Lithology fine characterization method based on in-hole logging combined waveform phase control technology

Abstract

The invention discloses a lithology fine characterization method based on in-hole logging combined waveform phase control technology, and the method comprises the steps: enabling seismic waveform indication inversion and simulation to be applied to lithology fine characterization based on a phase control idea, reflecting the lithology characteristics through the transverse change of a waveform, and improving the longitudinal and transverse resolution of inversion; and after inversion processing, lithology shielding and an accurate time-depth conversion method are combined, and the spatial distribution characteristics of the lithology of the research area are depicted finely, so that the aim of effectively identifying the lithology is fulfilled, and a reference is provided for fine interpretation of tunnel detection.

Description

Technical Field

[0001] The present invention relates to the field of engineering geophysical exploration technology, and in particular to a lithology fine characterization method based on in-hole logging combined with waveform phase control technology. Background Art

[0002] As the challenges related to exploration and development increase, the safe and efficient production of energy urgently needs more accurate and reliable data support. Therefore, the high-precision prediction of formation lithology has attracted more and more attention. As an important tool for lithology prediction, seismic inversion has developed rapidly in recent decades. In order to accurately characterize the lithology of formations, a variety of seismic inversion methods have been widely used, among which the main ones are wave impedance inversion and geostatistical inversion. Wave impedance inversion includes recursive inversion and constrained sparse pulse inversion. Although this method is less affected by model parameter differences, it has low vertical resolution. Model-based wave impedance inversion introduces well logging data and combines well logging and seismic data to improve vertical accuracy. However, the quality of the initial model directly affects the accuracy of the inversion results. When the sampling is insufficient, the inversion results have large errors. Geostatistical inversion uses random simulation or inversion, which means that the inversion results are more consistent with the geology and have higher resolution. However, the problems of high randomness and low horizontal resolution in the inversion results still exist.

[0003] In order to solve this problem, many scholars, based on the idea of ​​waveform indication inversion, have achieved good results in lithology prediction in different study areas using single waveform indication inversion. However, for complex lithology, single waveform indication inversion often cannot accurately identify lithology characteristics, and it is necessary to introduce characteristic curves that are sensitive to different lithologies on this basis. Aiming at the problem that the prediction accuracy of complex lithology is not high and the lithology cannot be accurately identified, the present invention applies waveform indication inversion and simulation to the fine characterization of lithology, uses the lateral changes of waveforms to reflect lithology characteristics, and combines lithology shielding and accurate time-depth conversion methods to finely characterize the spatial distribution characteristics of the stratum lithology (coal seam, limestone, sandstone and mudstone) in the study area, greatly improving the resolution of the inversion. Summary of the invention

[0004] The present application provides a method for fine lithology characterization based on in-hole logging combined with waveform phase control technology to solve the problem in the prior art that the prediction accuracy of complex lithology is low and the lithology cannot be accurately identified.

[0005] According to the first aspect, an embodiment provides a method for fine lithology characterization based on in-hole logging combined with waveform phase control technology, the method comprising:

[0006] Based on borehole imaging logging data, sensitive characteristic parameters of different lithologies of the target layer in the study area are analyzed to obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include longitudinal wave impedance curves and non-wave impedance curves;

[0007] The P-wave impedance curve is subjected to waveform indication inversion to obtain the P-wave impedance inversion volume, so as to classify the impedance sensitive lithology;

[0008] The non-impedance curve is simulated by waveform indication to obtain the non-impedance inversion volume to divide the non-impedance sensitive lithology;

[0009] Lithology masking is performed based on waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer;

[0010] Based on the waveform indication inversion and waveform indication simulation results, time-depth conversion processing is performed to obtain the lithology and thickness characteristics of the target layer.

[0011] Furthermore, based on the borehole imaging logging data, the sensitive characteristic parameters of different lithologies of the target layer in the study area are analyzed to obtain the sensitive characteristic parameter curves of different lithologies, including:

[0012] A histogram analysis is performed on the longitudinal wave impedance curve and the non-wave impedance curve in the logging data to determine sensitive characteristic parameter curves of different lithologies that are sensitive to lithology changes, wherein the non-wave impedance curve includes a natural gamma curve.

[0013] Furthermore, a histogram analysis is performed on the longitudinal wave impedance curve and the non-wave impedance curve in the logging data, specifically including:

[0014] By extracting different logging curves and based on the core conditions obtained from drilling, the data within the depth range of the target layer are labeled with lithology, and single parameter histogram analysis of different lithologies is achieved through SMI software.

