Method and device for mapping volcanic facies
By combining drilling and logging data to establish volcanic rock lithology charts, and combining seismic data for well-seismic calibration and multi-attribute fusion processing, the problem of unclear volcanic rock facies zones was solved, reservoir prediction accuracy was improved, and drilling risks were reduced.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA NAT PETROLEUM CORP
- Filing Date
- 2021-12-09
- Publication Date
- 2026-06-05
AI Technical Summary
Existing technologies have low accuracy in predicting high-quality volcanic reservoirs and inaccurate characterization of volcanic structures and lithofacies features, which increases drilling risks.
By combining drilling and logging data to establish a volcanic rock lithology identification chart, combining seismic data to determine the macroscopic characteristics of volcanic structures, performing fine well-seismic calibration, and using multiple seismic attributes for fusion processing, a clear volcanic rock facies distribution data volume is obtained.
It improves the prediction accuracy of high-quality volcanic rock reservoirs, reduces drilling risks, and provides reliable data for the efficient exploration and development of oil and gas reservoirs.
Smart Images
Figure CN116256798B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of seismic exploration technology for oil and gas, and particularly to a method and apparatus for the distribution of volcanic rock facies zones. Background Technology
[0002] Currently, my country has proven reserves of hundreds of millions of tons of oil and trillions of cubic meters of natural gas in volcanic rocks dating from the Mesozoic and Cenozoic eras in basins such as the Songliao Basin in the east and the Late Paleozoic era in basins such as the Junggar Basin in the west. This indicates that volcanic oil and gas reservoirs have become an important area for my country's energy transition. Extensive oil and gas exploration experience has shown that volcanic structures and lithofacies characteristics are important bases for predicting volcanic oil and gas reservoirs.
[0003] In related technologies, the facies method is commonly used to extract and characterize volcanic structures and lithofacies features, which involves using seismic reflection characteristics and human experience to classify lithofacies. However, this method is highly subjective, leading to inaccurate characterization of volcanic structures and lithofacies features, low accuracy in predicting high-quality volcanic reservoirs, and increased drilling risks. Summary of the Invention
[0004] In view of this, the present invention provides a method and apparatus for the distribution of volcanic rock facies zones, which can overcome the problem of inaccurate characterization of volcanic structures and rock facies features in related technologies and improve the prediction accuracy of high-quality volcanic rock reservoirs.
[0005] Specifically, the following technical solutions are included:
[0006] In a first aspect, this application provides a method for the distribution of volcanic rock facies zones, the method comprising:
[0007] Based on the drilling and logging data of the area to be tested, a volcanic rock lithology identification chart was established;
[0008] Based on the seismic data of the area to be measured, the macroscopic characteristics of the volcanic structure are determined, and the first seismic attribute data volume is obtained;
[0009] Based on the volcanic rock lithology identification chart and the macroscopic characteristics of the volcanic structure, multiple volcanic rock facies zones were identified;
[0010] Based on the drilling and logging data of the area to be tested, the first seismic attribute data volume is finely calibrated to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone.
[0011] Based on multiple target earthquake attributes, the first earthquake attribute data volume is fused to obtain the second earthquake attribute data volume.
[0012] In some embodiments, establishing a volcanic rock lithology identification map based on drilling and logging data of the area to be tested includes:
[0013] Based on the rock thin sections and core samples from the drilling data of the area to be tested, as well as the logging data of the area to be tested, multiple lithological sample points are determined.
[0014] Based on the well logging data of the area to be tested, multiple well logging curves were obtained;
[0015] Based on the multiple lithological sample points, matrix intersection is performed on the multiple logging curves to determine the first target parameter curve and the second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve;
[0016] Based on the first target parameter curve and the second target parameter curve, the volcanic rock lithology identification chart is obtained.
[0017] In some embodiments, obtaining the volcanic rock lithology identification chart based on the first target parameter curve and the second target parameter curve includes:
[0018] The first target parameter curve and the second target parameter curve are subjected to intersection processing to obtain the volcanic rock lithology identification map.
[0019] In some embodiments, determining the macroscopic features of the volcanic structure based on seismic data of the area to be measured includes:
[0020] The macroscopic characteristics of the volcanic structure were determined by flattening the seismic data, analyzing the layer-by-layer amplitude properties, and examining the coherence properties.
