Progressive reservoir fine prediction method for wide-azimuth seismic change rate attributes

Abstract

The invention discloses a progressive reservoir fine prediction method for wide-azimuth seismic change rate attributes, and relates to the technical field of reservoir prediction, comprising the following steps: analyzing seismic acquisition and observation system parameters, limiting effective offset, and performing azimuth division on seismic data; within the limited offset distance, generating an omnibearing near offset distance gather superposition seismic amplitude and an omnibearing far offset distance gather superposition seismic amplitude; calculating and outputting an amplitude anisotropy value by using the divided effective offset sub-azimuth gather, and taking the result as an earthquake prediction result of the sedimentary facies belt; difference is carried out by using the omni-directional far-offset gather superposition seismic amplitude and the omni-directional near-offset gather superposition seismic amplitude, an offset amplitude difference attribute is obtained, a result is output, and the result is used for predicting the thickness of a reservoir prediction work area; and the gradient attribute change rate of the azimuth gather is divided by using the effective offset, and is output as the prediction of the fluid.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir prediction, in particular to a progressive reservoir fine prediction method of wide-azimuth seismic change rate attributes. Background Art

[0002] Reservoir prediction is an important purpose of seismic data interpretation. The accuracy of reservoir prediction directly affects the well site deployment and comprehensive evaluation in oil and gas field exploration. There are many reservoir prediction methods at present, but in principle, they can be divided into two categories: one is the post-stack seismic prediction technology represented by conventional seismic attributes. This method mainly uses synthetic record calibration of seismic data to interpret the stratigraphic structure by determining the seismic reflection event axis of the target layer, and extracts the amplitude, frequency, phase and other attributes of the formation by using the layer position and time, or obtains extended attributes such as amplitude-frequency ratio by calculation on this type of seismic attributes. Another type is pre-stack seismic attribute prediction represented by P-wave velocity, S-wave velocity and AVO attributes. This method is to analyze the seismic response characteristics of geological bodies such as strata and fluids in pre-stack gathers, utilize the differences in the propagation velocities of P-waves and S-waves in rocks, use the stacking data of near, middle and far gathers, and use the simplified form of the Zoeppritz equation to predict the elastic parameters of pre-stack P-wave and S-wave ratio, Young's modulus and Poisson's ratio, or to predict the AVO attributes (intercept, gradient parameters) based on the rate of change of the amplitude of the reservoir and fluid on the pre-stack gathers with the incident angle.

[0003] With the continuous deepening of oil and gas field exploration, the targets of underground geological bodies have become more complex, and higher requirements have been put forward for the accuracy of reservoir prediction. Although the macroscopic laws of seismic sedimentation can be identified by the post-stack seismic attributes of longitudinal wave impedance, due to the different combinations and similar comprehensive velocities of different lithologies, it is difficult to refine the description of reservoir phase belt boundaries, lithological closure boundaries and fluid boundaries. In terms of reservoir thickness prediction, the traditional method is to use the Widess principle between sand thickness and apparent amplitude, that is, within the tuning thickness, the apparent amplitude and sand thickness are monotonically increasing, and the peak and amplitude and frequency are the two most basic seismic attributes. When the formation thickness is less than one-quarter wavelength, these two seismic attributes are generally used to estimate the formation thickness. However, the nonlinear relationship between these two seismic attributes and formation thickness reduces the accuracy of quantitative prediction of sand body thickness.

[0004] Compared with post-stack attribute technology, pre-stack attribute is suitable for complex geological structure areas. Pre-stack seismic attribute prediction not only considers the amplitude information of seismic waves, but also contains information on elastic parameter prediction of longitudinal and transverse wave ratio, Young's modulus, and Poisson's ratio. Compared with post-stack seismic attributes, the comprehensive application of these elastic information is more helpful to solve the post-stack influence of heterogeneous phases of underground sediments and phase belts, and use shear waves to carry out predictions to understand the underground geological structure more comprehensively. However, in terms of application, the results of pre-stack seismic attribute prediction depend largely on the accuracy of the geological model. If the geological model is inaccurate, the prediction results may also be unreliable. In addition, in some special geological environments, such as strong anisotropic strata, traditional pre-stack seismic attribute prediction methods may no longer be applicable.