[0015] Furthermore, the P-wave impedance curve is subjected to waveform indication inversion to obtain the P-wave impedance inversion volume to classify the impedance sensitive lithology, including:

[0016] First, a simple grid model is established under the constraints of the interpreted horizons;

[0017] Secondly, analyze the selected drilling data and adjust the appropriate inversion parameters, including smoothing radius, effective sample number, optimal cutoff frequency adjustment, and target volume sampling rate. The smoothing radius is used to control the lateral change of the inversion result, and the optimal cutoff frequency affects the vertical accuracy of the inversion result.

[0018] Finally, after adjusting the parameters, the waveform indication inversion is performed to obtain the inversion results.

[0019] Furthermore, the P-wave impedance curve is subjected to waveform indication inversion to obtain the P-wave impedance inversion volume to classify the impedance sensitive lithology, including:

[0020] Select a pre-established grid model, analyze the selected drilling data, and adjust the inversion parameters, including: smoothing radius, number of effective samples, optimal cutoff frequency adjustment, and target volume sampling rate;

[0021] After adjusting the parameters, perform waveform indication simulation and obtain the inversion results.

[0022] Furthermore, the method further comprises:

[0023] Waveform indication inversion and waveform indication simulation are performed based on SMI software.

[0024] Furthermore, lithology masking is performed based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer, including:

[0025] The waveform indication simulation section is taken as the obstructed body, and the waveform indication inversion section is taken as the obstructing body. According to the range of non-impedance sensitive lithology in the histogram, the data part of non-impedance sensitive lithology is retained, and the longitudinal wave impedance sensitive lithology is removed as much as possible, thereby highlighting the distribution characteristics of non-impedance sensitive lithology.

[0026] Furthermore, time-depth conversion processing is performed based on the waveform indication inversion and waveform indication simulation results to obtain the lithology thickness characteristics of the target layer, specifically including:

[0027] Based on the stratigraphic division results of waveform indication inversion and waveform indication simulation, the top and bottom layers of the target layer are manually marked, and the layer position of the target layer is tracked. The layer information at this time is the seismic data in the time domain. Combined with the drilling information, the time point of the top or bottom plate of the target layer of each well is extracted and recorded as t0, and the time contour map of the top or bottom plate of the target layer is obtained by gridding.

[0028] Taking the roof interface as an example, the average wellhead elevation is used as the reference plane, and the depth of the roof interface of the target layer is obtained by subtracting the elevation of the roof interface of the target layer from the average wellhead elevation, which is recorded as H. The average velocity V of the roof interface of the target layer is calculated by the following conversion formula:

[0029] V=2H / t0

[0030] The calculated average velocity is gridded to obtain the velocity contour map of the target layer top interface. Based on the velocity contour map and time contour map of the target layer top interface, the depth contour map of the target layer top interface is calculated through the following conversion formula:

[0031]

[0032] In this way, the seismic data is converted from the time domain to the depth domain through an accurate time-to-depth conversion method. Similarly, the relevant values ​​of the above-mentioned top plate interface are replaced with the bottom plate interface values. After calculation, the depth contour map of the bottom plate interface of the target layer is obtained. Finally, the depth contour map data of the top and bottom plate interfaces of the target layer are subtracted to obtain the thickness plane map of the target layer, thereby realizing the accurate prediction of the spatial distribution of stratigraphic lithology in the study area.

[0033] According to the second aspect, an embodiment provides a sandstone and mudstone fine characterization system based on in-hole logging combined with waveform phase control technology, the system comprising:

[0034] A sensitive parameter analysis module, which is used to analyze the sensitive characteristic parameters of different lithologies of the target layer in the study area based on the borehole imaging logging data, and obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include a longitudinal wave impedance curve and a non-wave impedance curve;

[0035] The waveform indication inversion module is used to obtain the P-wave impedance inversion volume by waveform indication inversion on the P-wave impedance curve, so as to divide the impedance sensitive lithology;

[0036] The waveform indication simulation module is used to obtain the non-impedance inversion volume by waveform indication simulation of the non-impedance curve to divide the non-impedance sensitive lithology;

[0037] The lithology shielding processing module is used to perform lithology shielding processing based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer;

[0038] The time-depth conversion processing module is used to perform time-depth conversion processing based on waveform indication inversion and waveform indication simulation results to obtain the lithology thickness characteristics of the target layer.