[0021] The macroscopic features of the volcanic structure include the location of the crater and the stratigraphic occurrence of the volcanic structure.
[0022] The determination of multiple volcanic facies zones based on the volcanic rock lithology identification chart and the macroscopic characteristics of the volcanic structure includes:
[0023] Based on the macroscopic characteristics of the volcanic structure, the volcanic rock lithology on the volcanic rock lithology identification chart is divided to obtain multiple volcanic rock facies zones;
[0024] Each volcanic facies zone includes at least one volcanic rock lithology.
[0025] In some embodiments, before fusing the first seismic attribute data volume based on multiple target seismic attributes, the method further includes:
[0026] Obtain the earthquake attributes of the multiple targets;
[0027] The target earthquake attributes include amplitude, continuity, and frequency.
[0028] In some embodiments, the fusion processing of the first seismic attribute data volume based on multiple target seismic attributes includes:
[0029] Low-pass filtering, band-pass filtering, and high-pass filtering are applied to the multiple target seismic attributes corresponding to each seismic data in the first seismic attribute data volume to obtain the fused attribute corresponding to each seismic data.
[0030] The fusion attribute corresponding to each seismic data point is calculated using the following formula:
[0031]
[0032] In the formula: f k (x) represents the target seismic attribute; m represents the number of target seismic attributes; w k The weights of each target seismic attribute, and x is the optimal solution; x is a linear weighted average.
[0033] On one hand, this application provides a device for the distribution of volcanic rock facies zones, the device comprising:
[0034] A module is established to create a volcanic rock lithology identification chart based on drilling and logging data of the area to be tested;
[0035] The determination module is used to determine the macroscopic characteristics of the volcanic structure based on the seismic data of the area to be measured, and to obtain the first seismic attribute data volume;
[0036] The determining module is also used to determine multiple volcanic rock facies zones based on the volcanic rock lithology identification chart and the macroscopic characteristics of the volcanic structure;
[0037] The determining module is also used to perform fine well-seismic calibration on the first seismic attribute data body based on the drilling data and logging data of the area to be measured, and to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone;
[0038] The fusion module is used to fuse the first seismic attribute data volume based on multiple target seismic attributes to obtain the second seismic attribute data volume.
[0039] The establishment module includes:
[0040] The first determining unit is used to determine multiple lithological sample points based on the rock thin sections and core samples in the drilling data of the area to be tested and the logging data of the area to be tested.
[0041] The first obtaining unit is used to obtain multiple logging curves based on the logging data of the area to be tested;
[0042] The second determining unit is used to perform matrix intersection on the multiple logging curves based on the multiple lithological sample points to determine a first target parameter curve and a second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve;
[0043] The second obtaining unit is used to obtain the volcanic rock lithology identification chart based on the first target parameter curve and the second target parameter curve.
[0044] The second obtaining unit includes:
[0045] The resulting sub-unit is used to perform intersection processing on the first target parameter curve and the second target parameter curve to obtain the volcanic rock lithology identification map.
[0046] The volcanic facies zone distribution method provided in this invention obtains a volcanic lithology identification map of the area to be tested using drilling and logging data. Combined with seismic data of the area, the macroscopic characteristics of the volcanic structure in the area are determined, thereby identifying multiple volcanic facies zones in the area. Furthermore, by combining drilling and logging data of the area, fine well-seismic calibration is performed on the first seismic attribute data volume obtained from the seismic data to determine the one-to-one correspondence between the seismic data and the volcanic facies zones, so that the seismic data can reflect the corresponding volcanic facies zones. Based on this, since a single seismic attribute is insufficient to adequately represent the distribution of volcanic facies zones, a second seismic attribute data body is obtained by fusing multiple target seismic attributes within the first seismic attribute data body. This second seismic attribute data body clearly shows the boundaries of each volcanic facies zone, allowing technicians to intuitively visualize the distribution of volcanic facies zones. The clear boundaries overcome the problem of inaccurate characterization of volcanic structures and lithofacies features in related technologies, improving the prediction accuracy of high-quality volcanic reservoirs, reducing drilling risks, and providing reliable data for the efficient exploration and development of oil and gas reservoirs. Attached Figure Description
[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 A flowchart illustrating a method for the distribution of volcanic rock facies zones, provided as an embodiment of this application;
[0049] Figure 2 A flowchart illustrating another method for the distribution of volcanic rock facies zones provided in this application embodiment;
[0050] Figure 3 A block diagram of a device for spreading volcanic rock facies zones provided in an embodiment of this application;
[0051] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;
[0052] Figure 5 A volcanic rock lithology identification chart provided for embodiments of this application;
[0053] Figure 6 A cross-sectional view of the distribution of volcanic rock facies zones provided in an embodiment of this application. Detailed Implementation
[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0055] To make the technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
[0056] Currently, my country has proven reserves of hundreds of millions of tons of oil and trillions of cubic meters of natural gas in volcanic rocks dating from the Mesozoic and Cenozoic eras in basins such as the Songliao Basin in the east and the Late Paleozoic era in basins such as the Junggar Basin in the west. This indicates that volcanic oil and gas reservoirs have become an important area for my country's energy transition. Extensive oil and gas exploration experience has shown that volcanic structures and lithofacies characteristics are important bases for predicting volcanic oil and gas reservoirs.