[0005] With the continuous advancement of seismic exploration acquisition technology and processing technology, seismic data has gradually expanded from traditional three-dimensional seismic data to "four-dimensional" information in the three-dimensional seismic + offset domain and "five-dimensional" information in the three-dimensional seismic + offset domain + azimuth domain. Five-dimensional seismic data has the advantage of OVT processing. Therefore, in summary, in the face of seismic data with richer dimensions, there is currently no good integrated technical process for using OVT seismic data to achieve reservoir phase zone division, reservoir thickness prediction and fluid detection. Summary of the invention

[0006] To solve the above problems, the present invention provides a progressive reservoir fine prediction method for wide-azimuth seismic change rate attributes. Step 1, collecting OVT seismic data, interpretation layer data, and observation system parameters of the seismic acquisition area in the reservoir prediction area; Step 2: Analyze the parameters of the seismic acquisition observation system to determine the maximum north-south distance and the maximum east-west distance of the shot check points in the seismic acquisition work area, and take the minimum value of the two as the effective offset distance L; Step 3, limit the effective offset distance L and divide the OVT seismic data into azimuths; Step 4, generating a full range of near-offset gathers and a full range of far-offset gathers with stacked seismic amplitudes within a limited effective offset distance L; Step 5, using the divided effective offset distance and azimuth gathers to calculate and output the amplitude anisotropy value, and use this result as the seismic prediction result of the sedimentary facies belt; Step 6, using the difference between the stacked seismic amplitude of the omni-directional far-offset gather and the stacked seismic amplitude of the omni-directional near-offset gather, obtain the offset amplitude difference attribute and output the result, which is used as the prediction of the thickness of the reservoir prediction area; Step 7, according to the azimuth division method of step 3, the gradient attribute change rate is calculated using the effective offset distance azimuth gather, and the output is used as the prediction result of the fluid.

[0007] In a preferred embodiment, in step 3, the principle of division is to divide the sector angle by 30 degrees at least, the number of sectors shall not be less than 6, and the azimuth angles shall be divided according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180.

[0008] In a preferred embodiment, in step 4, the near offset starts at 0 m, the end offset is no more than 1 / 2L, the far offset is no less than 1 / 2L, and the maximum is L.

[0009] In a preferred embodiment, in step 5, the amplitude change rate value is calculated using the divided effective offset distance and azimuth seismic data:

[0010] ); In the formula, is the amplitude change rate, is the maximum amplitude at position i, is the minimum amplitude of azimuth i, where i is the azimuth angle number.

[0011] In a preferred embodiment, in step 7, according to the azimuth division method of step 3, the gradient attribute change rate G(i) is calculated by using the effective offset distance divided azimuth gather: ; ; Where i=1,2,3,4,5,6; is the maximum effective offset amplitude value of the i-th azimuth, is the minimum offset amplitude value of the i-th azimuth.

[0012] In a preferred embodiment, ) are divided into 6 directions according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180.

[0013] Compared with the prior art, the present invention has the following beneficial technical effects: The present invention utilizes wide-azimuth seismic gather data. Compared with conventional three-dimensional seismic data and pre-stack offset domain seismic data, wide-azimuth seismic gather data can not only solve the seismic prediction of refining reservoir boundaries using elastic parameters, but also solve the problem that traditional pre-stack attributes are no longer applicable in anisotropic formations.

[0014] The present invention determines the effective offset of OVT seismic data by analyzing and clarifying the observation system of seismic acquisition, which can maintain the energy consistency of different azimuth stacking gathers when carrying out azimuth division of data, and eliminate the anisotropic prediction multi-solution caused by energy differences due to inconsistent coverage times.

[0015] The present invention proposes a progressive reservoir fine prediction method based on the change rate attribute, which can realize the prediction of reservoirs from macroscopic sedimentary distribution to reservoir and fluid prediction. It realizes layer-by-layer constraints, avoids the multiple solutions caused by a single prediction, and improves the scientificity, rationality and accuracy of reservoir prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the technical solution of the present invention.

[0017] Figure 2 is an analysis diagram of the earthquake observation system.

[0018] Fig. 3 Seismic data in azimuth within effective offset.

[0019] Fig. 4 All-directional offset stacked seismic profile.

[0020] Figure 5 is a plan view of the plane properties of the AvAz phase belt.

[0021] Figure 6 shows the plane diagram of the amplitude difference attributes at far offset and near offset.