[0039] According to a third aspect, an embodiment provides an electronic device, the device comprising: a processor and a memory;

[0040] The memory is used to store one or more program instructions;

[0041] The processor is used to run one or more program instructions to execute the steps of the sandstone and mudstone fine characterization method based on in-hole logging combined with waveform phase control technology as described in any one of the above items.

[0042] The present application provides a method for fine lithology characterization based on in-hole logging combined with waveform phase control technology. Based on the phase control concept, seismic waveform indication inversion and simulation are applied to fine lithology characterization, and the lateral changes of the waveform are used to reflect the lithology characteristics, thereby improving the vertical and horizontal resolution of the inversion; after the inversion processing, combined with lithology shielding and accurate time-depth conversion methods, the spatial distribution characteristics of the lithology of the formations in the study area are finely characterized, thereby achieving the purpose of effectively identifying the lithology and providing a reference for the refined interpretation of tunnel detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by one embodiment of the present invention;

[0044] Figure 2 A specific implementation flow chart of a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by one embodiment of the present invention;

[0045] Figure 3 A histogram of a borehole in a study area in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0046] Figure 4 A well logging curve histogram analysis in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0047] Figure 5 A grid model diagram in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0048] Figure 6 A waveform indication inversion longitudinal impedance volume profile in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0049] Figure 7 A waveform indication simulated natural gamma body profile in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0050] Figure 8 A lithology obstruction profile diagram in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0051] Fig. 9 A plane diagram of target layer thickness in a lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided by an embodiment of the present invention;

[0052] Fig.10A schematic diagram of the logical structure of a sandstone and mudstone fine characterization system based on in-hole logging combined with waveform phase control technology is provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0053] The present invention is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are for making the present application better understood. However, those skilled in the art can easily recognize that some features can be omitted in different situations, or can be replaced by other elements, materials, methods. In some cases, some operations related to the present application are not shown or described in the specification, this is to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations according to the description in the specification and the general technical knowledge in the art.

[0054] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0055] The first embodiment of the present invention provides a lithology fine characterization method based on in-hole logging combined with waveform phase control technology. Figure 1 and Figure 2 Provide detailed explanation.

[0056] The phase control technology involved in this embodiment refers to the principle of waveform indication inversion. The waveform indication inversion technology first realizes the dynamic clustering analysis of the seismic waveform near the well through singular value decomposition, establishes the mapping relationship between the seismic waveform structure and the logging curve structure, and generates logging curve sample sets of different types of waveform structures (representing different types of seismic phases); then, by analyzing the distribution of sample sets corresponding to different types of waveform structures, Bayesian inversion frameworks of different seismic phase types are established respectively; then, under different Bayesian frameworks, the common parts of the sample sets are respectively selected as the initial model for iterative inversion; finally, in the inversion iteration process, the optimal cutoff frequency of the sample set is used as a constraint condition to obtain a high-resolution inversion result. Thus, by establishing the relationship between the seismic waveform and the logging and lithology, it is realized that the change of the seismic waveform reflects the change of the lithology combination, and the lithology combination is the manifestation of the sedimentary phase or seismic phase. From the perspective of the logging curve, other curves such as wave impedance and natural gamma can reflect the changes in the lithology combination or sedimentary phase.

[0057] The data used in this example are taken from the eastern part of the Loess Plateau in Shanxi Province, located on the northern edge of the Qinshui Coalfield. The lithology of the strata in this area is relatively complex. In order to implement the spatial distribution characteristics of the lithology of the target layer, the K2 limestone, sandstone, 15# coal seam and 15# lower coal seam in the target layer of the study area are finely characterized. The lithology distribution of some boreholes in the target layer in the study area is as follows: Figure 3 shown.

[0058] like Figure 1 As shown, in step S100, sensitive characteristic parameters of different lithologies of the target layer in the study area are analyzed based on borehole imaging logging data to obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include a longitudinal wave impedance curve and a non-wave impedance curve.

[0059] Specifically, by performing histogram analysis on the P-wave impedance curve and natural gamma curve in the logging data, Figure 4 As shown, Figure 4 c. P-wave impedance in 4d can effectively distinguish coal seams and limestone, but cannot identify sandstone and mudstone. Figure 4 The natural gamma curves in a and 4b have obvious dividing lines for sandstone and mudstone, but cannot identify coal seams and limestone. Thus, the sensitive parameters of different lithologies of the target layer (P-wave impedance parameters and natural gamma parameters) are obtained. The P-wave impedance body can be further inverted using waveform indication to distinguish coal seams and limestone, and the natural gamma body can be simulated using waveform indication to distinguish sandstone and mudstone.