[0057] Because volcanic rocks are often developed deep within basins, the high-frequency information in the seismic data obtained by researchers is severely attenuated due to absorption and attenuation in the shallow layers. In addition, the low-frequency information in the seismic data is severely lacking, resulting in a generally low signal-to-noise ratio, which brings great difficulties and challenges to seismic exploration. Furthermore, due to the influence of volcanic eruptions and volcanic tectonic deformation, the strata and stratigraphy within the Carboniferous system are very complex, resulting in mostly chaotic reflections in the seismic data. Consequently, the macroscopic features of the volcanic structure are unclear, and the boundaries between different volcanic rock facies zones and lithological assemblages are indistinct, making it impossible to effectively and accurately characterize the volcanic structure and volcanic rock facies zones.
[0058] Currently, techniques for characterizing volcanic structures and lithofacies primarily rely on well logging or core analysis and seismic facies analysis. These techniques suffer from several problems: inaccurate well logging lithology identification; lithology identification mainly relies on well logging curves, but this method uses a limited range of curves and has poor accuracy in identifying transitional lithologies; and the subjective nature of volcanic lithofacies analysis. Significant differences exist in lithofacies classifications made by different individuals at different times using different data, leading to strong subjectivity. For example, intrusive rocks often exhibit parallel, transplate-like patterns, while eruptive rocks often display "mushroom-like" or "mound-like" patterns, with internal chaotic reflections. These seismic facies characteristics predict volcanic rock facies, but it is impossible to judge the correctness and accuracy of subjective seismic facies classification; the boundaries of facies are not clearly delineated. Because the use of single seismic attributes (horizontal slice, coherence attribute, amplitude attribute, absorption attenuation, etc.) for volcanic structure characterization and facies prediction can only reflect the underground geological conditions from one aspect. For example, using amplitude attribute can only reflect the intensity of seismic reflection of underground geological bodies. When the seismic amplitude reflection intensity of different geological bodies is the same, it is difficult to distinguish between the two. Moreover, the attribute characteristics are fragmented and the boundaries of different facies are unclear, resulting in poor overall regularity and strong ambiguity in the characterization effect.
[0059] This application provides a method for the distribution of volcanic rock facies zones, the flowchart of which can be found in [link to flowchart]. Figure 1 The method includes the following steps:
[0060] Step 101: Based on the drilling and logging data of the area to be tested, establish a volcanic rock lithology identification chart.
[0061] Step 102: Based on the seismic data of the area to be measured, determine the macroscopic characteristics of the volcanic structure and obtain the first seismic attribute data volume.
[0062] Step 103: Based on the volcanic rock lithology identification chart and the macroscopic characteristics of volcanic structures, identify multiple volcanic rock facies zones.
[0063] Step 104: Based on the drilling and logging data of the area to be measured, perform fine well-seismic calibration on the first seismic attribute data volume to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone.
[0064] Step 105: Based on multiple target earthquake attributes, the first earthquake attribute data volume is fused to obtain the second earthquake attribute data volume.
