Method and device for constructing geologic model and method for analyzing geology

Abstract

The embodiment of the invention provides a method and device for constructing a geologic model and a method for analyzing geology, and the method comprises the steps: obtaining the region information of a to-be-measured region, the region information comprises a seismic data body and well information, and the well data comprises a logging curve and the thickness of actual drilling sand on a well; obtaining layering information according to the seismic data volume and the well information, and performing time-frequency analysis on the to-be-measured area according to the layering information to obtain a plurality of single-frequency bodies; according to the logging curve and the profile of the single-frequency body, single-well seismic calibration is carried out to obtain a first main frequency; carrying out RGB fusion on the first main frequency to obtain a first frequency division group, and obtaining a first response sand thickness of the first frequency division group; performing correlation analysis on the first response sand thickness and the actual drilling sand thickness on the ground to obtain a second frequency division group; and constructing the geologic model by using the second frequency division group. According to the method, the result of reservoir characterization analysis is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir architecture characterization, and particularly to a method for constructing a geological model, a device, and a method for analyzing geology. Background Art

[0002] With the advancement of oil and gas field production and development, the geological units controlling the distribution of remaining oil and gas are becoming smaller and smaller, and it is more difficult to understand the distribution of remaining oil and gas. The stable production and increased production of oilfields urgently require the fine characterization of reservoir architecture to determine the morphology, scale, and superimposition relationship of reservoir architecture units at different levels.

[0003] In recent years, domestic and foreign scholars have gradually refined the research on the architecture of braided river delta sandbodies. Rich achievements have been made in the research on the architecture of braided river delta reservoirs based on outcrop, modern sedimentation, and dense well pattern data. However, the delta sandbodies developed continuously in the same geological history period are the result of multi-stage channel migration and superimposition, with strong reservoir heterogeneity and complex planar distribution patterns. Under the relatively sparse well pattern conditions at sea, conventional seismic attribute analysis techniques such as attribute extraction, coherence slice, and multi-attribute fusion, as important means for predicting the distribution of reservoir architecture through "well-seismic combination", often have limitations in their results and are difficult to meet the needs of scientific research and production, thus severely restricting the efficient development of such gas reservoirs.

[0004] Although the research on the architecture of braided river delta sandbodies is constantly developing and innovating, the current method for characterizing the architecture of braided river delta reservoirs based on "well-seismic combination" under sparse well pattern conditions at sea is still in the exploratory stage, and an effective method for identifying architecture units has not yet been formed. The well spacing scale of this well pattern is relatively large compared to the continuously developed delta sandbodies, and there is uncertainty in seismic prediction between wells. The results obtained by conventional seismic analysis techniques have insufficient accuracy in depicting the boundaries of the fourth and fifth level architectures, unable to meet the requirements for fine dissection of the internal architecture of the reservoir, and also restricting subsequent geological modeling work. Summary of the Invention

[0005] The objective of the embodiments of the present invention is to provide a method for constructing a geological model, a device, and a method for analyzing geology, which can make the results of reservoir characterization analysis more accurate.

[0006] To achieve the above objective, the embodiments of the present invention provide a method for constructing a geological model, the method comprising: Obtaining regional information of a region to be measured, the regional information including a seismic data volume and well information, and the well data including logging curves and actual drilled sand thickness on the well; Obtaining stratification information based on the seismic data volume and well information, and performing time-frequency analysis on the region to be measured according to the stratification information to obtain a plurality of single-frequency bodies; Performing single-well well-seismic calibration on the logging curves and the profiles of the single-frequency bodies to obtain a first main frequency; Perform RGB fusion on the first main frequency to obtain a first frequency division group, and acquire the first response sand thickness of the first frequency division group; Perform correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group; Construct the geological model by using the second frequency division group.

[0007] Optionally, the time-frequency analysis of the area to be measured according to the stratification information to obtain multiple single-frequency bodies includes: Perform a generalized S transform on the stratification information to obtain information features; Perform frequency division processing on the information features according to a certain frequency band range to obtain multiple single-frequency bodies.

[0008] Optionally, the single-well well-seismic calibration according to the logging curve and the profile of the single-frequency body to obtain the first main frequency includes: Perform single-well well-seismic calibration on the profile of one single-frequency body among the multiple single-frequency bodies and its corresponding logging curve in sequence to obtain multiple main frequencies; Select the one with the best well-seismic response from the multiple main frequencies as the first main frequency.