[0060] Histogram analysis: By extracting different logging curves and based on the core conditions obtained from drilling, the lithology of the data within the depth range of the target layer is marked. Through the SMI software, a single parameter histogram analysis of different lithologies is achieved, such as Figure 3 shown.

[0061] Furthermore, the present invention can select different logging sensitivity curves for corresponding inversion or simulation work according to the different geological conditions of the location, while ensuring that the seismic waveform is similar to the logging, and then achieve refined prediction of the lithology distribution characteristics of the target layer through lithology shielding, time-depth conversion and other methods.

[0062] like Figure 1 As shown, in step S200, a P-wave impedance inversion volume is obtained by waveform indication inversion of the P-wave impedance curve to divide impedance sensitive lithology.

[0063] Specifically, the waveform indication inversion is used to obtain the P-wave impedance inversion volume, and then the impedance sensitive lithology (coal seam, limestone, etc.) is divided, as follows:

[0064] (1) First, a simple grid model is established under the constraints of the interpreted horizon, such as Figure 5As shown, it specifically includes: firstly, according to the data results of the study area, the target layer stratigraphic data is imported into the SMI software. In the software, the seismic data volume is first selected, the smoothing radius is set, and the corresponding stratigraphic layers are added according to the sedimentary characteristics, so as to establish the basic grid model, which can be understood as a framework;

[0065] (2) Secondly, analyze the selected drilling data and adjust the appropriate inversion parameters. The inversion parameters are selected as follows: smoothing radius is 1, effective sample number is 5, optimal cutoff frequency is adjusted to 300 Hz, and the target volume sampling rate is controlled at 0.25 ms. The smoothing radius can be used to control the lateral changes of the inversion results, and the optimal cutoff frequency affects the vertical accuracy of the inversion results.

[0066] (3) After adjusting the parameters, perform waveform indication inversion. The inversion results are as follows: Figure 6 As shown in the figure, green represents coal seams, which show low values; blue-purple represents limestone, which shows high values. As can be seen from the figure, the inversion results are consistent with the logging curves, with clear resolution. The 15# coal, 15# lower coal, and limestone can be finely depicted from the inversion results.

[0067] like Figure 1 As shown, in step S300, a waveform indication simulation is used to obtain a non-impedance inversion volume for the non-impedance curve to divide the non-impedance sensitive lithology.

[0068] On the basis of the waveform inversion results, the sensitive parameter curves of the undifferentiated lithologies are inverted by waveform simulation technology, the corresponding inversion parameters are adjusted, and sensitive parameter simulation is performed to obtain other inversion bodies, and further classify different sensitive lithologies (sandstone, mudstone).

[0069] The waveform indication simulation is used to obtain the natural gamma inversion volume, as follows:

[0070] (1) Select a pre-defined grid model, analyze the selected drilling data, and adjust the inversion parameters. The inversion parameters are selected as follows: the smoothing radius is 1, the number of effective samples is 5, the optimal cutoff frequency is adjusted to 200 Hz, and the target volume sampling rate is controlled at 0.25 ms.

[0071] (2) After adjusting the parameters, the waveform indication simulation is performed, and the inversion results are as follows Figure 7 As shown, sandstone exhibits low natural gamma values, represented by light green, and mudstone exhibits high gamma values, represented by blue and purple. It can be seen from the figure that sandstone and mudstone are effectively distinguished based on the waveform indication simulation method.

[0072] The waveform indication inversion and waveform indication simulation in this embodiment are both processed based on the SMI software.

[0073] like Figure 1As shown, in step S400, lithology shielding processing is performed based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer.

[0074] Specifically, in order to further classify the lithology of the target layer, the two inversion sections are subjected to lithology shielding processing to more clearly distinguish sandstone and mudstone. Figure 8 It can be seen that the waveform indication simulation section is taken as the obstructed body, the waveform indication inversion section is taken as the obstructing body, and according to the range of sandstone and mudstone in the histogram, the data size is retained in the range of 5000-9000m / s*g / cm 3 The sandstone and mudstone parts are removed, and the coal seams and limestone are removed, thereby highlighting the distribution characteristics of sandstone and mudstone. Figure 8 In the figure, the continuous red segment is mudstone, and the continuous bluish-white segment on the mudstone is sandstone. The specific shielding process is realized by SMI software.

