume, S-wave velocity data volume and density data volume obtained in Step S4, and adopting the formula: ； Where V P is the longitudinal wave velocity, V S is the shear wave velocity, is the density, and the KC data volume is obtained by calculation; Step S6: Use the KC data volume as spatial constraint and the interpretation results of oil and water layers of well points as control, and adopt the BP neural network algorithm to obtain the probability model of the spatial distribution of oil layers, and use this model to obtain the distribution of the oil-water interface.

2. The prestack seismic method for identifying the oil-water interface according to claim 1, characterized in that, Step S2 includes: Based on the core data obtained in Step S1, obtain the interpretation results of oil layers and water layers through actual measurement and analysis. Use the spontaneous potential, resistivity curves and the interpretation results of oil and water layers to establish a quantitative interpretation chart of oil layers and water layers based on the spontaneous potential curve and resistivity curve, and based on this interpretation chart, use the spontaneous potential and resistivity curves of wells without core data to obtain the interpretation results of oil layers and water layers of wells without core data.

3. The prestack seismic method for identifying the oil-water interface according to claim 1, characterized in that, Step S6 includes: Using the KC data volume obtained in Step S5 as spatial constraint and the interpretation results of oil layers and water layers of well points obtained in Step S2 as control, and adopting the BP neural network algorithm to obtain the probability model of the spatial distribution of oil layers, and its value range is 0~100%; Interpret the area where the probability value in the probability model is greater than or equal to 50% as the oil layer; interpret the area where the probability value is less than 50% as the water layer, and the junction between the oil layer and the water layer is interpreted as the oil-water interface.

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