CN114427452B - Imaging method, device, storage medium and computer equipment for microstructure geologic body - Google Patents
Imaging method, device, storage medium and computer equipment for microstructure geologic body Download PDFInfo
- Publication number
- CN114427452B CN114427452B CN202010936091.5A CN202010936091A CN114427452B CN 114427452 B CN114427452 B CN 114427452B CN 202010936091 A CN202010936091 A CN 202010936091A CN 114427452 B CN114427452 B CN 114427452B
- Authority
- CN
- China
- Prior art keywords
- imaging data
- target reservoir
- imaging
- data volume
- volume
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000003384 imaging method Methods 0.000 title claims abstract description 411
- 238000003860 storage Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 claims abstract description 43
- 238000012545 processing Methods 0.000 claims abstract description 16
- 238000010606 normalization Methods 0.000 claims abstract description 12
- 239000011324 bead Substances 0.000 claims description 20
- 238000004590 computer program Methods 0.000 claims description 10
- 230000015572 biosynthetic process Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 4
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 10
- 208000010392 Bone Fractures Diseases 0.000 description 8
- 206010017076 Fracture Diseases 0.000 description 8
- 238000012512 characterization method Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 6
- 238000001914 filtration Methods 0.000 description 6
- 238000005755 formation reaction Methods 0.000 description 5
- 238000000354 decomposition reaction Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 4
- 230000005012 migration Effects 0.000 description 4
- 238000013508 migration Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 229910052704 radon Inorganic materials 0.000 description 3
- SYUHGPGVQRZVTB-UHFFFAOYSA-N radon atom Chemical compound [Rn] SYUHGPGVQRZVTB-UHFFFAOYSA-N 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 239000011435 rock Substances 0.000 description 2
- 235000013628 Lantana involucrata Nutrition 0.000 description 1
- 235000006677 Monarda citriodora ssp. austromontana Nutrition 0.000 description 1
- 240000007673 Origanum vulgare Species 0.000 description 1
- 208000013201 Stress fracture Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000009933 burial Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000001427 coherent effect Effects 0.000 description 1
- 238000005056 compaction Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000005553 drilling Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012067 mathematical method Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
Landscapes
- Engineering & Computer Science (AREA)
- Geology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Mining & Mineral Resources (AREA)
- Environmental & Geological Engineering (AREA)
- Fluid Mechanics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention provides an imaging method, an imaging device, a storage medium and computer equipment of a microstructure geologic body, wherein the method comprises the following steps: s200: imaging the target reservoir by using different imaging methods to obtain a plurality of initial imaging data volumes of the target reservoir; s400: carrying out normalization processing on the seismic amplitude of each initial imaging data body of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir; s600: determining a weighting coefficient for each imaged data volume of the target reservoir; s800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir. The imaging method of the microstructure geologic body provided by the invention can comprehensively utilize the advantages of various imaging methods to obtain more accurate imaging results.
Description
Technical Field
The invention relates to the technical field of oil and gas geophysics, in particular to an imaging method, an imaging device, a storage medium and computer equipment of a microstructure geologic body.
Background
The oil and gas exploration in China already enters the deep exploration and fine exploration stages. At this stage, the oil-gas reservoirs with weak reflection characteristics and special structures such as unconventional oil-gas reservoirs, fractured oil-gas reservoirs, thin interbedded oil-gas reservoirs, weak reflection beads, compact oil-gas reservoirs and the like are key targets for exploration work in the oil-gas industry. The fine imaging technology of the oil and gas reservoirs is an important precondition for the oil and gas reservoirs to be built.
Taking sea carbonate as an example, such reservoirs are rich in oil and gas resources, with oil and gas production accounting for about 60% of the total world production. Large carbonate oil and gas fields with the characteristics of the type and the type are arranged in a plurality of detection areas such as Sichuan basin, tarim basin, erdos basin, bohai sea, south sea bead river mouth and the like in China. Research on such reservoirs for many years has found that the collapsed structure of carbonate formations can form a large scale of elongated distributions, and circular and flat faults can develop in the elongated collapsed bands. When cave detritus has a large wave impedance difference with the carbonate reservoir surrounding rock, these collapsed cave and its detritus will appear as beaded reflections on the seismic profile, and thus the beaded reflections of the carbonate reservoir are also commonly interpreted as collapsed ancient cave. In addition, because of the differential compaction effect caused by the increase of the burial depth, cracks are generated above the collapsed karst cave, so that the karst cave connecting sheets become an ancient karst cave system with larger scale, and a good oil reservoir storage space is formed. We generally refer to such karst cave systems as fracture-cave connectors. Zhu Shengwang et al confirm that such collapsed karst cave systems are good formations by drilling. Such reservoirs diffract the seismic data with poor wave development and wave packet continuity. Therefore, the conventional imaging method using primary reflection waves as a main subject has difficulty in achieving accurate imaging of carbonate reservoirs. 86% of unused reserves of the Oregano fracture-cavity type oil reservoir of the Tahe oil field are positioned in a weak reflection area or a development area without obvious reflection characteristics. Thus, enhancing the study of imaging of the weak amplitude reflection feature is of great significance.