[0075] like Figure 1 As shown, in step S500, time-depth conversion processing is performed based on the waveform indication inversion and waveform indication simulation results to obtain the lithology thickness characteristics of the target layer.

[0076] Specifically, the process of time-depth conversion is as follows:

[0077] Based on the stratigraphic division results of waveform indication inversion and waveform indication simulation, the top and bottom layers of the target layer are manually marked, and the layer position of the target layer is tracked. The layer information at this time is the seismic data in the time domain. Combined with the drilling information, the time point of the top or bottom plate of the target layer of each well is extracted and recorded as t0, and the time contour map of the top or bottom plate of the target layer is obtained by gridding.

[0078] Taking the roof interface as an example, the average wellhead elevation is used as the reference plane, and the depth of the roof interface of the target layer is obtained by subtracting the elevation of the roof interface of the target layer from the average wellhead elevation, which is recorded as H. The average velocity V of the roof interface of the target layer is calculated by the following conversion formula:

[0079] V=2H / t0 (1)

[0080] The calculated average velocity is gridded to obtain the velocity contour map of the target layer top interface. Based on the velocity contour map and time contour map of the target layer top interface, the depth contour map of the target layer top interface is calculated through the following conversion formula:

[0081]

[0082] In this way, the seismic data is converted from the time domain to the depth domain through an accurate time-to-depth conversion method. Similarly, the relevant values ​​of the above-mentioned top plate interface are replaced with the bottom plate interface values. After calculation, the depth contour map of the bottom plate interface of the target layer is obtained. Finally, the depth contour map data of the top and bottom plate interfaces of the target layer are subtracted to obtain the thickness plane map of the target layer, thereby realizing the accurate prediction of the spatial distribution of stratigraphic lithology in the study area.

[0083] The specific operation process is as follows: through inversion and simulation of profile results, the target layers of coal seams, limestone and sandstone in the study area are divided, the seismic data body is imported into the geoframe software, and the top and bottom layers of the target layer are manually marked. The layer information at this time is the seismic information in the time domain. The existing drilling point location information and depth information are imported into the software, and the time information t0 of the drilling point is extracted through the software. Given certain grid parameters, the time plane map of the top or bottom plate of the target layer is obtained, that is, the time contour map. The average value of the drilling wellhead elevation is used as the reference plane, and the elevation value of the top or bottom plate interface of the target layer is subtracted from the wellhead elevation to obtain the depth data of the top or bottom plate interface of the target layer, which is recorded as H. Through the conversion of formula 1, the velocity value of the drilling point is obtained. By giving certain grid parameters, the velocity plane map of the top or bottom plate of the target layer, that is, the velocity contour map, is obtained. By combining the time and velocity plane data of the top or bottom plate of the target layer with formula 2, the depth plane map of the top or bottom plate of the target layer, i.e., the depth contour map, is obtained. The depth data of the top and bottom plates are subtracted to finally obtain the thickness data of the target layer and the thickness plane map, such as Fig. 9 shown.

[0084] Fig. 9 The main lithology thickness maps of the study area are the 15# coal thickness plane map ( Fig. 9 a) 15# coal thickness plan ( Fig. 9 b) Thickness plan of K2 limestone ( Fig. 9 c) Sandstone thickness plan ( Fig. 9 d).

[0085] Comparison and verification of the accuracy of the method of the present invention:

[0086] In order to further verify the accuracy of this method, four verification wells were taken, and the sandstone thickness was taken as an example. The actual drilling thickness value was compared with the thickness value predicted by the inversion result of this inversion and the traditional prediction based on wave impedance inversion. The comparison results are shown in Table 1. The waveform indication simulation results are more consistent with the actual logging results, and the error is controlled within 0.1m. The error based on the wave impedance inversion result is relatively high. It can be seen that the waveform indication inversion characterization method of the present invention has a higher inversion result accuracy than the wave impedance inversion method, and can be better applied in the prediction of complex lithology.