[0022] Figure 7 is a plan view of the fluid properties of AvoAz. DETAILED DESCRIPTION

[0023] The technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0024] The progressive reservoir fine prediction method of wide azimuth seismic change rate attribute of the present invention collects seismic data of the research work area, stratigraphic interpretation data and other basic data; clarifies the observation system of seismic acquisition, and determines the effective offset of OVT seismic data; after determining the effective offset, carries out azimuth division of OVT gathers within the effective offset, and generates sub-azimuth gathers of the effective offset; carries out omnidirectional sub-offset division by using OVT seismic data, and generates omnidirectional near-offset gathers and omnidirectional far-offset gathers; uses the divided effective offset sub-azimuth gathers to carry out amplitude anisotropy value calculation to carry out seismic prediction of sedimentary facies belt; uses the generated omnidirectional near-offset gathers and omnidirectional far-offset gathers to carry out offset amplitude difference attribute calculation to predict sedimentary thickness; and uses the AVO attribute of the effective offset sub-azimuth gathers to calculate AVO gradient anisotropy.

[0025] like Figure 1 FIG. 1 is a flowchart of a progressive reservoir fine prediction method of wide azimuth seismic change rate attributes of the present invention, which specifically includes the following steps: Step 1: Collect OVT seismic data, interpretation layer data, and observation system parameters of the seismic acquisition area in the reservoir prediction area.

[0026] OVT seismic data has offset information and azimuth information, which is conducive to the precise prediction of geological bodies. When studying the reservoir prediction area, the focus is on and analysis of basic data such as the seismic interpretation data of the underground strata or geological body layers, the parameters of the seismic acquisition area observation system, etc., mainly referring to the maximum longitudinal distance and maximum non-longitudinal distance of seismic data acquisition.

[0027] Step 2: Analyze the parameters of the seismic acquisition observation system to determine the maximum north-south distance and the maximum east-west distance of the shot checkpoints in the seismic acquisition area, and take the minimum of the two as the effective offset distance L.

[0028] Through the OVT bin analysis of the target layer, it is believed that the maximum north-south distance of the shot check point of the OVT bin in the seismic acquisition area is 3237.5m, and the maximum east-west distance is 2037.5m. In order to maintain the consistency of the coverage times of different azimuth angles and improve the accuracy of the azimuth attribute change rate of seismic data, the minimum value of 2037.5 is used as the effective offset distance L.

[0029] like Figure 2 The observation system of the earthquake work area is shown in Figure 1. The observation system parameters are shown in Table 1. The observation system mainly refers to the maximum non-longitudinal distance 2037.5 as the effective offset distance L.

[0030] Table 1 Observation system parameters

[0031] Step 3: Define the effective offset distance L and divide the OVT seismic data into azimuth angles.

[0032] In a preferred embodiment, the effective offset distance L is limited to 2037.5 m, and the OVT seismic data is divided into azimuths according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180 to obtain 6 groups of earthquake superposition earthquakes, such as Figure 3 .

[0033] Step 4: Generate, within the limited effective offset distance L, a full range of near-offset gathers stacking seismic amplitudes and a full range of far-offset gathers stacking seismic amplitudes.

[0034] Within the limited offset distance of 2037.5m, generate all-round near-offset gather stacked seismic data seismic_near and all-round far-offset gather stacked seismic data seismic_far according to 0m-1018.75m and 1018.75m-2037.5m, such as Figure 4 .

[0035] Step 5, using the divided effective offset distance and azimuth gathers, calculate and output the amplitude anisotropy value, and use this result as the seismic prediction result of the sedimentary facies belt.

[0036] The effective offset distance is defined in step 3, and then the azimuth angle is divided into 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180 degrees to obtain the effective offset distance azimuth gather.

[0037] The amplitude change rate is calculated using the divided effective offset and azimuth seismic data. The specific formula is: ); In the formula, is the amplitude change rate, is the maximum amplitude at position i, is the minimum amplitude of the i-th azimuth, where i is the azimuth angle number.

[0038] Calculate and output, and use this result as the sedimentary facies result of the study area, such as Figure 5 shown.

[0039] Step 6, using the difference between the stacked seismic amplitude of the omni-directional far-offset gather and the stacked seismic amplitude of the omni-directional near-offset gather, the offset amplitude difference attribute is obtained and the result is output, and the result is used as the prediction of the thickness of the reservoir prediction area.

[0040] The amplitude attribute of the target layer is extracted from the two sets of seismic data, and the seismic_near amplitude attribute is subtracted from the seismic_far amplitude attribute, and the offset amplitude difference attribute is output. The offset amplitude difference attribute is the reservoir deposition thickness of the study area, such as Figure 6 ; Step 7, according to the azimuth division method of step 3, the gradient attribute change rate is calculated using the effective offset distance azimuth gather, and the output is used as the prediction result of the fluid.