[0065] In some embodiments, establishing a volcanic rock lithology identification chart based on drilling and logging data of the area to be tested includes:
[0066] Based on the rock thin sections and core samples from the drilling data of the area to be tested, as well as the logging data of the area to be tested, multiple lithological sample points were determined.
[0067] Based on the logging data of the area to be tested, multiple logging curves were obtained;
[0068] Based on multiple lithological sample points, matrix intersection of multiple logging curves is performed to determine the first target parameter curve and the second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve;
[0069] Based on the first target parameter curve and the second target parameter curve, a volcanic rock lithology identification chart is obtained.
[0070] In some embodiments, obtaining a volcanic rock lithology identification chart based on a first target parameter curve and a second target parameter curve includes:
[0071] The intersection of the first target parameter curve and the second target parameter curve is used to obtain the volcanic rock lithology identification map.
[0072] In some embodiments, determining the macroscopic characteristics of a volcanic structure based on seismic data of the area to be measured includes:
[0073] Macroscopic features of volcanic structures were determined by flattening body slices, layer-by-layer amplitude properties, and coherence properties of seismic data.
[0074] Among them, the macroscopic characteristics of volcanic structures include the location of the crater and the stratigraphic occurrence of the volcanic structure.
[0075] In some embodiments, determining multiple volcanic facies zones based on volcanic rock lithology identification charts and macroscopic features of volcanic structures includes:
[0076] Based on the macroscopic characteristics of volcanic structures, the volcanic rock lithology on the volcanic rock lithology identification chart is divided into multiple volcanic rock facies zones;
[0077] Each volcanic facies zone includes at least one volcanic rock lithology.
[0078] In some embodiments, before fusing the first seismic attribute data volume based on multiple target seismic attributes, the method further includes:
[0079] Obtain earthquake attributes from multiple targets;
[0080] The target earthquake attributes include amplitude, continuity, and frequency.
[0081] In some embodiments, fusing the first seismic attribute data volume based on multiple target seismic attributes includes:
[0082] Low-pass filtering, band-pass filtering, and high-pass filtering are applied to the multiple target seismic attributes corresponding to each seismic data in the first seismic attribute data volume to obtain the fused attribute corresponding to each seismic data.
[0083] The fusion attribute corresponding to each seismic data point is calculated using the following formula:
[0084]
[0085] In the formula: f k (x) represents the target seismic attribute; m represents the number of target seismic attributes; w k The weights of each target seismic attribute, and x is the optimal solution; x is a linear weighted average.
[0086] Therefore, the volcanic facies zone distribution method provided in this application obtains a volcanic lithology identification map for the area to be tested using drilling and logging data. Combined with seismic data of the area, the macroscopic characteristics of the volcanic structure in the area are determined, thereby identifying multiple volcanic facies zones in the area. Furthermore, by combining drilling and logging data of the area, fine well-seismic calibration is performed on the first seismic attribute data volume obtained from the seismic data to determine the one-to-one correspondence between the seismic data and the volcanic facies zones, so that the seismic data can reflect the corresponding volcanic facies zones. Based on this, since a single seismic attribute is insufficient to adequately represent the distribution of volcanic facies zones, a second seismic attribute data body is obtained by fusing multiple target seismic attributes within the first seismic attribute data body. This second seismic attribute data body clearly shows the boundaries of each volcanic facies zone, allowing technicians to intuitively visualize the distribution of volcanic facies zones. The clear boundaries overcome the problem of inaccurate characterization of volcanic structures and lithofacies features in related technologies, improving the prediction accuracy of high-quality volcanic reservoirs, reducing drilling risks, and providing reliable data for the efficient exploration and development of oil and gas reservoirs.
[0087] This application also provides a method for the distribution of volcanic rock facies zones, the flowchart of which is as follows: Figure 2 As shown, the method includes:
[0088] Step 201: Based on the drilling and logging data of the area to be tested, establish a volcanic rock lithology identification chart.
[0089] This step can be achieved as follows: Based on the rock thin sections and core samples in the drilling data of the area to be tested, as well as the logging data of the area to be tested, determine multiple lithological sample points;
[0090] Based on the logging data of the area to be tested, multiple logging curves were obtained;
[0091] Based on multiple lithological sample points, matrix intersection of multiple logging curves is performed to determine the first target parameter curve and the second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve;
[0092] The intersection of the first target parameter curve and the second target parameter curve is used to obtain the volcanic rock lithology identification map.