[0087] Table 1 Comparison between inversion results and actual thickness

[0088]

[0089]

[0090] The present invention uses waveform indication inversion and simulation methods to establish the relationship between the seismic waveform and the longitudinal wave impedance curve and the natural gamma curve in a phased inversion manner, thereby improving the vertical and horizontal resolution of the inversion results; based on the inversion results, the lithology shielding technology and the accurate time-depth conversion are combined, and the lithology shielding technology is used to highlight the sandstone and mudstone lithology characteristics of the target layer. Then, according to the accurate time-depth conversion method, the seismic data is converted from the time domain to the depth domain to obtain the thickness characteristics of the target layer, which greatly improves the accuracy of the spatial distribution prediction of the target layer and provides a reference for the identification of complex lithology.

[0091] Corresponding to the above-disclosed method for fine characterization of formation lithology based on in-hole logging combined with waveform phase control technology, the embodiment of the present invention further discloses a fine characterization system for sandstone and mudstone based on in-hole logging combined with waveform phase control technology, such as Fig.10 As shown, it specifically includes:

[0092] A sensitive parameter analysis module, which is used to analyze the sensitive characteristic parameters of different lithologies of the target layer in the study area based on the borehole imaging logging data, and obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include a longitudinal wave impedance curve and a non-wave impedance curve;

[0093] The waveform indication inversion module is used to obtain the P-wave impedance inversion volume by waveform indication inversion on the P-wave impedance curve, so as to divide the impedance sensitive lithology;

[0094] The waveform indication simulation module is used to obtain the non-impedance inversion volume by waveform indication simulation of the non-impedance curve to divide the non-impedance sensitive lithology;

[0095] The lithology shielding processing module is used to perform lithology shielding processing based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer;

[0096] The time-depth conversion processing module is used to perform time-depth conversion processing based on waveform indication inversion and waveform indication simulation results to obtain the lithology thickness characteristics of the target layer.

[0097] It should be noted that for the detailed description of the sandstone and mudstone fine characterization system based on in-hole logging combined with waveform phase control technology provided in an embodiment of the present invention, reference can be made to the relevant description of the lithology fine characterization method based on in-hole logging combined with waveform phase control technology provided in an embodiment of the present application, which will not be repeated here.

[0098] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0099] The above specific examples are used to illustrate the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the art, according to the concept of the present invention, some simple deductions, modifications or substitutions can be made.

Claims

1. A lithology fine characterization method based on in-hole logging combined with waveform phase control technology, characterized in that: The method comprises: Based on borehole imaging logging data, sensitive characteristic parameters of different lithologies of the target layer in the study area are analyzed to obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include longitudinal wave impedance curves and non-wave impedance curves; The P-wave impedance curve is subjected to waveform indication inversion to obtain the P-wave impedance inversion volume, so as to classify the impedance sensitive lithology; The non-impedance curve is simulated by waveform indication to obtain the non-impedance inversion volume to divide the non-impedance sensitive lithology; Lithology masking is performed based on waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer; Based on the waveform indication inversion and waveform indication simulation results, time-depth conversion processing is performed to obtain the lithology and thickness characteristics of the target layer.

2. A lithology fine characterization method based on in-hole logging combined with waveform phase control technology as claimed in claim 1, characterized in that: Based on borehole imaging logging data, the sensitive characteristic parameters of different lithologies of the target layer in the study area are analyzed to obtain the sensitive characteristic parameter curves of different lithologies, including: A histogram analysis is performed on the longitudinal wave impedance curve and the non-wave impedance curve in the borehole imaging logging data to determine sensitive characteristic parameter curves of different lithologies that are sensitive to lithology changes, wherein the non-wave impedance curve includes a natural gamma curve.

3. A lithology fine characterization method based on in-hole logging combined with waveform phase control technology as claimed in claim 2, characterized in that: The histogram analysis of the longitudinal wave impedance curve and non-wave impedance curve in the logging data includes: By extracting different logging curves and based on the core conditions obtained from drilling, the data within the depth range of the target layer are labeled with lithology, and single parameter histogram analysis of different lithologies is achieved through SMI software.

4. The lithology fine characterization method based on in-hole logging combined with waveform phase control technology according to claim 1, characterized in that: The P-wave impedance curve is inverted by waveform indication to obtain the P-wave impedance inversion volume to divide the impedance sensitive lithology, including: First, a simple grid model is established under the constraints of the interpreted horizons; Secondly, analyze the selected drilling data and adjust the appropriate inversion parameters, including smoothing radius, effective sample number, optimal cutoff frequency adjustment, and target volume sampling rate. The smoothing radius is used to control the lateral change of the inversion result, and the optimal cutoff frequency affects the vertical accuracy of the inversion result. Finally, after adjusting the parameters, the waveform indication inversion is performed to obtain the inversion results.

