A wave impedance inversion method

Abstract

This invention relates to a wave impedance inversion method, comprising the following steps: Step 1, collecting post-stack seismic data, sonic logging curves, density logging curves, lithology-representing curves, and reservoir interpretation results within the work area; Step 2, calculating wave impedance curves based on sonic logging and density logging curves; Step 3, assigning values ​​to various types of reservoirs to obtain formation identification codes; and reconstructing the wave impedance curves using the formation identification codes to obtain reconstructed wave impedance curves; Step 4, performing intersection analysis using the lithology-representing curves and the reconstructed wave impedance curves; Step 5, performing wave impedance inversion on the post-stack seismic data using the reconstructed wave impedance curves. This invention can directly identify effective energy storage with high accuracy.

Description

Technical Field

[0001] This invention relates to a wave impedance inversion method, belonging to the field of seismic data processing technology. Background Technology

[0002] Impedance inversion is a technique that uses post-stack seismic data for inversion. It combines seismic data, well logging data, and geological interpretation, making full use of the high vertical resolution of well logging data and the good lateral continuity of seismic profiles to convert seismic profiles into impedance profiles. This not only makes it easier for interpreters to connect and compare seismic data with well logging data, but also effectively studies the changes in formation properties, thereby obtaining the spatial distribution patterns of physical parameters and guiding oil and gas exploration and development.

[0003] However, for most basins in my country, due to the strong diagenesis of sedimentary rocks, the difference in wave impedance between reservoirs and non-reservoirs is small. It is difficult to identify reservoirs based on wave impedance property profiles obtained by inversion technology.

[0004] To address the challenge of identifying reservoirs using conventional impedance retrieval techniques due to the small difference in acoustic impedance between reservoirs and non-reservoir areas, many scholars have proposed acoustic impedance retrieval techniques based on curve reconstruction, achieving good results. For example, the paper "Application of Wave Group Impedance Inversion Based on Characteristic Curve Reconstruction in Prediction of Complex Reservoirs" (Yu Weiwei et al., 2019.2.8) proposes an acoustic impedance retrieval method based on characteristic curve reconstruction. This method utilizes seismic and well logging data, starting from the characteristics of acoustic logging data. Based on correlation analysis, it integrates different characteristic curves such as natural gamma, spontaneous potential, and resistivity with acoustic curves according to different weights to construct reconstructed characteristic curves. On this basis, reservoirs are identified through well logging-constrained acoustic impedance retrieval.

[0005] The wave impedance profile obtained by the above-mentioned method of reconstructing characteristic curves has a certain positive effect on reservoir identification, but its ability to identify effective reservoirs (oil and gas reservoirs) is still limited and the identification accuracy is not high.

[0006] A patent document with publication number CN108802812A discloses a well-seismic fusion method for stratigraphic lithology inversion. This method combines well logging curves and seismic data, uses a neural network algorithm to compare well logging lithology data and seismic lithology data to obtain a lithology fusion parameter volume, and then uses this parameter to perform layered, segment-weighted fusion of the well logging lithology data volume and the seismic lithology data volume to obtain the inverted lithology volume. For example... Figure 11 (The specification of this patent document is attached) Figure 11 As shown in the figure, there is still a large overlap in the wave impedance in the longitudinal section.

[0007] Patent document CN106842289A discloses a method for decompacting P-wave impedance curves applicable to well logging constrained inversion. This method extracts P-wave impedance curves for each lithology, removes the non-compacted components of the P-wave impedance, and subtracts the compacted P-wave impedance curves for each lithology. The resulting decompacted P-wave impedance curves are then used in subsequent P-wave impedance inversion, effectively amplifying the P-wave impedance differences between the reservoir and the surrounding rock. However, when using the methods described in the two patent documents for lithological P-wave impedance inversion, there is still a significant overlap between the reservoir and the surrounding rock in the P-wave impedance distribution range, making effective differentiation difficult.

[0008] When using the methods described in the two patent documents above to perform lithological impedance inversion, there is still a large overlap between the reservoir and the surrounding rock in the P-wave impedance distribution range, making it difficult to effectively distinguish them. Summary of the Invention

[0009] The purpose of this application is to provide a wave impedance inversion method to solve the problem that existing wave impedance inversion methods are unable to effectively distinguish between reservoirs and surrounding rocks in the P-wave impedance range.

[0010] To achieve the above objectives, this invention proposes a wave impedance inversion method, comprising the following steps:

[0011] Step 1: Collect post-stack seismic data, sonic logging curves, density logging curves, lithology curves, and reservoir interpretation results within the work area;

[0012] Step 2: Calculate the wave impedance curve based on the acoustic logging curve and the density logging curve;

[0013] Step 3: Assign values ​​to various types of reservoirs to obtain formation identification codes; and reconstruct the wave impedance curves using the formation identification codes to obtain the reconstructed wave impedance curves.