[0093] Among them, multiple logging curves include: caliper curve, spontaneous potential curve, spontaneous gamma curve, density curve, sonic transit time curve, neutron porosity curve, deep resistivity curve, transition zone resistivity curve, and flushing zone resistivity curve.
[0094] In some embodiments, see Figure 5 The first target parameter curve can be a gamma curve, and the second target parameter curve can be a density curve. By performing cross-hatching with the gamma curve as the horizontal axis and the density curve as the vertical axis, a volcanic rock lithology identification map can be obtained.
[0095] Step 202: Based on the seismic data of the area to be measured, determine the macroscopic characteristics of the volcanic structure and obtain the first seismic attribute data volume.
[0096] Based on seismic data from the area to be measured, the macroscopic characteristics of the volcanic structure were determined, including:
[0097] Macroscopic features of volcanic structures were determined by flattening body slices, layer-by-layer amplitude properties, and coherence properties of seismic data.
[0098] Among them, the macroscopic characteristics of volcanic structures include the location of the crater and the stratigraphic occurrence of the volcanic structure.
[0099] Step 203: Based on the volcanic rock lithology identification chart and the macroscopic characteristics of volcanic structures, identify multiple volcanic rock facies zones.
[0100] This step can be achieved as follows: Based on the macroscopic characteristics of volcanic structures, the volcanic rock lithology on the volcanic rock lithology identification chart is divided to obtain multiple volcanic rock facies zones; wherein each volcanic rock facies zone includes at least one volcanic rock lithology.
[0101] In the embodiments of this application, multiple volcanic rock facies zones may include: eruptive facies zone, overflow facies zone, volcanic sedimentary facies zone, and sedimentary facies zone.
[0102] Step 204: Based on the drilling and logging data of the area to be measured, perform fine well-seismic calibration on the first seismic attribute data volume to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone.
[0103] Understandably, seismic data of volcanic rocks are mainly studied from aspects such as amplitude strength, continuity of phase axes, frequency characteristics, and external morphology. Seismic data of eruptive facies zones generally show medium to weak reflection amplitudes and low-frequency characteristics on seismic profiles, with disordered phase axis reflections and a mound-like shape. Seismic data of effusive facies zones generally show medium to weak reflection amplitudes and mid-to-low-frequency characteristics on seismic profiles, with relatively continuous phase axes and an external morphology of sheet-like, wedge-like, or layered shapes. Seismic data of volcanic sedimentary facies zones generally show strong reflection amplitudes and mid-frequency characteristics on seismic profiles, with good continuity of phase axes and a layered shape. Seismic data of sedimentary facies zones generally show medium to weak reflection amplitudes and mid-to-high-frequency characteristics on seismic profiles, with continuous phase axis reflections and a layered shape.
[0104] Step 205: Obtain earthquake attributes for multiple targets.
[0105] The target earthquake attributes include amplitude, continuity, and frequency.
[0106] In some embodiments, the number of target seismic attributes can be 2, 3, 4, 5, or 10, etc.
[0107] Step 206: Based on multiple target earthquake attributes, the first earthquake attribute data volume is fused to obtain the second earthquake attribute data volume.
[0108] It is understandable that the relationship between the first data volume and the second data volume is that the second seismic attribute data volume is obtained by fusing the first seismic attribute data volume.
[0109] The fusion processing of the first seismic attribute data volume based on multiple target seismic attributes includes:
[0110] Low-pass filtering, band-pass filtering, and high-pass filtering are applied to the multiple target seismic attributes corresponding to each seismic data in the first seismic attribute data volume to obtain the fused attribute corresponding to each seismic data.
[0111] The fusion attribute corresponding to each seismic data point is calculated using the following formula:
[0112]
[0113] In the formula: f k (x) represents the target seismic attribute; m represents the number of target seismic attributes; w k For each purpose
[0114] The weights of the earthquake attributes are marked, and x is the optimal solution; x is a linear weighted average.
