CN110927789A - Method and device for predicting shale plane distribution based on loss data - Google Patents
Method and device for predicting shale plane distribution based on loss data Download PDFInfo
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Abstract
The invention discloses a method and a device for predicting shale plane distribution based on loss data, which can realize accurate prediction of the distribution characteristics of high-quality shale in a shale target layer on a plane, shorten the shale gas exploration period and improve the development efficiency. The method comprises the following steps: inputting two-dimensional seismic data in a target area, and analyzing and determining the control range and the missing degree of the data; cleaning two-dimensional lines in the two-dimensional seismic data, and removing mutually contradictory two-dimensional lines in each layer; calibrating and correcting the two-dimensional seismic data; performing three-dimensional space unified modeling on the corrected two-dimensional seismic data according to the calibrated shale target layer in a three-dimensional modeling mode; performing unified inversion operation on the two-dimensional data according to a three-dimensional inversion mode to obtain a two-dimensional line measurement inversion result of a target area; and extracting a two-dimensional survey line inversion result of a shale target layer according to shale layer position information of the two-dimensional seismic data, and acquiring distribution prediction data of shale thickness.
Description
Technical Field
The invention relates to the technical field of high-quality shale plane distribution prediction, in particular to a method and a device for predicting shale plane distribution based on loss data.
Background
Shale gas is a typical continuous gas reservoir. The shale gas reservoir with the benefit generally has the characteristics of high-quality shale, such as large thickness, moderate burial depth, wide distribution, good gas content and the like. The high-quality shale plane distribution mainly refers to the distribution of the thickness of the high-quality shale.
Seismic inversion is a main means for predicting the planar distribution of high-quality shale. The seismic inversion is based on high-quality logging data and high-resolution seismic data, takes geological and well drilling data as reference, and carries out qualitative or quantitative prediction and evaluation on a target reservoir stratum through inversion operation. The seismic inversion methods are numerous, and the purpose can be achieved only by selecting a proper seismic inversion method according to the technical characteristics of different inversion methods and the characteristics of geological problems to be solved.
The effect of predicting the high-quality shale plane distribution by using seismic inversion depends on the accuracy and quality of available seismic data besides the inversion method and the quantity and quality of well drilling and logging data which can be referred to and used. If the exploration degree of a research area is high, the seismic data acquisition condition is good, three-dimensional data are acquired, the acquisition quality is high, the processing result is good, the prediction of the seismic inversion high-quality shale plane distribution is very favorable, and the high-quality shale plane distribution can be predicted conveniently and reliably. However, in many cases, seismic data in shale gas exploration areas are lacking, only a few two-dimensional seismic lines exist, and the quality of seismic data may be poor due to complex earth surfaces in mountainous areas and the like. How to utilize the data with small quantity, poor quality and lack of deficiency to realize the prediction of the plane distribution of the high-quality shale becomes a key technical problem for shale gas exploration in the areas.
Disclosure of Invention
At least one of the objectives of the present invention is to overcome the problems in the prior art, and provide a method and an apparatus for predicting shale plane distribution based on missing data, which can accurately predict the distribution characteristics of high quality shale in a shale target layer on a plane, shorten the shale gas exploration cycle, and improve the development efficiency. The method is mainly applied to the field of petroleum and natural gas exploration and development, and can also be applied to the geophysical related fields such as mineral resource general survey, engineering geological survey and the like.
In order to achieve the above object, the present invention adopts the following aspects.
A method of predicting shale plane distribution based on loss-of-data, comprising:
inputting two-dimensional seismic data in a target area, and analyzing and determining the control range and the missing degree of the data; cleaning two-dimensional lines in the two-dimensional seismic data, and removing mutually contradictory two-dimensional lines in each layer; calibrating the two-dimensional seismic data, determining shale horizon information, and correcting the horizon according to the attribute along the shale target layer;
performing three-dimensional space unified modeling on the corrected two-dimensional seismic data according to the calibrated shale target layer in a three-dimensional modeling mode; performing unified inversion operation on the two-dimensional data according to a three-dimensional inversion mode to obtain a two-dimensional line measurement inversion result of a target area; and extracting a two-dimensional survey line inversion result of a shale target layer according to shale layer position information of the two-dimensional seismic data, and acquiring distribution prediction data of shale thickness.
Preferably, the two-dimensional seismic data in the target area are irregular two-dimensional seismic acquisition data, and the acquisition accuracy and the acquisition frequency of the two-dimensional seismic acquisition data are smaller than the required threshold.
Preferably, the method comprises: and performing three-dimensional splicing on each section in the two-dimensional seismic data to acquire three-dimensional model data of the target area.