[0009] Optionally, the performing RGB fusion on the first main frequency to obtain a first frequency division group includes: Perform RGB fusion on multiple first main frequencies in sequence to obtain multiple frequency division groups; Select the frequency division group with the best planar fusion graph effect among the multiple frequency division groups as the first frequency division group.

[0010] Optionally, the acquiring the first response sand thickness of the first frequency division group includes: Perform data transformation on the first frequency division group to obtain the sand body thickness corresponding to the RGB response of its frequency; The data transformation is a data transformation among frequency, wave velocity, wavelength, and seismic tuning thickness.

[0011] Optionally, the method further includes: Project the horizontal well well trajectory onto the planar fusion graph of the first frequency division group to obtain a fusion frequency division group, and acquire the second response sand thickness of the fusion frequency division group; Perform correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group.

[0012] Optionally, the first main frequency includes a low-frequency band main frequency, a middle-frequency band main frequency, and a high-frequency band main frequency; The single-frequency body is a seismic data body of a single frequency, and the single-frequency body includes absolute phase information.

[0013] On the other hand, the present invention also proposes a device for constructing a geological model, and the device includes: An acquisition module, configured to acquire area information of an area to be measured, where the area information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness in the well; A first processing module, configured to obtain stratification information based on the seismic data volume and well information, and perform time-frequency analysis on the area to be measured according to the stratification information to obtain a plurality of single-frequency volumes; A second processing module, configured to perform single-well well-seismic calibration on the logging curves and the profiles of the single-frequency volumes to obtain a first main frequency; A third processing module, configured to perform RGB fusion on the first main frequency to obtain a first frequency division group, and obtain a first response sand thickness of the first frequency division group; A fourth processing module, configured to perform correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group, and construct the geological model by using the second frequency division group.

[0014] Optionally, the performing RGB fusion on the first main frequency to obtain a first frequency division group includes: Performing RGB fusion on a plurality of first main frequencies in sequence to obtain a plurality of frequency division groups; Selecting the frequency division group with the best planar fusion graph effect among the plurality of frequency division groups as the first frequency division group.

[0015] Optionally, the apparatus further includes: a verification module, configured to project a horizontal well trajectory onto a planar fusion graph of the first frequency division group to obtain a fused frequency division group, obtain a second response sand thickness of the fused frequency division group, and perform correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group.

[0016] Optionally, the first main frequency includes a low-frequency band main frequency, a medium-frequency band main frequency, and a high-frequency band main frequency; The single-frequency volume is a seismic data volume with a single frequency, and the single-frequency volume includes absolute phase information.

[0017] On the other hand, the present application further provides a method for analyzing geology, which includes performing geological analysis on a geological model obtained by using the method for constructing a geological model described above to obtain geological parameters of an area to be measured.

[0018] On the other hand, the present application further provides a machine-readable storage medium, on which instructions are stored, and the instructions are used to cause a machine to execute the method for constructing a geological model described above.

[0019] On the other hand, the present application further provides a processor, configured to run a program, where the program, when run, is used to execute the method for constructing a geological model described above.

[0020] The present invention provides a method for constructing a geological model, which includes: obtaining regional information of a region to be measured, where the regional information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness in the well; obtaining stratification information based on the seismic data volume and well information, and performing time-frequency analysis on the stratification information to obtain multiple single-frequency bodies; performing single-well seismic calibration on the logging curves and the profiles of the single-frequency bodies to obtain a first main frequency; performing RGB fusion on the first main frequency to obtain a first frequency division group, and obtaining a first response sand thickness of the first frequency division group; performing correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group; and constructing the geological model using the second frequency division group. Through frequency division RGB fusion of the reservoir, the present application obtains signal features richer than the original seismic data volume. Combining methods such as time-frequency analysis, correlation analysis, horizontal well analysis, well-seismic combination, and plane-section interaction, more accurate seismic attribute analysis and a reservoir configuration characterization result with higher resolution can be obtained.

[0021] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification. They are used to explain the embodiments of the present invention together with the following specific implementation, but do not limit the embodiments of the present invention. In the drawings: Figure 1 is a flowchart of a method for constructing a geological model of the present invention; FIGS. 2a-2c are frequency division seismic profiles and frequency division RGB fusion seismic profiles of an embodiment of the present invention; FIG. 3 is a 60 Hz frequency division RGB fusion plane effect diagram of an embodiment of the present invention; FIG. 4 is a correlation diagram between the sand body thickness interpreted by logging and the RGB response sand body thickness of an embodiment of the present invention; FIG. 5 is a verification diagram of the frequency division RGB fusion effect based on the well-seismic information of the B3 horizontal well of an embodiment of the present invention; FIGS. 6a-6e are response characteristics of a frequency division RGB fusion plane effect diagram of an embodiment of the present invention; FIG. 7 is a reservoir configuration plan view of frequency division RGB fusion of an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The following will detail the specific implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiments of the present invention, and does not limit the embodiments of the present invention.