[0115] Taking amplitude, frequency, and continuity attributes as target seismic attributes as an example, the first seismic attribute data volume is fused. The amplitude, frequency, and continuity attributes are respectively low-pass filtered, band-pass filtered, and high-pass filtered before being input into the above formula for fusion. Where f k1 It can be an amplitude attribute, f k2 It can be a frequency attribute, f k3 It can be a continuous attribute, where m is 3.
[0116] Figure 6 This is a cross-sectional view of the distribution of volcanic rock facies zones provided in an embodiment of this application. From... Figure 6 The boundaries of each volcanic rock facies zone are clearly visible, which can provide technicians with a direct view of the distribution of the volcanic rock facies zones.
[0117] Therefore, the volcanic facies zone distribution method provided in this embodiment of the invention obtains a volcanic lithology identification map for the area to be tested using drilling and logging data. Combined with seismic data of the area, the macroscopic characteristics of the volcanic structure in the area are determined, thereby identifying multiple volcanic facies zones in the area. Furthermore, by combining drilling and logging data of the area, fine well-seismic calibration is performed on the first seismic attribute data volume obtained from the seismic data to determine the one-to-one correspondence between the seismic data and the volcanic facies zones, so that the seismic data can reflect the corresponding volcanic facies zones. Based on this, since a single seismic attribute is insufficient to adequately represent the distribution of volcanic facies zones, a second seismic attribute data body is obtained by fusing multiple target seismic attributes within the first seismic attribute data body. This second seismic attribute data body clearly shows the boundaries of each volcanic facies zone, allowing technicians to intuitively visualize the distribution of volcanic facies zones. The clear boundaries overcome the problem of inaccurate characterization of volcanic structures and lithofacies features in related technologies, improving the prediction accuracy of high-quality volcanic reservoirs, reducing drilling risks, and providing reliable data for the efficient exploration and development of oil and gas reservoirs.
[0118] This application embodiment also provides a device 300 for spreading volcanic rock facies zones, the structural block diagram of which is shown below. Figure 3 As shown, the device 300 includes: an establishment module 301, a determination module 302, and a fusion module 303.
[0119] Among them, module 301 is used to establish a volcanic rock lithology identification chart based on drilling and logging data of the area to be tested.
[0120] The determination module 302 is used to determine the macroscopic characteristics of the volcanic structure based on the seismic data of the area to be measured, and to obtain the first seismic attribute data volume.
[0121] The determination module 302 is also used to determine multiple volcanic rock facies zones based on the volcanic rock lithology identification chart and the macroscopic characteristics of volcanic structures.
[0122] The determination module 302 is also used to perform fine well-seismic calibration of the first seismic attribute data volume based on the drilling data and well logging data of the area to be measured, and to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone.
[0123] The fusion module 303 is used to fuse the first seismic attribute data volume based on multiple target seismic attributes to obtain the second seismic attribute data volume.
[0124] In some embodiments, the establishment module 301 includes: a first determining unit, a first obtaining unit, a second determining unit, and a second obtaining unit.
[0125] The first determining unit is used to determine multiple lithological sample points based on rock thin sections and core samples from the drilling data of the area to be tested, as well as the logging data of the area to be tested.
[0126] The first obtaining unit is used to obtain multiple logging curves based on the logging data of the area to be tested.
[0127] The second determining unit is used to perform matrix intersection on multiple logging curves based on multiple lithological sample points to determine the first target parameter curve and the second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve.
[0128] The second obtaining unit is used to obtain a volcanic rock lithology identification chart based on the first target parameter curve and the second target parameter curve.
[0129] In some embodiments, the second obtaining unit includes:
[0130] The resulting sub-units are used to perform intersection processing on the first target parameter curve and the second target parameter curve to obtain a volcanic rock lithology identification map.
[0131] In some embodiments, the determining module 302 includes:
[0132] The third determining unit is used to determine the macroscopic characteristics of the volcanic structure by flattening the seismic data, analyzing the layer amplitude properties, and the coherence properties.
[0133] Among them, the macroscopic characteristics of volcanic structures include the location of the crater and the stratigraphic occurrence of the volcanic structure.
[0134] In some embodiments, the determining module 302 further includes:
[0135] The third unit is used to classify the volcanic rock lithology on the volcanic rock lithology identification plate according to the macroscopic characteristics of the volcanic structure, and to obtain multiple volcanic rock facies zones.