Preferably, the method comprises: two-dimensional line measurement inversion results of the target area are obtained by using seismic inversion software (such as a Jason geoscience platform software system, a Strata two-dimensional/three-dimensional seismic sequence analysis and inversion software package, Interwell multichannel inversion software, ISIS seismic inversion software and the like) and operating seismic inversion algorithms (such as one or more of constrained sparse impulse inversion, post-stack geostatistical inversion using a Markov chain-Monte Carlo algorithm, interactive wave impedance inversion of multiple iterative extrapolation, and fast simulated annealing algorithm).
Preferably, the method comprises: and performing three-dimensional visualization on the two-dimensional line measurement inversion result, and converting the geophysical model into a geological model according to the corresponding relation between physical properties and lithology.
Preferably, the method comprises: and (4) taking the impedance value less than 10600(m/s) × (g/cm3) as a threshold value statistic of the high-quality shale to extract the thickness of the high-quality shale.
Preferably, the variation range of the high-quality shale thickness in the shale thickness distribution prediction data is 10-40 m.
Preferably, the method comprises: and performing plane gridding processing on the two-dimensional prediction result of the shale thickness to correct the shale thickness variation range.
Preferably, the geostatistical inversion algorithm includes: one or more of an acoustic impedance inversion algorithm based on seismic data, a logging property inversion algorithm, a geostatistically based stochastic simulation, and a stochastic inversion algorithm.
An apparatus for predicting shale plane distribution based on delinquent data, comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any of the methods described herein.
In summary, due to the adoption of the technical scheme, the invention at least has the following beneficial effects:
the two-dimensional seismic acquisition data which are irregular and poor in acquisition and processing quality are utilized, the uniform inversion of irregular under-lost seismic data is carried out, the shale plane distribution of a work area is predicted by utilizing the under-lost data inversion result, the distribution characteristic prediction of high-quality shale of a shale target layer on the plane is realized, the evaluation of the shale gas exploration and development potential in a large work area in a short time is facilitated, the resource evaluation, the zone evaluation, the exploration and development and the like of the current shale gas have good effects, the practicability is high, and the application prospect is wide.
Drawings
Fig. 1 is a flowchart of a method for predicting shale plane distribution based on loss-less data according to an exemplary embodiment of the present invention.
Fig. 2 is a two-dimensional line schematic according to an exemplary embodiment of the invention.
Fig. 3 is a schematic structural diagram of an apparatus for predicting shale plane distribution based on loss-less data according to an exemplary embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and embodiments, so that the objects, technical solutions and advantages of the present invention will be more clearly understood. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 illustrates a method for predicting shale plane distribution based on loss-less data according to an exemplary embodiment of the present invention. The method of this embodiment essentially comprises the steps of:
step 101: inputting two-dimensional seismic data in a target area, analyzing and determining the control range and the missing degree of the data
The two-dimensional seismic data in the target area can be irregular two-dimensional seismic acquisition data with poor acquisition and processing quality (for example, the acquisition accuracy and the acquisition frequency are less than a required threshold), and a more accurate shale target layer high-quality shale distribution characteristic prediction result on a plane can still be obtained through the subsequent steps of the method.
Step 102: cleaning two-dimensional lines in two-dimensional seismic data to remove mutually contradictory two-dimensional lines in each layer
As shown in fig. 2, the closed time difference of the offset section is difficult to eliminate, but as a two-dimensional line, most of the work is still completed on an independent two-dimensional line, and the attribute extraction along the shale target layer is also performed on each two-dimensional line, and then the attribute extraction is integrated and gridded into planar data. The two-dimensional line closure time difference therefore does not have a decisive influence on the subsequent operation. But after data with particularly poor quality or inconsistent with the data are cleaned, noise can be reduced, and the prediction accuracy can be improved.
Step 103: calibrating the two-dimensional seismic data, determining shale horizon information, and correcting the horizon according to attributes along the shale target horizon
Step 104: performing three-dimensional space unified modeling on the corrected two-dimensional seismic data according to the calibrated shale target layer in a three-dimensional modeling mode
For example, the individual profiles in the two-dimensional seismic data are three-dimensionally stitched to obtain three-dimensional model data of the target area. Unified modeling through three-dimensional space: the low-frequency model can be well extended on both the near-well two-dimensional line and the far-well two-dimensional line, and the modeling effect is the same as that on the three-dimensional data body.
Step 105: performing unified inversion operation on the two-dimensional data according to the three-dimensional inversion mode to obtain the two-dimensional line measurement inversion result of the target area
For example, seismic inversion software can be adopted, a geostatistical inversion algorithm is operated, the result is visualized in three dimensions, the geophysical model is converted into the geological model according to the corresponding relation between physical properties and lithology, and the obtained inversion result is stable and reliable in the whole region of the target area.