[0024] Embodiment 1 Figure 1 is a schematic flow chart of a method for constructing a geological model according to the present invention. As Figure 1 shown, the present invention provides a method for constructing a geological model, which includes: Step S101 is to obtain the regional information of the area to be measured, and the regional information includes seismic data volume and well information. The well data includes logging curves and actual drilled sand thickness on the well. The area to be measured is preferably a braided river delta reservoir under the condition of sparse well network in the sea. The well data also includes well name, well location (at the well point), well trajectory, logging GR curve, actual drilled sand body thickness on the well, wave velocity (reciprocal of acoustic travel time DT), etc.

[0025] Specifically, the logging curve is a GR curve, and the GR curve is a jagged curve with irregular changes along the well trajectory, which is used to display the change of rock gamma value at the well position. The gamma value of sandstone is lower than that of mudstone, and it is often used in combination with the seismic profile at the well position to identify and calibrate the sand-mudstone section. The sand thickness is the thickness of the sand body.

[0026] Step S102 is to obtain stratification information based on the seismic data volume and well information, and perform time-frequency analysis on the stratification information to obtain multiple single-frequency bodies. The single-frequency body is the original seismic body, and the single-frequency body includes absolute phase information. Preferably, the hierarchical analysis includes two steps: first, determine the fifth-level composite river channels at the large-scale level, and then determine the fourth-level single river channels at the small-scale level under the constraint of the fifth level.

[0027] According to a specific implementation manner, the performing time-frequency analysis on the stratification information to obtain multiple single-frequency bodies includes: performing a generalized S transform on the stratification information to obtain information characteristics; performing frequency division processing on the information characteristics according to a certain frequency band range to obtain multiple single-frequency bodies. For example, perform time-frequency analysis on each small layer according to the stratification information, obtain richer signal characteristics of each small layer compared with the original seismic data volume through the generalized S transform, and perform frequency division processing on the original seismic body with a spacing of 5 Hz within the frequency band range displayed in the spectrogram to obtain several single-frequency bodies.

[0028] The time-frequency analysis includes transforming the non-stationary seismic signal from the time domain through the generalized S transform to obtain a joint function of time and frequency, describing the energy density and intensity of the signal at different times and frequencies, and obtaining a spectrogram based on the generalized S transform. Among them, there is a phase factor in the generalized S transform, and the phase factor retains the absolute phase information corresponding to each frequency, which is a unique property compared with other time-frequency analysis methods.

[0029] When performing reservoir configuration characterization through seismic and logging data, the time-frequency analysis method of the generalized S transform is used to convert seismic signals. Under the conversion of a lossless reversible window function with adaptive resolution in both the time domain and the frequency domain for the original single-time-domain seismic signals, they are transformed into a new seismic data volume in the time-frequency joint domain, obtaining richer signal characteristics of each small layer compared to the original seismic data volume.

[0030] Step S103 is to perform single-well seismic calibration based on the logging curve and the profile of the single-frequency volume to obtain the first main frequency. Specifically, the process of performing single-well seismic calibration based on the logging curve and the profile of the single-frequency volume to obtain the first main frequency includes: sequentially performing single-well seismic calibration on the profile of one single-frequency volume among the multiple single-frequency volumes and its corresponding logging curve to obtain multiple main frequencies; selecting the one with the best well-seismic response from the multiple main frequencies as the first main frequency. For example, through the combination of the seismic profiles of each single-frequency volume and the logging GR curve for single-well seismic calibration, the main frequency with a good well-seismic response is preferably selected as the first main frequency.

[0031] Step S104 is to perform RGB fusion on the first main frequency to obtain the first frequency division group and acquire the first response sand thickness of the first frequency division group. Specifically, the process of performing RGB fusion on the first main frequency to obtain the first frequency division group includes: sequentially performing RGB fusion on multiple first main frequencies to obtain multiple frequency division groups; selecting the frequency division group with the best planar fusion map effect among the multiple frequency division groups as the first frequency division group.

[0032] Specifically, the first main frequency includes the main frequency in the low-frequency band, the main frequency in the middle-frequency band, and the main frequency in the high-frequency band. For example, if the frequency band range is 0 - 85 Hz, the low-frequency range can be set as 0 - 30 Hz, the middle frequency as 30 - 60 Hz, and the high frequency as 60 - 85 Hz.