[0136] Each volcanic facies zone includes at least one volcanic rock lithology.
[0137] In some embodiments, the device further includes:
[0138] The acquisition module is used to acquire seismic attributes of multiple targets.
[0139] The target earthquake attributes include amplitude, continuity, and frequency.
[0140] In some embodiments, the fusion module 302 includes:
[0141] The fourth unit is used to perform low-pass filtering, band-pass filtering, and high-pass filtering on multiple target seismic attributes corresponding to each seismic data in the first seismic attribute data volume, respectively, to obtain the fused attribute corresponding to each seismic data.
[0142] The fusion attribute corresponding to each seismic data point is calculated using the following formula:
[0143]
[0144] In the formula: f k (x) represents the target seismic attribute; m represents the number of target seismic attributes; w k The weights of each target seismic attribute, and x is the optimal solution; x is a linear weighted average.
[0145] Therefore, the volcanic rock facies zone distribution device provided in this application obtains a volcanic rock lithology identification map for the area to be measured by drilling and logging data in the area to be measured, and determines the macroscopic characteristics of the volcanic structure in the area by combining the seismic data of the area, thereby identifying multiple volcanic rock facies zones in the area; then, by combining the drilling and logging data of the area, the first seismic attribute data volume obtained from the seismic data is finely calibrated by well-seismic calibration to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zones, so that the seismic data can reflect the corresponding volcanic rock facies zones. Based on this, since a single seismic attribute is insufficient to adequately represent the distribution of volcanic facies zones, a second seismic attribute data body is obtained by fusing multiple target seismic attributes within the first seismic attribute data body. This second seismic attribute data body clearly shows the boundaries of each volcanic facies zone, allowing technicians to intuitively visualize the distribution of volcanic facies zones. The clear boundaries overcome the problem of inaccurate characterization of volcanic structures and lithofacies features in related technologies, improving the prediction accuracy of high-quality volcanic reservoirs, reducing drilling risks, and providing reliable data for the efficient exploration and development of oil and gas reservoirs.
[0146] This application also provides an electronic device, the structural schematic diagram of which is shown below. Figure 4 The electronic device can vary considerably due to differences in configuration or performance. It may include one or more central processing units (CPUs) 401 and one or more memories 402. The memory 401 stores at least one line of program code, which is loaded and executed by the processor 401 to implement the volcanic facies belt distribution method provided in the above-described method embodiments. Of course, the electronic device may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The electronic device may also include other components for implementing device functions, which will not be elaborated upon here.
[0147] In some embodiments, the computer program involved in the present application embodiments may be deployed on an electronic device for execution, or executed on multiple electronic devices located in one location, or executed on multiple electronic devices distributed in multiple locations and interconnected through a communication network. Multiple electronic devices distributed in multiple locations and interconnected through a communication network may constitute a blockchain system.
[0148] This application also provides a computer-readable storage medium, such as a memory including program code, which can be executed by a processor in an electronic device to complete the method for fixing the distribution of volcanic rock facies provided in the above method embodiments. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.
[0149] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.
[0150] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.
Claims
1. A method for the distribution of volcanic rock facies zones, characterized in that, The method includes: Based on the drilling and logging data of the area to be tested, a volcanic rock lithology identification chart was established; Based on the seismic data of the area to be measured, the macroscopic features of the volcanic structure are determined, and a first seismic attribute data volume is obtained; the determination of the macroscopic features of the volcanic structure based on the seismic data of the area to be measured includes: determining the macroscopic features of the volcanic structure by flattening the seismic data into slices, analyzing the amplitude attributes along the layers, and determining the coherence attributes; wherein, the macroscopic features of the volcanic structure include the location of the crater and the stratigraphic attitude of the volcanic structure; Based on the macroscopic characteristics of the volcanic structure, the volcanic rock lithology on the volcanic rock lithology identification chart is divided into multiple volcanic rock facies zones; wherein each volcanic rock facies zone includes at least one volcanic rock lithology. Based on the drilling and logging data of the area to be tested, the first seismic attribute data volume is finely calibrated to determine the one-to-one correspondence between the seismic data and the volcanic rock facies zone. The seismic data includes: amplitude intensity, phase axis continuity, frequency characteristics, and external morphology. Based on multiple target seismic attributes, the first seismic attribute data volume is fused to obtain the second seismic attribute data volume; the target seismic attributes include amplitude, continuity, and frequency.