Microstructural reservoir studies of weak reflection and fracture development have focused mainly on both reservoir characterization and imaging. With respect to imaging technology, a great deal of research work has been currently done by many scholars. Kozlov, moser and the like respectively compress reflection and highlight diffraction energy in the imaging process by modifying a weighting function in a Kirchhoff prestack depth migration integral formula, and according to characteristic differences of reflection and diffraction energy on different prestack gathers such as a common offset gather, a common gun gather, a synthetic plane wave gather and the like and a local imaging matrix gather, weak reflection energy is extracted by utilizing wave field separation methods such as dip angle filtering, reflection focusing, weighted Radon transformation, plane wave deconstruction filtering, singular value decomposition and the like, so that the imaging precision of a scattering target body is improved; zhu Shengwang, and the like, suppressing coherent noise of the co-scattering point gathers by using an inclination decomposition method so as to improve diffraction wave imaging resolution of carbonate rock; cohen and Bleistein establish a reverse scattering disturbance inversion imaging method based on small disturbance approximation and Born approximation; tarantola, mora and Pratt et al 1999 explored least squares inversion methods to correct the best subsurface medium model in the time and frequency domains, respectively; du Zhengcong, and the like, deducing and utilizing Rytov approximate Fourier wave field prolongation operators to forward and shift the carbonate fracture-cavity reservoir and reveal wave field characteristics of the carbonate fracture-cavity reservoir; lu Minghui analyzes the main control factors affecting the imaging precision of the carbonate karst cave in the frequency domain sound wave back scattering imaging method.
Most of the above imaging methods focus on improving the imaging effect based on an improvement of a certain mathematical method. In the practical application aspect, as the actual data has extremely complex reflection characteristics, the imaging problems of weak reflection and microstructure are generally difficult to be well solved by the result of a single method.
Disclosure of Invention
The invention mainly aims to provide an imaging method, an imaging device, a storage medium and computer equipment of a microstructure geologic body, so as to solve the problem of fine imaging of the microstructure geologic body.
In a first aspect, the application provides a method for imaging a microstructured body, comprising the steps of: s200: imaging the target reservoir by using different imaging methods to obtain a plurality of initial imaging data volumes of the target reservoir; s400: normalizing the seismic amplitude of each initial imaging data volume in a plurality of initial imaging data volumes of a target reservoir to obtain a plurality of imaging data volumes of the target reservoir; s600: determining an imaging data volume from a plurality of imaging data volumes of a target reservoir as a basic imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structure geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structure geologic volume in the basic imaging data volume; s800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
In one embodiment, in S600, the base imaging data volume is one of a plurality of imaging data volumes of a target reservoir that is capable of characterizing a geologic formation of the target reservoir.
In one embodiment, in S600, after determining one imaging data volume from the plurality of imaging data volumes in the target reservoir as the base imaging data volume, the method further includes the steps of: selecting a valid imaging data volume from imaging data volumes of a target reservoir other than the base imaging data volume, wherein the valid imaging data volume is one of the imaging data volumes of the target reservoir that is capable of characterizing a structural feature of a micro-geologic formation of the target reservoir; determining a weighting coefficient for each imaging data volume of the target reservoir based on a proportional relationship between a mean value of seismic amplitudes of the microstructured bodies in each imaging data volume of the target reservoir and a mean value of seismic amplitudes of the microstructured bodies in the base imaging data volume, comprising: and determining the weighting coefficient of the effective imaging data volume of the target reservoir according to the proportional relation between the seismic amplitude average value of the micro-structural geologic volume in the effective imaging data volume of the target reservoir and the seismic amplitude average value of the micro-structural geologic volume in the basic imaging data volume.
In one embodiment, in S600, determining a weighting factor for an effective imaging data volume of a target reservoir based on a proportional relationship between a seismic amplitude average for a microstructured volume in the effective imaging data volume of the target reservoir and a seismic amplitude average for a microstructured volume in a base imaging data volume, comprises: when the average value of the seismic amplitudes of the micro-structure bodies in the effective imaging data body of the target reservoir is smaller than the average value of the seismic amplitudes of the micro-structure bodies in the base imaging data body, taking the ratio of the average value of the seismic amplitudes of the micro-structure bodies in the base imaging data body to the average value of the seismic amplitudes of the micro-structure bodies in the effective imaging data body of the target reservoir as the weighting coefficient of the effective imaging data body of the target reservoir, and taking the ratio of the average value of the seismic amplitudes of the micro-structure bodies in the effective imaging data body of the target reservoir to the average value of the seismic amplitudes of the micro-structure bodies in the base imaging data body as the weighting coefficient of the effective imaging data body of the target reservoir.
In one embodiment, in S800, weighting and summing each imaging data volume of the target reservoir according to each imaging data volume of the target reservoir and its weighting coefficients, includes: and carrying out weighted summation on the basic imaging data volume and the effective imaging data volume of the target reservoir according to the basic imaging data volume and the effective imaging data volume of the target reservoir and the weighting coefficient of the effective imaging data volume.