[0033] The process of acquiring the first response sand thickness of the first frequency division group includes: performing data transformation on the first frequency division group to obtain the sand body thickness corresponding to the RGB response of its frequency; the data transformation is the data transformation among frequency, wave velocity, wavelength, and seismic tuning thickness.

[0034] According to a specific implementation manner, the low frequency, middle frequency, or high frequency is determined based on the sand body thickness corresponding to the first main frequency. The several single-frequency volumes of the three frequency volumes are repeatedly subjected to RGB fusion, and the frequency division group with a good planar fusion map effect is selected as the first frequency division group. According to the mathematical transformation relationship among the frequency, wave velocity, wavelength, and seismic tuning thickness of the first frequency division group, the RGB response sand thickness corresponding to its frequency is calculated as the first response sand thickness. Among them, the mathematical transformation relationship among frequency (f), wave velocity (v), wavelength (λ), and seismic tuning thickness (ΔZ) is: seismic tuning thickness ΔZ = λ / 4, and λ = v / f.

[0035] RGB fusion technology is based on the optimization of the main frequency of the original seismic data body through time-frequency analysis, and the three single-frequency bodies of low, medium and high frequencies or the three non-overlapping low, medium and high frequency band bodies selected near the main frequency are fused respectively corresponding to the three primary colors of R (red), G (green) and B (blue), and displayed in the form of plane slices. Different colors represent different thicknesses, and the brightness of the color scale represents different lithologies, thereby analyzing and depicting different geological bodies in the study area.

[0036] Step S105 is to perform a correlation analysis on the first response sand thickness and the actual drilling sand thickness on the well to obtain a second frequency division group. Specifically, the first response sand thickness of each well point displayed on the plane fusion map is statistically analyzed, and the correlation analysis is performed on it and the actual drilling sand thickness on the well, and the frequency division group with high correlation is selected as the second frequency division group.

[0037] Step S106 is to construct the geological model using the second frequency division group. According to a specific implementation, the present invention comprehensively applies hierarchical analysis, phase pattern guidance and recognized configuration splicing style, and constructs the geological model using the second frequency division group. The boundaries of the fourth and fifth level configuration units are identified according to the color difference and brightness change of the RGB mixed color display, and the fine dissection of the reservoir configuration is completed.

[0038] The method also includes: projecting the horizontal well trajectory onto the plane fusion map of the first frequency division group to obtain a fused frequency division group, obtaining the second response sand thickness of the fused frequency division group; performing correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group. Specifically, the horizontal well trajectory is projected onto the plane fusion map, and the frequency division RGB fusion effect is analyzed and evaluated in combination with the horizontal well information, and the final frequency division group is selected based on the correlation analysis. The hierarchical analysis, phase pattern guidance and recognized configuration splicing styles are comprehensively applied. On the plane fusion map, the boundaries of the fourth and fifth level configuration units are identified according to the color differences and brightness changes of the mixed color display, and the fine dissection of the reservoir configuration is completed.

[0039] The phase model guidance includes the sedimentary microfacies type, river channel planar distribution morphology and configuration unit contact relationship of the braided river delta sedimentary system. The configuration splicing style includes overlapping type, contact type and segmentation type.

[0040] Compared with conventional seismic attribute analysis technology, the present invention is more accurate and has higher resolution; and by converting seismic signals from a single time domain into a joint time-frequency domain, richer seismic information can be mined.

[0041] Embodiment 2 In this application, the time-frequency analysis technology can be short-time Fourier transform (STFT), continuous wavelet transform (CWT), and generalized S transform. The generalized S transform is a method combining the former two, having both the advantages of STFT and CWT and solving the deficiencies of STFT and CWT. In addition, due to the presence of a phase factor in the S transform, the phase factor retains the absolute phase information corresponding to each frequency, which is a unique property compared with the former two. Its basic principle is as follows: The calculation method of the S transform proposed by StockWell is as follows: (1)

[0042] Wherein, is the frequency (Hz); τ is the center of the time window (ms), and the position of the window function on the time axis changes with the change of τ. Formula (1) uses a Gaussian window function with scale :

[0043] (2)

[0044] In order for the S transform to adjust the time-frequency resolution, a parameter β is added for adjustment, and thus the form of the window function becomes: (3)

[0045] Replacing the window function in formula (1) with the new window function with the adjustment parameter, the calculation method of the generalized S transform is obtained: (4)

[0046] The time width and frequency width of the window function are controlled by the adjustment parameter β. Different values of the adjustment parameter are selected, and the time width and frequency width of the window function change accordingly, resulting in different resolutions of the time-frequency spectrum results. Therefore, the signal characteristics obtained by the time-frequency analysis method of the generalized S transform are more accurate and have higher resolution than other methods.