2. The method for the distribution of volcanic rock facies zones according to claim 1, characterized in that, The process of establishing a volcanic rock lithology identification chart based on drilling and logging data of the area to be tested includes: Based on the rock thin sections and core samples from the drilling data of the area to be tested, as well as the logging data of the area to be tested, multiple lithological sample points are determined. Based on the well logging data of the area to be tested, multiple well logging curves were obtained; Based on the multiple lithological sample points, matrix intersection is performed on the multiple logging curves to determine the first target parameter curve and the second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve; Based on the first target parameter curve and the second target parameter curve, the volcanic rock lithology identification chart is obtained.
3. The method for the distribution of volcanic rock facies zones according to claim 2, characterized in that, The step of obtaining the volcanic rock lithology identification chart based on the first target parameter curve and the second target parameter curve includes: The first target parameter curve and the second target parameter curve are subjected to intersection processing to obtain the volcanic rock lithology identification map.
4. The method for the distribution of volcanic rock facies zones according to claim 1, characterized in that, Before fusing the first seismic attribute data volume based on multiple target seismic attributes, the method further includes: Obtain the earthquake attributes of the multiple targets.
5. The method for the distribution of volcanic rock facies zones according to claim 1, characterized in that, The step of fusing the first seismic attribute data volume based on multiple target seismic attributes includes: Low-pass filtering, band-pass filtering, and high-pass filtering are applied to the multiple target seismic attributes corresponding to each seismic data in the first seismic attribute data volume to obtain the fused attribute corresponding to each seismic data. The fusion attribute corresponding to each seismic data point is calculated using the following formula: In the formula: f k (x) represents the target seismic attribute; m represents the number of target seismic attributes; w k The weights of each target seismic attribute, and ; This is the optimal solution; x is a linear weighted sum.
6. A device for displaying volcanic rock facies zones, characterized in that, The device includes: A module is established to create a volcanic rock lithology identification chart based on drilling and logging data of the area to be tested; The determination module is used to determine the macroscopic characteristics of the volcanic structure based on the seismic data of the area to be measured, and to obtain the first seismic attribute data volume; The determining module is used to determine the macroscopic features of the volcanic structure by flattening the seismic data, analyzing the amplitude attributes along the layers, and determining the coherence attributes; wherein, the macroscopic features of the volcanic structure include the location of the crater and the stratigraphic attitude of the volcanic structure; The determining module is further configured to divide the volcanic rock lithology on the volcanic rock lithology identification chart according to the macroscopic characteristics of the volcanic structure, thereby obtaining multiple volcanic rock facies zones; wherein each volcanic rock facies zone includes at least one volcanic rock lithology; the determining module is further configured to perform fine well-seismic calibration on the first seismic attribute data volume according to the drilling data and logging data of the area to be measured, thereby determining the one-to-one correspondence between the seismic data and the volcanic rock facies zones, wherein the seismic data includes: amplitude intensity, phase axis continuity, frequency characteristics, and external morphology; The fusion module is used to fuse the first seismic attribute data volume according to multiple target seismic attributes to obtain a second seismic attribute data volume; the target seismic attributes include amplitude, continuity and frequency.
7. The device for distributing volcanic rock facies zones according to claim 6, characterized in that, The establishment module includes: The first determining unit is used to determine multiple lithological sample points based on the rock thin sections and core samples in the drilling data of the area to be tested and the logging data of the area to be tested. The first obtaining unit is used to obtain multiple logging curves based on the logging data of the area to be tested; The second determining unit is used to perform matrix intersection on the multiple logging curves based on the multiple lithological sample points to determine a first target parameter curve and a second target parameter curve, wherein the multiple logging curves include the first target parameter curve and the second target parameter curve; The second obtaining unit is used to obtain the volcanic rock lithology identification chart based on the first target parameter curve and the second target parameter curve.
8. The device for distributing volcanic rock facies zones according to claim 7, characterized in that, The second obtaining unit includes: The resulting sub-unit is used to perform intersection processing on the first target parameter curve and the second target parameter curve to obtain the volcanic rock lithology identification map.