In one embodiment, in S800, the final imaged data volume of the target reservoir is determined using the following equation:
A＝A0+∑Ai*Ci
Where A represents the final imaging data volume of the target reservoir, A 0 represents the base imaging data volume of the target reservoir, A i represents the i-th valid imaging data volume of the target reservoir, and C i represents the weighting coefficients of the valid imaging data volumes A i of the target reservoir.
In one embodiment, the weighting factor of the underlying imaged data volume of the target reservoir is 1.
In a second aspect, the present application provides an imaging device for a microstructured geological volume, comprising: the data acquisition module is used for imaging the target reservoir by utilizing different imaging methods to acquire a plurality of initial imaging data volumes of the target reservoir; the normalization processing module is used for normalizing the amplitude of each initial imaging data body in the plurality of initial imaging data bodies of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir; the weight calculation module is used for determining one imaging data body from a plurality of imaging data bodies of the target reservoir as a basic imaging data body, and determining a weighting coefficient of each imaging data body of the target reservoir according to a proportional relation between an average value of the seismic amplitude of the micro-structure geologic body in each imaging data body of the target reservoir and an average value of the seismic amplitude of the micro-structure geologic body in the basic imaging data body; and the imaging processing module is used for carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
In a third aspect, the present application provides a storage medium storing a computer program which, when executed by a processor, performs the steps of the method of imaging a microstructured geological volume as described above.
In a fourth aspect, the present application provides a computer device comprising a processor and a storage medium storing program code which, when executed by the processor, performs the steps of the method of imaging a microstructured geological volume as described above.
The micro-structure geologic body imaging method of the invention quantitatively fuses the advantages of various imaging technologies aiming at the weak reflection and the micro-structure geologic body in the seismic data, improves the structural imaging effect of the weak reflection and the micro-structure geologic body, improves the characterization effect of the micro-structure geologic body, and is beneficial to increasing the storage and production.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a undue limitation on the application, wherein:
FIG. 1 is a flow chart of a method of imaging a microstructured body in accordance with an exemplary embodiment of the present application;
FIG. 2 is a cross-sectional view of the results of imaging a target reservoir using pure diffraction imaging techniques for a method of imaging a microstructured body of land according to an embodiment of the present application;
FIG. 3 is a cross-sectional view of imaging results of a target reservoir using dip imaging techniques for a method of imaging a microstructured body in accordance with an embodiment of the present application;
FIG. 4 is a cross-sectional view of the results of imaging a target reservoir using conventional kirchhoff migration imaging techniques, according to an embodiment of the present application;
FIG. 5 is a cross-sectional view of the final imaging result of a target reservoir using the method of imaging a microstructured body of land according to an embodiment of the present application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
Example 1
Fig. 1 is a flow chart of a method of imaging a microstructured body in accordance with an exemplary embodiment of the present application. As shown in fig. 1, the present embodiment provides an imaging method of a microstructure geological body, including the following steps:
s200: imaging the target reservoir using different imaging methods to obtain a plurality of initial imaged data volumes of the target reservoir.
Among other things, different imaging methods may include, but are not limited to, the following:
(1) The method comprises the steps of compressing reflection and standing diffraction energy in an imaging process by modifying a weighting function in a Kirchhoff prestack depth migration integral formula, extracting weak reflection energy according to characteristic differences of reflection and diffraction energy on different prestack gathers such as a common offset gather, a common shot gather and a synthetic plane wave gather and a local imaging matrix gather and by utilizing wave field separation methods such as dip angle filtering, reflection focusing, weighted Radon transformation, plane wave deconstructing filtering and singular value decomposition, and the like, so that imaging precision of a scattering target body is improved;
(2) Establishing a back scattering disturbance inversion imaging method based on the small disturbance approximation and the Born approximation;
(3) A least squares inversion method for modifying an optimal subsurface medium model in the time and frequency domains.
Each imaging method has its own advantages and disadvantages, and a plurality of different imaging methods with advantages meeting imaging requirements can be selected to image the target reservoir.
S400: and carrying out normalization processing on the seismic amplitude of each initial imaging data body in the plurality of initial imaging data bodies of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir.
And unifying the seismic amplitude of each initial imaging data body of the target reservoir into the same numerical range through normalization processing. The specific normalization method and the normalized numerical range can be set according to the requirements.
S600: determining one imaging data volume from a plurality of imaging data volumes of a target reservoir as a base imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structural geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structural geologic volume in the base imaging data volume.
S800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
Wherein, the microstructure geologic body can comprise a weak reflection geologic body and a microstructure geologic body such as a bead, a karst cave, a small fracture, a small-scale crack and the like.
The imaging method of the microstructure geologic body provided by the invention can comprehensively utilize the advantages of various imaging methods to obtain more accurate imaging results.
Example two
The embodiment provides an imaging method of a microstructure geologic body, which comprises the following steps:
s200: imaging the target reservoir using different imaging methods to obtain a plurality of initial imaged data volumes of the target reservoir.