[0047] As Figure 2a shown, the frequency spectrum diagram shows that the frequency band range of the target horizon of the original seismic body is 0 - 85 Hz, and the main frequencies (ƒ) are 23 Hz and 35 Hz. In the frequency band range, frequency division with a small interval can be carried out at an interval of 5 Hz. Combining well and seismic data, the cross-well profiles of each single-frequency seismic body are calibrated, and the single-frequency body with good correspondence between the seismic in-phase axis reflection characteristics and the sand body section corresponding to the response of the GR curve on the well is selected. The GR curve is a serrated curve that changes irregularly along the well trajectory and is used to show the change of the rock gamma value at the cross-well position. The curve is small on the left and large on the right. Among them, A1, A2, and A3 are the well names of 3 exploration wells in the study area of the embodiment, H5Top is the top interface of the target horizon in the study area of the embodiment, and H6Top is the bottom interface of the target horizon in the study area of the embodiment.

[0048] AsFigure 2b and 2c As shown, the in-phase axis of the 23Hz single-frequency body has the best response to the thick sand body above the well, which is a continuous strong reflection trough. After repeated frequency division tests in the frequency band above 23Hz and within 30 - 85Hz, the higher the frequency, the smaller the corresponding sand body thickness. Under the constraint of the sand body thickness range above the well, the medium and high frequencies are optimized, and they are RGB fused with the low-frequency body (23Hz) and sliced for display. After multiple frequency division fusions, three groups of frequency division fusion bodies are optimized (12Hz, 23Hz, 40Hz; 23Hz, 35Hz, 47Hz; 23Hz, 35Hz, 60Hz). In the first group, 23Hz is used as the medium frequency, and 12Hz is used to identify sand bodies in the work area that may be thicker than the thick sand above the well. In the latter two groups, the thick sand above the well responded by 23Hz is used as the thick sand in the entire study area, and the frequency corresponding to the thin sand is determined by changing the high-frequency value. Among them, the RGB fusion effect of the 23Hz, 35Hz, and 60Hz frequency division bodies is the best. The low, medium, and high frequencies are respectively mapped to red, green, and blue to represent the thick sand, medium-thick sand, and thin sand of the target layer.

[0049] It can be seen from the well-seismic calibration results of the frequency division RGB fusion body that the brightness of the color is closely related to the mud content. Black and dark areas often respond to mud, and bright areas mostly respond to sand bodies calibrated by strong reflection troughs. Different colors respond to different lithologies and thicknesses. The boundaries and morphologies of each lithology are visually presented on the plane with the slice as the carrier, so as to identify the distribution characteristics of each sedimentary microfacies in the braided river delta front facies of the target layer.

[0050] As Figure 3 shown, based on the fine seismic interpretation of the target layer, the plane fusion effect of the frequency division RGB fusion formation slice is analyzed. The sand bodies drilled in the well area basically respond to the mixture of red, green, and blue, and the degree of sand body development is relatively high. The well penetration rate of the target layer reaches 93%. Mudstone responds to dark areas, and the color difference also clearly depicts the sand body boundary. The braided river delta front composite channel system in the study area is mainly divided into four stages of composite channels along the provenance direction. The white dotted line is the envelope line of the macroscopic distribution of the sand body, corresponding to the configuration boundary of the fifth-level composite channel in the braided river delta front of the study area. The evolutionary characteristics of the sand body thickness in space and time are characterized by different ratios of the three primary colors. The brightness can reflect the mud content. The dark area has a high mud content, and bright, moderately bright, and dim respectively represent pure sandstone, muddy sandstone, and mudstone. Among them, A1 - A4 are the well names of 4 exploration wells in the study area of the embodiment, and B1 - B11 are the well names of 11 development wells.