[0014] Step 4: Perform an intersection analysis between the lithology curve and the reconstructed wave impedance curve to determine the reservoir identification capability of the reconstructed wave impedance curve. If the reconstructed wave impedance curve cannot identify an effective reservoir, adjust the values ​​assigned to various types of reservoirs and reconstruct the wave impedance curve again until the reconstructed wave impedance curve can identify an effective reservoir.

[0015] Step 5: Use the reconstructed wave impedance curves to perform wave impedance inversion on the post-stack seismic data volume.

[0016] Furthermore, the step of assigning values ​​to various types of reservoirs includes: setting a tuning coefficient k, and assigning values ​​to each reservoir based on k, with each reservoir being a corresponding multiple of k.

[0017] Furthermore, based on dry layers, water layers, low-yield oil / low-yield gas layers, and oil / gas layers, 2*k, 3*k, 4*k, and 5*k are assigned respectively.

[0018] Furthermore, in step three, the formation identification code is multiplied by the wave impedance curve to obtain the reconstructed wave impedance curve.

[0019] Furthermore, step three also includes the step of interpolating the stratigraphic identification code.

[0020] Furthermore, in step four, the assignment to various types of reservoirs is adjusted by increasing the value of k by a predetermined step size Δk.

[0021] Furthermore, the initial value of k is 1, and Δk is 0.1.

[0022] Furthermore, the curve representing lithology is a natural gamma curve or a caliber curve.

[0023] The beneficial effects of this invention are: This invention reconstructs the wave impedance curve by integrating the results of reservoir interpretation, and, based on intersection analysis, distinguishes the reconstructed wave impedance attributes of different types of reservoirs and non-reservoirs. By constraining the reconstructed wave impedance curve, seismic inversion technology can be applied, which can obtain a high-precision wave impedance attribute body. Based on this wave impedance attribute body, effective reservoirs can be directly identified with high accuracy. Attached Figure Description

[0024] Figure 1 This is a flowchart of the present invention;

[0025] Figure 2 The acoustic waveform, density curve, natural gamma curve, and calculated wave impedance curve of a certain well are provided.

[0026] Figure 3 This is a table showing the comprehensive interpretation results of well logging for a certain well;

[0027] Figure 4 The numerical results of the comprehensive interpretation table of well logging results for a certain well;

[0028] Figure 5 Interpretation code for a specific stratum in a specific well;

[0029] Figure 6 Interpret the formation code curve for a certain well;

[0030] Figure 7 The reconstructed wave impedance curve of a certain well;

[0031] Figure 8 This is a diagram showing the intersection of the reconstructed wave impedance curve and the natural gamma curve.

[0032] Figure 9This is based on the reconstructed wave impedance inversion profile;

[0033] Figure 10 This is a conventional wave impedance inversion profile;

[0034] Figure 11 To obtain the cross-sectional image of the inverted lithological body using a well-seismic fusion stratigraphic lithology inversion method;

[0035] Figure 12 This is the probability density distribution of the longitudinal wave impedance curve obtained by using a wave impedance curve decompaction processing method suitable for well logging constrained inversion. Detailed Implementation

[0036] The present invention will now be described in detail with reference to the accompanying drawings.

[0037] like Figure 1 The steps of this invention are as follows:

[0038] Step 1: Data preparation.

[0039] A three-dimensional post-stack seismic data volume for a certain depression was obtained. This data volume was acquired in 2017, and the area is 12.5 meters × 12.5 meters.

[0040] Collect logging data from completed drilling operations in this work area, including the acoustic density curve, wave curve, and natural gamma curve of a certain well, as shown below. Figure 2 The first three columns of curves are shown, where DT represents the sound wave curve, RHOB is the density curve, and GR is the natural gamma curve. Figure 2 The sampling rate Δh for various logging curves in the data is uniformly set to 0.125 meters at depth.

[0041] Collect the comprehensive interpretation results of well logging from the completed wells in this work area, such as... Figure 3 As shown.

[0042] Step 2: Calculate the wave impedance.

[0043] Let the acoustic wave curve be DT(i) and the density curve be RHOB(i), where i = 1, 2, ..., N, representing the sampling point at depth, and the depth corresponding to point i is i*Δh. The wave impedance curve P(i) is obtained by multiplying the acoustic wave curve and the density curve, i.e., P(i) = DT(i)*RHOB(i). Figure 2 The fourth column of curves (pimp).

[0044] Step 3, wave impedance reconstruction.

[0045] A tuning coefficient k is set, and in this embodiment, the initial value of k is set to 1. Then, according to the dry layer, water layer, low-yield oil / low-yield gas layer, and oil / gas layer, k is assigned 2*k, 3*k, 4*k, and 5*k respectively. The well logging interpretation results table obtained in step one is then quantified, as shown below. Figure 4 As shown.

[0046] Simultaneously, all sections in the well that were not comprehensively interpreted were identified as non-reservoir sections. For example, the section between sections 23 and 24 (3523.4–3532.2) in Table 3, which was not interpreted by well logging, was identified as a non-reservoir section, assigned 1*k, and merged with the comprehensive interpretation table of well logging values ​​obtained in step three to obtain the complete formation identification codes for this well section. Figure 5 As shown.