Among other things, different imaging methods may include, but are not limited to, the following:
(1) The method comprises the steps of compressing reflection and standing diffraction energy in an imaging process by modifying a weighting function in a Kirchhoff prestack depth migration integral formula, extracting weak reflection energy according to characteristic differences of reflection and diffraction energy on different prestack gathers such as a common offset gather, a common shot gather and a synthetic plane wave gather and a local imaging matrix gather and by utilizing wave field separation methods such as dip angle filtering, reflection focusing, weighted Radon transformation, plane wave deconstructing filtering and singular value decomposition, and the like, so that imaging precision of a scattering target body is improved;
(2) Establishing a back scattering disturbance inversion imaging method based on the small disturbance approximation and the Born approximation;
(3) A least squares inversion method for modifying an optimal subsurface medium model in the time and frequency domains.
Each imaging method has its own advantages and disadvantages, and a plurality of different imaging methods with advantages meeting imaging requirements can be selected to image the target reservoir.
S400: and carrying out normalization processing on the seismic amplitude of each initial imaging data body in the plurality of initial imaging data bodies of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir.
And unifying the seismic amplitude of each initial imaging data body of the target reservoir into the same numerical range through normalization processing. The specific normalization method and the normalized numerical range can be set according to the requirements.
S600: determining one imaging data volume from a plurality of imaging data volumes of a target reservoir as a base imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structural geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structural geologic volume in the base imaging data volume.
Wherein the base imaging data volume is one of a plurality of imaging data volumes of a target reservoir that is capable of characterizing a geologic structure of the target reservoir. Preferably, a relatively smooth imaging data volume capable of reflecting the geological structure pattern of the target reservoir is selected as the base imaging data volume from among the plurality of imaging data volumes of the target reservoir. The base imaging data volume may not have the characteristics to highlight the structural features that reflect the weak reflection or microstructure of the target reservoir, as is required with conventional imaging techniques.
In one example, after determining the base imaging data volume from the plurality of imaging data volumes of the target reservoir, S600 further includes the steps of: a valid imaging data volume is selected from the imaging data volumes of the target reservoir other than the base imaging data volume, wherein the valid imaging data volume is one of the imaging data volumes of the target reservoir that is capable of characterizing a structural feature of a micro-geologic formation of the target reservoir. Correspondingly, determining the weighting coefficient of each imaging data volume of the target reservoir according to the proportional relationship between the average value of the seismic amplitude of the micro-structure geologic volume in each imaging data volume of the target reservoir and the average value of the seismic amplitude of the micro-structure geologic volume in the base imaging data volume, comprising: and determining the weighting coefficient of the effective imaging data volume of the target reservoir according to the proportional relation between the seismic amplitude average value of the micro-structural geologic volume in the effective imaging data volume of the target reservoir and the seismic amplitude average value of the micro-structural geologic volume in the basic imaging data volume. Wherein the weighting coefficient of the underlying imaged data volume of the target reservoir is 1.
Specifically, the effective imaging data volume is an imaging data volume which can still represent the microstructure geologic body characteristics of the target reservoir after the seismic amplitude normalization.
Determining a weighting coefficient of an effective imaging data volume of a target reservoir according to a proportional relationship between an average value of seismic amplitudes of the micro-structural geologic volume in the effective imaging data volume of the target reservoir and an average value of seismic amplitudes of the micro-structural geologic volume in the base imaging data volume, comprising:
When the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir is smaller than the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body, taking the ratio of the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body to the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir as the weighting coefficient of the effective imaging data body of the target reservoir,
When the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir is larger than or equal to the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body, taking the ratio of the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir to the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body as the weighting coefficient of the effective imaging data body of the target reservoir.
S800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
Wherein the weighted summation of the imaging data volumes of the target reservoir according to the imaging data volumes of the target reservoir and the weighting coefficients thereof comprises: and carrying out weighted summation on the basic imaging data volume and the effective imaging data volume of the target reservoir according to the basic imaging data volume and the effective imaging data volume of the target reservoir and the weighting coefficient of the effective imaging data volume.
In one example, the final imaging data volume for the target reservoir may be determined using expression (1):
A＝A0+∑Ai*Ci (1)
Where A represents the final imaging data volume of the target reservoir, A 0 represents the base imaging data volume of the target reservoir, A i represents the i-th valid imaging data volume of the target reservoir, and C i represents the weighting coefficients of the valid imaging data volumes A i of the target reservoir. In expression (1), the valid data volumes of the target reservoir are secondarily weighted based on the weighting coefficient of each valid data volume.
The micro-structure geologic body imaging method of the invention quantitatively fuses the advantages of various imaging technologies, screens out basic data bodies from a plurality of data bodies, screens out possible false image data bodies, applies targeted imaging results to carry out weighted superposition, further improves the weak reflection and the structure imaging effect of the micro-structure geologic body, and provides finer characterization data for the reservoir research.
Example III
The method for imaging a microstructured body according to the present invention will be described with reference to one embodiment.