[0051] As Figure 4As shown in the figure, using the logging data of 4 exploration wells and 11 development wells in the study area, the thickness distribution range of individual sand bodies measured in the wells was statistically analyzed. Combining the well-seismic calibration results, a correlation analysis was carried out on the sand body thickness of each well's response in the optimized frequency-divided RGB fusion body and the sand body thickness measured in the wells. The results show that there is a strong correlation between the two. Among the selected 3-component frequency-divided fusion bodies, the 23Hz, 35Hz, and 60Hz frequency-divided RGB fusion has the best response effect with the single sand body thickness in the wells. The average velocity (v) of the sandstone in this sand layer group was calculated to be 4153 - 4355 m / s through the acoustic travel time (DT) of the exploration wells. According to the seismic tuning thickness ΔZ = λ / 4 (λ is the wavelength), λ = v / f, the seismic tuning thicknesses corresponding to the high frequency of 60Hz and the low frequency of 23Hz are 17m and 45m respectively. A correlation analysis was carried out on the RGB-predicted sand body thickness and the actual drilled thickness in the wells, and the correlation coefficient R = 0.7999.

[0052] As Figure 5 shown, the frequency-divided RGB fusion prediction results are relatively consistent with the measured results in the wells. Among them, the thick sand wells with large box-shaped bell-shaped low GR shown by logging are all located in the low-frequency red area or the high-brightness white area representing the relatively pure lithology of the thick-layer sandstone deposition center. The thin sand and medium-thick sand wells with interbedded sand and mud shown by logging are located in the blue-green area. Among them, the B3 horizontal well drilled along the provenance direction encounters a single channel, which shows a continuous strong-amplitude trough on the seismic data, and the GR curve of the logging shows a large box shape, which coincides with the thick sand with continuous high-brightness white response shown by the frequency-divided RGB.

[0053] Comprehensively applying hierarchical analysis, facies model guidance, and identified configuration splicing patterns, combined with the detection results of the lateral splicing patterns of the horizontal well configuration boundaries, based on the sedimentary pattern of "wide dam and narrow river" in modern braided rivers, on the RGB frequency-divided fusion slice, using the strip-shaped dark response characteristics inside the 5th-level composite channel as the 4th-level configuration unit boundary, the 4th-level configuration boundaries of the 5th-level composite channels divided in the study area were identified respectively.

[0054] As Figure 6a-6e shown, a cross-section of the well connected to the provenance was selected, and the lateral splicing patterns of the 4th-level single-channel configuration units were identified through the combination of well and seismic data, which were divided into three types: single-channel - single-channel independent type, single-channel - single-channel superimposed type, and single-channel - single-channel cut-and-overlapped type. Figure 6a-6b In the independent type and superimposed type of the fourth-level boundaries, the shale content is relatively high and not connected, which plays a lateral blocking role between the sand bodies. The shale content of the cut-and-overlapped type of the fourth-level boundary is low, which is a semi-connected seepage barrier. The sand bodies of the three single channels where wells B1, A2, and B3 are located are clearly separated by shale filling. Horizontally, wells B1 and A2 show the single-channel - single-channel independent type, and A2 and B3 show the single-channel - single-channel superimposed type, and the GR curves of the logging show different box-shaped characteristics.

[0055] Figure 6a , 6b For the corresponding frequency division RGB fusion effect display in 6e, the positions of Wells B1, A2, and B3 show three colors and brightness levels respectively. Well B1, a horizontal well, is located in a single channel within Compound Channel II that converges into Compound Channel I. The sand body thickness is small and corresponds to a blue-green response. The horizontal section drills through a continuous black band towards the south, corresponding to the boundary of a fourth-order single channel configuration. Well A2, a vertical well, is located in a single channel within Compound Channel II. The sand body thickness is large and corresponds to a red response, with a medium brightness and a small amount of mud. Well B3, a horizontal well, is located in a single channel within Compound Channel II. The sand body thickness is large and corresponds to a white response, with a high brightness and little mud, being a pure sandstone. There are continuous and obvious black bands in the direction of the sediment source between any two of the three wells, which coincides with the fourth-order single channel configuration boundary in the single channel - single channel independent type and single channel - single channel superimposed type presented in the seismic profile.

[0056] Figure 6c , 6d For Wells B2, A1, and B4 in 6e, the channel sand bodies are not completely separated by mud filling and are shown as troughs with weak amplitudes. Horizontally, the channel sand bodies between any two of the three wells show a single channel - single channel overlapping type, and the GR logging curves show similar box-shaped and bell-shaped characteristics. For the corresponding frequency division RGB fusion effect display, the positions of Wells B2, A1, and B4 show three colors and brightness levels respectively, all being warm colors corresponding to thick sand. There are continuous and obvious warm color band boundaries formed by color differences in the direction of the sediment source between any two of the three wells, and they are different from the black mud bands corresponding to the above independent type and superimposed type, which coincides with the fourth-order single channel configuration boundary in the single channel - single channel overlapping type presented in the seismic profile. The fifth-order and fourth-order boundary contours presented in the frequency division RGB fusion map are clear, and the color differences on both sides of the boundary are obvious and easy to identify, and they can be well responded to by both wells and seismic data.