5. A lithology fine characterization method based on in-hole logging combined with waveform phase control technology as claimed in claim 4, characterized in that: The P-wave impedance curve is inverted by waveform indication to obtain the P-wave impedance inversion volume to divide the impedance sensitive lithology, including: Select a pre-established grid model, analyze the selected drilling data, and adjust the inversion parameters, including: smoothing radius, number of effective samples, optimal cutoff frequency adjustment, and target volume sampling rate; After adjusting the parameters, perform waveform indication simulation and obtain the inversion results.

6. A lithology fine characterization method based on in-hole logging combined with waveform phase control technology as claimed in claim 5, characterized in that: The method further comprises: Waveform indication inversion and waveform indication simulation are performed based on SMI software.

7. The method for fine lithology characterization based on in-hole logging combined with waveform phase control technology according to claim 1, characterized in that: Lithology shielding processing is performed based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer, including: The waveform indication simulation section is taken as the obstructed body, and the waveform indication inversion section is taken as the obstructing body. According to the range of non-impedance sensitive lithology in the histogram, the data part of non-impedance sensitive lithology is retained, and the longitudinal wave impedance sensitive lithology is removed as much as possible, thereby highlighting the distribution characteristics of non-impedance sensitive lithology.

8. The method for fine lithology characterization based on in-hole logging combined with waveform phase control technology according to claim 1, characterized in that: Based on the waveform indication inversion and waveform indication simulation results, time-depth conversion processing is performed to obtain the lithology thickness characteristics of the target layer, including: Based on the stratigraphic division results of waveform indication inversion and waveform indication simulation, the top and bottom layers of the target layer are manually marked, and the layer position of the target layer is tracked. The layer information at this time is the seismic data in the time domain. Combined with the drilling information, the time point of the top or bottom plate of the target layer of each well is extracted and recorded as t0, and the time contour map of the top or bottom plate of the target layer is obtained by gridding. Taking the roof interface as an example, the average wellhead elevation is used as the reference plane, and the depth of the roof interface of the target layer is obtained by subtracting the elevation of the roof interface of the target layer from the average wellhead elevation, which is recorded as H. The average velocity V of the roof interface of the target layer is calculated by the following conversion formula: V=2H / t0 The calculated average velocity is gridded to obtain the velocity contour map of the target layer top interface. Based on the velocity contour map and time contour map of the target layer top interface, the depth contour map of the target layer top interface is calculated through the following conversion formula: In this way, the seismic data is converted from the time domain to the depth domain through an accurate time-to-depth conversion method. Similarly, the relevant values ​​of the above-mentioned top plate interface are replaced with the bottom plate interface values. After calculation, the depth contour map of the bottom plate interface of the target layer is obtained. Finally, the depth contour map data of the top and bottom plate interfaces of the target layer are subtracted to obtain the thickness plane map of the target layer, thereby realizing the accurate prediction of the spatial distribution of stratigraphic lithology in the study area.

9. A sandstone and mudstone fine characterization system based on in-hole logging combined with waveform phase control technology, characterized in that: The system comprises: A sensitive parameter analysis module, which is used to analyze the sensitive characteristic parameters of different lithologies of the target layer in the study area based on the borehole imaging logging data, and obtain sensitive characteristic parameter curves of different lithologies, wherein the sensitive characteristic parameter curves include a longitudinal wave impedance curve and a non-wave impedance curve; The waveform indication inversion module is used to obtain the P-wave impedance inversion volume by waveform indication inversion on the P-wave impedance curve, so as to divide the impedance sensitive lithology; The waveform indication simulation module is used to obtain the non-impedance inversion volume by waveform indication simulation of the non-impedance curve to divide the non-impedance sensitive lithology; The lithology shielding processing module is used to perform lithology shielding processing based on the waveform indication inversion and waveform indication simulation results to highlight the lithology distribution characteristics of the target layer; The time-depth conversion processing module is used to perform time-depth conversion processing based on waveform indication inversion and waveform indication simulation results to obtain the lithology thickness characteristics of the target layer.

10. An electronic device, characterized in that: The device comprises: a processor and a memory; The memory is used to store one or more program instructions; The processor is used to run one or more program instructions to execute the steps of a sandstone and mudstone fine characterization method based on in-hole logging combined with waveform phase control technology as described in any one of claims 1 to 8.

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