Step 106: extracting a two-dimensional survey line inversion result of a shale target layer according to shale position information of the two-dimensional seismic data, and acquiring distribution prediction data of shale thickness
And (3) counting and extracting the thickness of the high-quality shale by taking the impedance value smaller than 10600(m/s) × (g/cm3) as a threshold value of the high-quality shale, wherein the variation range of the thickness of the high-quality shale is 10-40 m.
The earthquake prediction thickness and the earthquake prediction thickness taking the Dingshan shale No. 1 well and the Dingshan shale No. 2 well as examples are shown in the following table 1.
TABLE 1
| Well name | Dingshan shale No. 1 well | Dingshan shale No. 2 well |
| Earthquake prediction thickness (m) | 23.9 | 28.5 |
| Well logging dividing thickness (m) | 22.61 | 28.1 |
| Prediction error | 5.7％ | 1.4％ |
Furthermore, the two-dimensional prediction result of the shale thickness can be subjected to plane gridding processing to correct the variation range of the shale thickness, so that the accuracy of the prediction result of the high-quality shale plane distribution is improved.
Fig. 3 illustrates an apparatus for predicting shale plane distribution based on loss-of-interest data, namely an electronic device 310 (e.g., a computer server with program execution functionality) including at least one processor 311, a power source 314, and a memory 312 and an input-output interface 313 communicatively coupled to the at least one processor 311, according to an exemplary embodiment of the present invention; the memory 312 stores instructions executable by the at least one processor 311, the instructions being executable by the at least one processor 311 to enable the at least one processor 311 to perform a method disclosed in any one of the embodiments; the input/output interface 313 may include a display, a keyboard, a mouse, and a USB interface for inputting/outputting data; the power supply 314 is used to provide power to the electronic device 310.
Those skilled in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
When the integrated unit of the present invention is implemented in the form of a software functional unit and sold or used as a separate product, it may also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The foregoing is merely a detailed description of specific embodiments of the invention and is not intended to limit the invention. Various alterations, modifications and improvements will occur to those skilled in the art without departing from the spirit and scope of the invention.
Claims (10)
1. A method for predicting shale plane distribution based on loss data, the method comprising:
inputting two-dimensional seismic data in a target area, and analyzing and determining the control range and the missing degree of the data; cleaning two-dimensional lines in the two-dimensional seismic data, and removing mutually contradictory two-dimensional lines in each layer; calibrating the two-dimensional seismic data, determining shale horizon information, and correcting the horizon according to the attribute along the shale target layer;
performing three-dimensional space unified modeling on the corrected two-dimensional seismic data according to the calibrated shale target layer in a three-dimensional modeling mode; performing unified inversion operation on the two-dimensional data according to a three-dimensional inversion mode to obtain a two-dimensional line measurement inversion result of a target area; and extracting a two-dimensional survey line inversion result of a shale target layer according to shale layer position information of the two-dimensional seismic data, and acquiring distribution prediction data of shale thickness.
2. The method of claim 1, wherein the two-dimensional seismic data within the target area is irregular and the acquisition accuracy and acquisition frequency are less than a desired threshold for the two-dimensional seismic acquisition data.
3. The method according to claim 1, characterized in that it comprises: and performing three-dimensional splicing on each section in the two-dimensional seismic data to acquire three-dimensional model data of the target area.
4. The method according to claim 1, characterized in that it comprises: and acquiring a two-dimensional line measurement inversion result of the target area by adopting seismic inversion software and operating a seismic inversion algorithm.
5. The method of claim 4, wherein the method comprises: and performing three-dimensional visualization on the two-dimensional line measurement inversion result, and converting the geophysical model into a geological model according to the corresponding relation between physical properties and lithology.
6. The method according to claim 1, characterized in that it comprises: the impedance value is less than 10600(m/s) × (g/cm)3) Extracting high quality shale thickness as threshold statistics of high quality shale。
7. The method according to claim 6, wherein the variation range of the high-quality shale thickness in the distribution prediction data of the shale thickness is 10-40 m.
8. The method according to any one of claims 1 to 7, characterized in that it comprises: and performing plane gridding processing on the two-dimensional prediction result of the shale thickness to correct the shale thickness variation range.
9. The method according to any one of claims 1 to 7, wherein the unified inversion operation employs: one or more of an acoustic impedance inversion algorithm based on seismic data, a logging property inversion algorithm, a geostatistically based stochastic simulation, and a stochastic inversion algorithm.
10. An apparatus for predicting shale plane distribution based on delinquent data, comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 9.
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| BE1030856B1 (en) * | 2023-05-18 | 2024-07-23 | China Univ Of Geosciences Beijing | METHODS, DEVICES AND APPARATUS FOR PROCESSING ANOMALIC DATA IN AN ASSESSMENT OF RESOURCE RESERVES |
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