In a certain target exploration area in Xinjiang, imaging characterization needs to be carried out on beads with weak reflection characteristics in a target layer, and the beads can be communicated with each other only by being associated with cracks, so that a good oil and gas reservoir bead group is formed. Thus, imaging requires simultaneous characterization of beads and micro-fractures, which is difficult to achieve with conventional methods. According to the method of the invention, beads and micro-breaks can be characterized as follows:
Step one: three imaging result data volumes of bead imaging are selected. As shown in fig. 2, 3 and 4, the target reservoir is imaged using pure diffracted wave imaging technique, dip imaging technique and conventional kirchhoff offset imaging technique, respectively.
The region has a target layer near the depth of 3.85s, the layer develops weak reflection beads, X-type partial beads develop in the medium of the homophase shaft layer of 3.75s in figures 2, 3 and 4, and joint development regions of Y-type beads exist near the depth of 3.82s below the homophase shaft. The three technical result data volume graphs in fig. 2, 3 and 4 are subjected to amplitude normalization processing. The pure diffraction wave imaging result of fig. 2 is set as a data volume A1, the tilt imaging result of fig. 3 is set as a data volume A2, and the kirchhoff shift result of fig. 4 is set as a data volume A3.
Step two: analyzing each data body of A1, A2 and A3, selecting a basic imaging data body A0, and simultaneously selecting an Ai data body capable of effectively representing a target layer.
Of the 3 imaging data, the relatively smooth imaging result that can substantially reflect the geological structure pattern of the region is the kirchhoff shift technique result of fig. 4, and thus A3 is set as the base data volume A0.
The A1 result data body is extremely messy, and the 3.75s of X-type partial beads developed in the homophase axis layer medium have imaging characterization, but the homophase axis of the layer cannot be imaged, so that the lamellar medium is destroyed, the A1 result data body is abandoned, and only A2 is used for participating in the next step.
A2 imaging result data body is seen in the section result of 3, the imaging effect of the imaging result data body on the X class and the Y class of the weak reflection beads can be found to be ideal, but the beads have too many artifacts and do not accord with the actual geological condition. Therefore, the following calculation is only participated as a parameter data volume.
Step three: the amplitude value ranges of other data volumes than A0 (in this example, only A2 data volume) are weighted twice. According to the method of the present invention, the weighting coefficient c2=1.31 is obtained, and the final imaging result data volume a is obtained according to expression (1) as shown in fig. 5. The plane result in the graph can find that the X-class and Y-class weak beads and the fracture and the boundary thereof can be better distinguished by imaging characterization, and the effective weak beads and the fracture resolution can be distinguished by imaging effect.
In this example, it can be seen that the imaging of the present invention has significantly better structural characteristics than conventional results, and therefore has significant advantages in finding beads, karst cave, small breaks, small-scale cracks, and the like.
Example IV
The present embodiment provides an imaging device of a microstructure geological body, including: the data acquisition module is used for imaging the target reservoir by utilizing different imaging methods to acquire a plurality of initial imaging data volumes of the target reservoir; the normalization processing module is used for normalizing the amplitude of each initial imaging data body in the plurality of initial imaging data bodies of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir; the weight calculation module is used for determining one imaging data body from a plurality of imaging data bodies of the target reservoir as a basic imaging data body, and determining a weighting coefficient of each imaging data body of the target reservoir according to a proportional relation between an average value of the seismic amplitude of the micro-structure geologic body in each imaging data body of the target reservoir and an average value of the seismic amplitude of the micro-structure geologic body in the basic imaging data body; and the imaging processing module is used for carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
Example five
The present embodiment provides a storage medium storing a computer program which, when executed by a processor, performs the steps of the method of imaging a microstructured body as described above:
S200: imaging the target reservoir by using different imaging methods to obtain a plurality of initial imaging data volumes of the target reservoir;
s400: normalizing the seismic amplitude of each initial imaging data volume in a plurality of initial imaging data volumes of a target reservoir to obtain a plurality of imaging data volumes of the target reservoir;
S600: determining an imaging data volume from a plurality of imaging data volumes of a target reservoir as a basic imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structure geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structure geologic volume in the basic imaging data volume;
s800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or a computer program product. Thus, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations of methods and computer program products according to embodiments of the invention. It will be understood that each flow in the flowchart, and combinations of flows in the flowchart, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows.
Storage media, including both permanent and non-permanent, removable and non-removable media, may be implemented in any method or technology for storage of information. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
Example six
The present embodiment provides a computer device comprising a processor and a storage medium storing program code which, when executed by the processor, performs the steps of the method of imaging a microstructured geological volume as described above:
S200: imaging the target reservoir by using different imaging methods to obtain a plurality of initial imaging data volumes of the target reservoir;
s400: normalizing the seismic amplitude of each initial imaging data volume in a plurality of initial imaging data volumes of a target reservoir to obtain a plurality of imaging data volumes of the target reservoir;
S600: determining an imaging data volume from a plurality of imaging data volumes of a target reservoir as a basic imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structure geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structure geologic volume in the basic imaging data volume;
s800: and carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir.