[0041] According to the azimuth division scheme in step 3, the AVO gradient attribute change rate G(i) is calculated using the effective offset distance divided azimuth gather. The specific calculation formula is:

[0042] ); In the formula, is the maximum effective offset amplitude value of the i-th azimuth, is the minimum offset amplitude value of the i-th azimuth; L is the effective offset, is the maximum gradient attribute change rate of the i-th direction, is the minimum gradient attribute change rate of the i-th direction.

[0043] ) are divided into 6 directions according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180.

[0044] The rate of change of the AVO gradient property is calculated and output, and the result is used as the prediction of the fluid, such as Figure 7 shown.

[0045] The present invention utilizes wide-azimuth seismic gather data. Compared with conventional three-dimensional seismic data and pre-stack offset domain seismic data, wide-azimuth seismic gather data can not only solve the seismic prediction of refining reservoir boundaries using elastic parameters, but also solve the problem that traditional pre-stack attributes are no longer applicable in anisotropic formations.

[0046] The present invention determines the effective offset of OVT seismic data by analyzing and clarifying the observation system of seismic acquisition, which can maintain the energy consistency of different azimuth stacking gathers when carrying out azimuth division of data, and eliminate the anisotropic prediction multi-solution caused by energy differences due to inconsistent coverage times.

[0047] The present invention proposes a progressive reservoir fine prediction method based on the change rate attribute, which can realize the prediction of reservoirs from macroscopic sedimentary distribution to reservoir and fluid prediction. It realizes layer-by-layer constraints, avoids the multiple solutions caused by a single prediction, and improves the scientificity, rationality and accuracy of reservoir prediction.

[0048] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. The embodiments should therefore be considered exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A progressive reservoir fine prediction method for wide-azimuth seismic change rate attributes, characterized by: Step 1, collecting OVT seismic data, interpretation layer data, and observation system parameters of the seismic acquisition area in the reservoir prediction area; Step 2: Analyze the parameters of the seismic acquisition observation system to determine the maximum north-south distance and the maximum east-west distance of the shot checkpoints in the seismic acquisition area, and take the minimum value of the two as the effective offset distance L; Step 3, limit the effective offset distance L and divide the OVT seismic data into azimuths; Step 4, generating a full range of near-offset gathers and a full range of far-offset gathers with stacked seismic amplitudes within a limited effective offset distance L; Step 5, using the divided effective offset distance and azimuth gathers to calculate and output the amplitude anisotropy value, and use this result as the seismic prediction result of the sedimentary facies belt; Step 6, using the difference between the stacked seismic amplitude of the omni-directional far-offset gather and the stacked seismic amplitude of the omni-directional near-offset gather, obtain the offset amplitude difference attribute and output the result, which is used as the prediction of the thickness of the reservoir prediction area; Step 7, according to the azimuth division method of step 3, the gradient attribute change rate is calculated using the effective offset distance azimuth gather, and the output is used as the prediction result of the fluid.

2. The progressive reservoir fine prediction method of wide-azimuth seismic change rate attributes according to claim 1 is characterized in that: In step 3, the principle of division is to divide the sector angle by 30 degrees at least, the number of sectors shall not be less than 6, and the azimuth angles shall be divided according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180.

3. The progressive reservoir fine prediction method of wide azimuth seismic change rate attributes according to claim 1 is characterized in that: In step 4, the near offset starts at 0 m, the end offset is no more than 1 / 2L, the far offset is no less than 1 / 2L, and the maximum is L.

4. The progressive reservoir fine prediction method of wide-azimuth seismic change rate attributes according to claim 1 is characterized in that: In step 5, the amplitude change rate value is calculated using the divided effective offset distance and azimuth seismic data: ） In the formula, is the amplitude change rate, is the maximum amplitude at position i, is the minimum amplitude of azimuth i, where i is the azimuth angle number.

5. The progressive reservoir fine prediction method of wide azimuth seismic change rate attributes according to claim 1, characterized in that: In step 7, according to the azimuth division method of step 3, the gradient attribute change rate G(i) is calculated using the effective offset distance divided azimuth gather: ； ； Where i=1,2,3,4,5,6; is the maximum effective offset amplitude value of the i-th azimuth, is the minimum offset amplitude value of the i-th azimuth.

6. The progressive reservoir fine prediction method of wide azimuth seismic change rate attributes according to claim 4 or 5, characterized in that: ) are divided into 6 directions according to 0-30, 30-60, 60-90, 90-120, 120-150, and 150-180.

Images