[0057] As Figure 7 shown, under the guidance of the braided river delta front sedimentation model, combined with the frequency division RGB fusion results, the fifth-order and fourth-order configuration unit plane is characterized. Five fifth-order compound channel configuration boundaries are divided in the whole area. The width of the fifth-order configuration unit is 1000 - 3000m, and the thickness is 15 - 80m. Fourth-order single channel configuration boundaries are divided within the fifth-order configuration unit, and the connectivity characteristics are qualitatively and finely characterized according to the lateral division scheme of the fourth-order configuration unit. The width of the fourth-order configuration unit is 150 - 800m.

[0058] Example 3 On the other hand, the present invention also provides a device for constructing a geological model, which includes: an acquisition module for acquiring regional information of a region to be measured, where the regional information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness in the well; a first processing module for obtaining stratification information based on the seismic data volume and well information, and performing time-frequency analysis on the stratification information to obtain a plurality of single-frequency bodies; a second processing module for performing single-well seismic calibration on the logging curves and the profiles of the single-frequency bodies to obtain a first main frequency; a third processing module for performing RGB fusion on the first main frequency to obtain a first frequency division group, and obtaining a first response sand thickness of the first frequency division group; a fourth processing module for performing correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group, and constructing the geological model using the second frequency division group. The performing RGB fusion on the first main frequency to obtain a first frequency division group includes: sequentially performing RGB fusion on a plurality of first main frequencies to obtain a plurality of frequency division groups; selecting a first frequency division group from the plurality of frequency division groups, where the planar fusion map of the first frequency division group meets a certain threshold. The device further includes: a verification module for projecting the horizontal well trajectory onto the planar fusion map of the first frequency division group to obtain a fusion frequency division group, obtaining a second response sand thickness of the fusion frequency division group, and performing correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group. The geological model obtained by the device is used to analyze the results of reservoir characterization more accurately.

[0059] Embodiment 4 On the other hand, the present invention also provides a method for analyzing geology, which includes performing geological analysis on the geological model obtained by using the above-mentioned method for constructing a geological model to obtain geological parameters of the region to be measured. For example: performing fine characterization of reservoir architecture on the geological model by means of hierarchical analysis, facies pattern guidance, and identification of configuration splicing style constraints to obtain geological features of the region to be measured, where the geological features include spatio-temporal evolution features of fourth- and fifth-level configuration units and connectivity features between channel sand bodies.

[0060] The present invention provides a method for constructing a geological model, which includes: obtaining regional information of a region to be measured, where the regional information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness on the well; obtaining stratification information based on the seismic data volume and well information, and performing time-frequency analysis on the stratification information to obtain a plurality of single-frequency bodies; performing single-well seismic calibration on the logging curves and the profiles of the single-frequency bodies to obtain a first main frequency; performing RGB fusion on the first main frequency to obtain a first frequency division group, and obtaining a first response sand thickness of the first frequency division group; performing correlation analysis on the first response sand thickness and the actual drilled sand thickness on the well to obtain a second frequency division group; and constructing the geological model by using the second frequency division group. Through frequency division RGB fusion of the reservoir, the present application obtains signal characteristics richer than the original seismic data volume. Combining methods such as time-frequency analysis, correlation analysis, horizontal well analysis, well-seismic combination, and plane-section interaction, more accurate seismic attribute analysis and a reservoir configuration characterization result with higher resolution are obtained.

[0061] An embodiment of the present application provides a storage medium, on which a program is stored, and when the program is executed by a processor, the method for constructing a geological model as described above is implemented.

[0062] An embodiment of the present application provides a processor, which is used to run a program, and when the program runs, the method for constructing a geological model as described above is executed.

[0063] An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored on the memory and executable on the processor. When the processor executes the program, the method for constructing a geological model as described above is implemented.

[0064] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0065] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementation in the process Figure 1one or more processes and / or blocks Figure 1 means for the functions specified in one or more blocks

[0066] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means that implements the functions in the process Figure 1 one or more processes and / or blocks Figure 1 specified in one or more blocks

[0067] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the process Figure 1 one or more processes and / or blocks Figure 1 specified in one or more blocks

[0068] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory

[0069] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media

[0070] Computer-readable media includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves

[0071] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0072] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for constructing a geological model, characterized in that, The method includes: Obtaining regional information of the area to be measured, where the regional information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness in the well; Obtaining stratification information based on the seismic data volume and well information, and performing time-frequency analysis on the area to be measured according to the stratification information to obtain multiple single-frequency bodies; Performing single-well seismic calibration on the logging curve and the profile of the single-frequency body to obtain a first main frequency; Performing RGB fusion on the first main frequency to obtain a first frequency division group, and obtaining a first response sand thickness of the first frequency division group; Performing correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group; Constructing the geological model using the second frequency division group.