In one embodiment, a computer device includes one or more processors (CPUs), an input/output interface, a network interface, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash memory (FLASH FLASH RAM). Memory is an example of computer-readable media.
The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is noted that the terms used herein are used merely to describe particular embodiments and are not intended to limit exemplary embodiments in accordance with the present application, when the terms "comprising" and/or "including" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
It should be noted that the terms "first," "second," and the like in the description and the claims and drawings of the present application are used for distinguishing between similar objects and not for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein.
It should be understood that the exemplary embodiments in this specification may be embodied in many different forms and should not be construed as limited to only the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of these exemplary embodiments to those skilled in the art, and should not be construed as limiting the application.
All equivalent structures or equivalent flow changes made by the specification and the attached drawings of the invention or directly or indirectly applied to other related technical fields are included in the protection scope of the invention.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a readable storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, including several instructions for causing a system device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
Claims (8)
1. An imaging method of a microstructure geologic body, comprising the steps of:
S200: imaging the target reservoir by using different imaging methods to obtain a plurality of initial imaging data volumes of the target reservoir;
s400: normalizing the seismic amplitude of each initial imaging data volume in a plurality of initial imaging data volumes of a target reservoir to obtain a plurality of imaging data volumes of the target reservoir;
S600: determining an imaging data volume from a plurality of imaging data volumes of a target reservoir as a basic imaging data volume, and determining a weighting coefficient of each imaging data volume of the target reservoir according to a proportional relationship between an average value of the seismic amplitudes of the micro-structure geologic volume in each imaging data volume of the target reservoir and an average value of the seismic amplitudes of the micro-structure geologic volume in the basic imaging data volume;
S800: carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and a weighting coefficient thereof, determining a final imaging data body of the target reservoir according to a result of the weighted summation, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir;
The weighting coefficient of the basic imaging data volume of the target reservoir is 1;
The microstructure geologic body comprises a weak reflection geologic body with beads, karst cave, small fracture and small-scale crack and a microstructure geologic body;
after said determining an imaging data volume of the plurality of imaging data volumes of the target reservoir as a base imaging data volume, the method further comprises the steps of:
Selecting a valid imaging data volume from imaging data volumes of a target reservoir other than the base imaging data volume, wherein the valid imaging data volume is one of the imaging data volumes of the target reservoir that is capable of characterizing a structural feature of a micro-geologic formation of the target reservoir;
Determining a weighting coefficient for each imaging data volume of the target reservoir based on a proportional relationship between a mean value of seismic amplitudes of the microstructured bodies in each imaging data volume of the target reservoir and a mean value of seismic amplitudes of the microstructured bodies in the base imaging data volume, comprising:
And determining the weighting coefficient of the effective imaging data volume of the target reservoir according to the proportional relation between the seismic amplitude average value of the micro-structural geologic volume in the effective imaging data volume of the target reservoir and the seismic amplitude average value of the micro-structural geologic volume in the basic imaging data volume.
2. The method of imaging a microstructured geologic volume of claim 1, wherein in S600 the base imaging data volume is one of a plurality of imaging data volumes of a target reservoir that is capable of characterizing a geologic structure pattern of the target reservoir.
3. The method of imaging a microstructured volume of claim 1, wherein in S600, determining the weighting factor of the effective imaging data volume of the target reservoir based on the proportional relationship between the average of the seismic amplitudes of the microstructured volume in the effective imaging data volume of the target reservoir and the average of the seismic amplitudes of the microstructured volume in the base imaging data volume comprises:
When the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir is smaller than the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body, taking the ratio of the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body to the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir as the weighting coefficient of the effective imaging data body of the target reservoir,
When the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir is larger than or equal to the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body, taking the ratio of the average value of the seismic amplitudes of the micro-structure geologic bodies in the effective imaging data body of the target reservoir to the average value of the seismic amplitudes of the micro-structure geologic bodies in the basic imaging data body as the weighting coefficient of the effective imaging data body of the target reservoir.
4. The method of imaging a microstructured body of claim 1, wherein in S800, weighting and summing each imaging data volume of the target reservoir according to each imaging data volume of the target reservoir and its weighting coefficients comprises:
And carrying out weighted summation on the basic imaging data volume and the effective imaging data volume of the target reservoir according to the basic imaging data volume and the effective imaging data volume of the target reservoir and the weighting coefficient of the effective imaging data volume.
5. The method of imaging a microstructured geological volume of claim 1, wherein in S800, the final imaged data volume of the target reservoir is determined using the following equation:
A＝A0+∑Ai*Ci
Where A represents the final imaging data volume of the target reservoir, A 0 represents the base imaging data volume of the target reservoir, A i represents the i-th valid imaging data volume of the target reservoir, and C i represents the weighting coefficients of the valid imaging data volumes A i of the target reservoir.