[0047] The obtained stratigraphic identification code is interpolated with an interpolation step size of Δh to obtain the complete stratigraphic identification code C(i), as follows. Figure 6 As shown in (explain_logs). The purpose of interpolation is to make the strata code more complete.

[0048] By multiplying the identification code C(i) by the wave impedance curve P(i), the reconstructed wave impedance curve P'(i) is obtained, as follows: Figure 7 As shown in (pimp_CG).

[0049] Step 4: Cross-cutting analysis and adjustment of the reconstruction results.

[0050] The reconstructed wave impedance curve is intersected with the natural gamma curve collected in step one. If the effective reservoir (i.e., the oil and gas-bearing reservoir) cannot be distinguished from other strata on the intersecting map (i.e., it cannot be clearly separated), then the tuning coefficient k is increased by a step size Δk = 0.1, and step three is repeated until the effective reservoir can be distinguished from other strata on the intersecting map.

[0051] If the effective reservoir can be well distinguished from other formations through cross-plot analysis, then the acoustic impedance curve P'(i) obtained in step three is accepted. Figure 8 As shown, circle 1 represents the oil and gas reservoir, circle 2 represents the dry layer, and circle 3 represents the non-reservoir layer. Among them, the oil and gas reservoir has the highest wave impedance, followed by the dry layer, and the non-reservoir layer has the lowest. The circles can be clearly separated, that is, the oil and gas reservoir, dry layer, and non-reservoir layer can be well distinguished by wave impedance.

[0052] Step 5: Wave impedance inversion.

[0053] Using the reconstructed wave impedance curve P'(i) and the three-dimensional post-stack seismic data volume collected in step one, well-logging constrained wave impedance inversion is performed to obtain the final wave impedance profile, as shown below. Figure 9 As shown.

[0054] To demonstrate the effects of the present invention, a comparison was made in this embodiment: such as Figure 10 The wave impedance profile obtained based on conventional wave impedance inversion techniques, such as Figure 11To obtain the cross-sectional image of the inverted lithological body using a well-seismic fusion stratigraphic lithology inversion method, such as... Figure 12 To compare the probability density distribution of the P-wave impedance curve obtained by using a wave impedance curve decompaction processing method suitable for well logging constrained inversion, and to... Figure 9 It can be seen that the longitudinal resolution of the wave impedance volume obtained by this invention is much higher than that of the standard wave impedance volume. Figure 10 , Figure 11 , Figure 12 The wave impedance body in the middle has a higher degree of consistency with the completed wells, which greatly improves the accuracy of effective reservoir identification.

[0055] In the above embodiments, the dry layer, water layer, low-yield oil / gas layer, and oil / gas layer are assigned 2*k, 3*k, 4*k, and 5*k respectively, and k is increased by a step size Δk during the adjustment of the assignment in step four. As other embodiments, the assignment can also be performed in other ways, but the basic requirement is that the assignment value of the oil / gas layer is the largest, and the difference between the assignment values ​​of each layer and the oil / gas layer should be greater during the adjustment of the assignment in step four.

[0056] In the above embodiments, natural gamma curves are used for intersection analysis. In other embodiments, other types of curves that can represent lithology, such as wellbore curves, can also be used.

Claims

1. A wave impedance inversion method, characterized by, The method comprises the following steps: 1) collecting a post-stack seismic data volume, sonic logging curves, density logging curves, rock property indicating curves and reservoir interpretation results in a work area; 2) calculating wave impedance curves according to the sonic logging curves and the density logging curves; 3) setting a tuning coefficient k and assigning values to each reservoir based on k to obtain a formation identification code; and multiplying the formation identification code with the wave impedance curves to obtain reconstructed wave impedance curves, wherein 2*k, 3*k, 4*k and 5*k are respectively assigned to dry layers, water layers, low-yield oil / gas layers and oil / gas layers according to the dry layers, the water layers, the low-yield oil / gas layers and the oil / gas layers; 4) performing crossplot analysis on the rock property indicating curves and the reconstructed wave impedance curves to determine the reservoir identification ability of the reconstructed wave impedance curves; if the reconstructed wave impedance curves cannot identify effective reservoirs, adjusting the values assigned to various types of reservoirs, reconstructing the wave impedance curves again until the reconstructed wave impedance curves can identify effective reservoirs; 5) using the reconstructed wave impedance curves to perform wave impedance inversion on the post-stack seismic data volume.

2. The wave impedance inversion method of claim 1, wherein, In step 3), the method further comprises a step of interpolating the formation identification code.

3. The wave impedance inversion method of claim 1, wherein, In step 4), the adjustment of the values assigned to various types of reservoirs is increasing the value of k by a predetermined step size Δk.

4. The wave impedance inversion method of claim 3, wherein, The initial value of k is 1 and Δk is 0.

1.

5. The wave impedance inversion method according to any one of claims 1-4, wherein, The rock property indicating curves are natural gamma ray curves or caliper curves.

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