2. The method according to claim 1, wherein The performing time-frequency analysis on the area to be measured according to the stratification information to obtain multiple single-frequency bodies includes: Performing a generalized S transform on the stratification information to obtain information characteristics; Performing frequency division processing on the information characteristics according to a certain frequency band range to obtain multiple single-frequency bodies.

3. The method according to claim 1, wherein The performing single-well seismic calibration on the logging curve and the profile of the single-frequency body to obtain a first main frequency includes: Sequentially performing single-well seismic calibration on the profile of a single-frequency body in the multiple single-frequency bodies and its corresponding logging curve to obtain multiple main frequencies; Selecting the one with the best well-seismic response from the multiple main frequencies as the first main frequency.

4. The method according to claim 1, wherein The performing RGB fusion on the first main frequency to obtain a first frequency division group includes: Sequentially performing RGB fusion on multiple first main frequencies to obtain multiple frequency division groups; Selecting the frequency division group with the best planar fusion graph effect from the multiple frequency division groups as the first frequency division group.

5. The method according to claim 1, wherein The obtaining a first response sand thickness of the first frequency division group includes: Performing data transformation on the first frequency division group to obtain the sand body thickness corresponding to the RGB response of its frequency; The data transformation is a data transformation among frequency, wave velocity, wavelength, and seismic tuning thickness.

6. The method according to claim 1, characterized in that The method further includes: Projecting the horizontal well trajectory onto the planar fusion graph of the first frequency division group to obtain a fused frequency division group, and obtaining a second response sand thickness of the fused frequency division group; Performing correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group.

7. According to the method described in claim 1, wherein The first main frequency includes a low-frequency band main frequency, a medium-frequency band main frequency, and a high-frequency band main frequency; The single-frequency body is a seismic data volume of a single frequency, and the single-frequency body includes absolute phase information.

8. An apparatus for constructing a geological model, characterized in that, The device includes: An obtaining module, configured to obtain regional information of the area to be measured, where the regional information includes a seismic data volume and well information, and the well data includes logging curves and actual drilled sand thickness in the well; A first processing module, configured to obtain stratification information based on the seismic data volume and well information, and perform time-frequency analysis on the area to be measured according to the stratification information to obtain multiple single-frequency bodies; A second processing module, configured to perform single-well seismic calibration on the logging curve and the profile of the single-frequency body to obtain a first main frequency; A third processing module, configured to perform RGB fusion on the first main frequency to obtain a first frequency division group, and obtain a first response sand thickness of the first frequency division group; A fourth processing module, configured to perform a correlation analysis on the first response sand thickness and the actual drilled sand thickness in the well to obtain a second frequency division group, and construct the geological model by using the second frequency division group.

9. The device according to claim 8, wherein The step of performing RGB fusion on the first main frequency to obtain a first frequency division group includes: Performing RGB fusion on multiple first main frequencies in sequence to obtain multiple frequency division groups; Selecting the frequency division group with the best planar fusion map effect among the multiple frequency division groups as the first frequency division group.

10. The device according to claim 8, characterized in that, The apparatus further includes: A verification module, configured to project the horizontal well trajectory onto the planar fusion map of the first frequency division group to obtain a fused frequency division group, obtain a second response sand thickness of the fused frequency division group, and perform a correlation analysis on the second response sand thickness and the well information to obtain a second frequency division group.

11. The apparatus according to claim 8, wherein The first main frequency includes a low-frequency band main frequency, a medium-frequency band main frequency, and a high-frequency band main frequency; The single-frequency body is a seismic data body with a single frequency, and the single-frequency body includes absolute phase information.

12. A method for analyzing geology, characterized in that, The method includes performing geological analysis by using the geological model obtained by the method according to any one of claims 1-7 to obtain geological parameters of the area to be measured.

13. A machine-readable storage medium, characterized in that, Instructions are stored on the machine-readable storage medium, and the instructions are used to cause the machine to execute a method for constructing a geological model according to any one of claims 1-7.

14. A processor, characterized in that, For running a program, wherein the program, when run, is used to execute a method for constructing a geological model according to any one of claims 1-7.

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