6. An imaging device for a microstructured body, comprising:
the data acquisition module is used for imaging the target reservoir by utilizing different imaging methods to acquire a plurality of initial imaging data volumes of the target reservoir;
The normalization processing module is used for normalizing the amplitude of each initial imaging data body in the plurality of initial imaging data bodies of the target reservoir to obtain a plurality of imaging data bodies of the target reservoir;
The weight calculation module is used for determining one imaging data body from a plurality of imaging data bodies of the target reservoir as a basic imaging data body, and determining a weighting coefficient of each imaging data body of the target reservoir according to a proportional relation between an average value of the seismic amplitude of the micro-structure geologic body in each imaging data body of the target reservoir and an average value of the seismic amplitude of the micro-structure geologic body in the basic imaging data body; the weighting coefficient of the basic imaging data volume of the target reservoir is 1; the microstructure geologic body comprises a bead string, a karst cave, a weak reflection of a small fracture and a small-scale crack, and a microstructure weak reflection and microstructure geologic body;
The imaging processing module is used for carrying out weighted summation on each imaging data body of the target reservoir according to each imaging data body of the target reservoir and the weighting coefficient thereof, determining a final imaging data body of the target reservoir according to the weighted summation result, and imaging the microstructure geologic body of the target reservoir according to the final imaging data body of the target reservoir;
after determining an imaging data volume as a base imaging data volume among the plurality of imaging data volumes of the target reservoir, further comprising:
Selecting a valid imaging data volume from imaging data volumes of a target reservoir other than the base imaging data volume, wherein the valid imaging data volume is one of the imaging data volumes of the target reservoir that is capable of characterizing a structural feature of a micro-geologic formation of the target reservoir;
Determining a weighting coefficient for each imaging data volume of the target reservoir based on a proportional relationship between a mean value of seismic amplitudes of the microstructured bodies in each imaging data volume of the target reservoir and a mean value of seismic amplitudes of the microstructured bodies in the base imaging data volume, comprising:
And determining the weighting coefficient of the effective imaging data volume of the target reservoir according to the proportional relation between the seismic amplitude average value of the micro-structural geologic volume in the effective imaging data volume of the target reservoir and the seismic amplitude average value of the micro-structural geologic volume in the basic imaging data volume.
7. A storage medium storing a computer program which, when executed by a processor, performs the steps of the method of imaging a microstructured body as defined in any one of claims 1-5.
8. A computer device comprising a processor and a storage medium storing program code which, when executed by the processor, performs the steps of the method of imaging a microstructured geological volume of any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010936091.5A CN114427452B (en) | 2020-09-08 | 2020-09-08 | Imaging method, device, storage medium and computer equipment for microstructure geologic body |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010936091.5A CN114427452B (en) | 2020-09-08 | 2020-09-08 | Imaging method, device, storage medium and computer equipment for microstructure geologic body |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114427452A CN114427452A (en) | 2022-05-03 |
| CN114427452B true CN114427452B (en) | 2024-05-03 |
Family
ID=81309968
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010936091.5A Active CN114427452B (en) | 2020-09-08 | 2020-09-08 | Imaging method, device, storage medium and computer equipment for microstructure geologic body |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114427452B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4561074A (en) * | 1982-12-29 | 1985-12-24 | Amoco Corporation | Computationally efficient weighting and vertical stacking methods and apparatus for improving signal-to-noise ratio of seismic data |
| CN1516814A (en) * | 2001-06-16 | 2004-07-28 | ά˹�ض���Ƶ���ع�����˾ | Method of processing data |
| CN102116869A (en) * | 2011-02-12 | 2011-07-06 | 中国石油大学(华东) | High-precision prestack domain least square migration seismic imaging technology |
| CN102426387A (en) * | 2011-09-15 | 2012-04-25 | 中国科学院地理科学与资源研究所 | Seismic scattering wave imaging method |
| CN102788994A (en) * | 2012-07-12 | 2012-11-21 | 恒泰艾普石油天然气技术服务股份有限公司 | Reservoir fracture determining method |
| CN103527184A (en) * | 2013-10-28 | 2014-01-22 | 北京大学 | Method and system for predicting dolomite reservoir |
| CN104730571A (en) * | 2015-03-11 | 2015-06-24 | 中国科学院地质与地球物理研究所 | Method and device for identifying small-scale geologic body through diffraction refocusing |
| WO2016063125A1 (en) * | 2014-10-23 | 2016-04-28 | Cgg Services Sa | Imaging the near subsurface with surface consistent deconvolution operators |
| WO2018129844A1 (en) * | 2017-01-10 | 2018-07-19 | 中国科学院地质与地球物理研究所 | Seismic diffracted wave separation method and device |
| CN108693559A (en) * | 2017-04-05 | 2018-10-23 | 中国石油化工股份有限公司 | Seismic wave joint imaging method and system |
| CN109655883A (en) * | 2017-10-10 | 2019-04-19 | 中国石油化工股份有限公司 | A kind of earthquake dividing method and system for target |
| CN111399048A (en) * | 2020-04-29 | 2020-07-10 | 四川杰瑞泰克科技有限公司 | Method for calculating correlation attribute and data weighted reconstruction of broken solution |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107346035B (en) * | 2017-08-07 | 2020-01-07 | 中国石油天然气股份有限公司 | Method and device for identifying fracture |
-
2020
- 2020-09-08 CN CN202010936091.5A patent/CN114427452B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4561074A (en) * | 1982-12-29 | 1985-12-24 | Amoco Corporation | Computationally efficient weighting and vertical stacking methods and apparatus for improving signal-to-noise ratio of seismic data |
| CN1516814A (en) * | 2001-06-16 | 2004-07-28 | ά˹�ض���Ƶ���ع�����˾ | Method of processing data |
| CN102116869A (en) * | 2011-02-12 | 2011-07-06 | 中国石油大学(华东) | High-precision prestack domain least square migration seismic imaging technology |
| CN102426387A (en) * | 2011-09-15 | 2012-04-25 | 中国科学院地理科学与资源研究所 | Seismic scattering wave imaging method |
| CN102788994A (en) * | 2012-07-12 | 2012-11-21 | 恒泰艾普石油天然气技术服务股份有限公司 | Reservoir fracture determining method |
| CN103527184A (en) * | 2013-10-28 | 2014-01-22 | 北京大学 | Method and system for predicting dolomite reservoir |
| WO2016063125A1 (en) * | 2014-10-23 | 2016-04-28 | Cgg Services Sa | Imaging the near subsurface with surface consistent deconvolution operators |
| CN104730571A (en) * | 2015-03-11 | 2015-06-24 | 中国科学院地质与地球物理研究所 | Method and device for identifying small-scale geologic body through diffraction refocusing |
| WO2018129844A1 (en) * | 2017-01-10 | 2018-07-19 | 中国科学院地质与地球物理研究所 | Seismic diffracted wave separation method and device |
| CN108693559A (en) * | 2017-04-05 | 2018-10-23 | 中国石油化工股份有限公司 | Seismic wave joint imaging method and system |
| CN109655883A (en) * | 2017-10-10 | 2019-04-19 | 中国石油化工股份有限公司 | A kind of earthquake dividing method and system for target |
| CN111399048A (en) * | 2020-04-29 | 2020-07-10 | 四川杰瑞泰克科技有限公司 | Method for calculating correlation attribute and data weighted reconstruction of broken solution |
Non-Patent Citations (1)
| Title |
|---|
| 倾角域逆时偏移绕射波成像方法;汪天池;刘少勇;顾汉明;唐永杰;严哲;石油地球物理勘探(03);第591-597页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114427452A (en) | 2022-05-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Asjad et al. | A new approach for salt dome detection using a 3D multidirectional edge detector | |
| CN110058303B (en) | Acoustic wave anisotropy reverse time migration mixing method | |
| CN105425299B (en) | The method and apparatus for determining formation fracture distribution | |
| CN109655918B (en) | Method and system for determining position of ground shallow well micro-seismic monitoring observation station | |
| WO2018102813A2 (en) | Seismic acquisition geometry full-waveform inversion | |
| Vinard et al. | Localizing microseismic events on field data using a U-Net-based convolutional neural network trained on synthetic data | |
| US11719836B1 (en) | Methods of oil and gas exploration using digital imaging | |
| CN114427452B (en) | Imaging method, device, storage medium and computer equipment for microstructure geologic body | |
| US20230297843A1 (en) | Deep learning method for defect characterization | |
| CN113219531A (en) | Method and device for identifying gas-water distribution of tight sandstone | |
| CN111399055A (en) | Gravel rock mass phase zone description method based on velocity frequency dispersion factor | |
| CN112433248B (en) | Method for detecting hidden reservoir stratum in carbonate rock deposition environment | |
| CN113093274B (en) | Method, device, terminal and storage medium for identifying low-order faults | |
| CN115598700A (en) | Seismic profile imaging method and device, storage medium and electronic equipment | |
| CN113743193A (en) | Pre-stack seismic data linear interference suppression method and system | |
| Du et al. | Research and application of Rayleigh wave extraction method based on microtremors signal analysis | |
| Corradini et al. | Investigating the influence of earthquake source complexity on back-projection images using convolutional neural networks | |
| Yang et al. | Seismic source location with time-reversal and maximum-amplitude path for sparse and small-aperture acquisitions | |
| CN114721044B (en) | Method and system for joint inversion of crust structure by using multi-frequency receiving function and amplitude ratio | |
| CN115616660B (en) | Method and device for monitoring carbon dioxide leakage condition of sea area carbon sealing project by using diffraction waves | |
| CN114114420B (en) | Diffraction identification imaging method, diffraction identification imaging device, electronic equipment and medium | |
| Dai et al. | Study of an Automatic Picking Method for Multimode Dispersion Curves of Surface Waves Based on an Improved U-Net | |
| Zaręba et al. | Some statistical consideration of azimuth and inclination angles determination based on walk-away VSP data in Python | |
| CN112835096B (en) | Gas layer identification method and device | |
| CN114994762A (en) | Sparse domain seismic diffracted wave separation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |