CN113970786B

CN113970786B - Method and system for predicting thickness of underground river, storage medium and electronic equipment

Info

Publication number: CN113970786B
Application number: CN202010711347.2A
Authority: CN
Inventors: 吕慧; 孙振涛; 马灵伟; 胡华锋; 李子锋
Original assignee: China Petroleum and Chemical Corp; Sinopec Geophysical Research Institute
Current assignee: China Petroleum and Chemical Corp; Sinopec Geophysical Research Institute
Priority date: 2020-07-22
Filing date: 2020-07-22
Publication date: 2024-07-09
Anticipated expiration: 2040-07-22
Also published as: CN113970786A

Abstract

The invention discloses a method, a system, a storage medium and electronic equipment for predicting the thickness of a hidden river, and relates to the technical field of geological exploration, wherein the method comprises the following steps: acquiring a frequency attenuation gradient plan of the hidden river in a development layer section thereof; and obtaining a river development map marked with the river development thickness by marking the corresponding river development thickness on each frequency attenuation gradient in the frequency attenuation gradient plan based on the fitting relation between the frequency attenuation gradient and the river development thickness, so as to analyze the favorable development area of the reservoir body according to the river development map. The beneficial effects of the invention are as follows: the method can realize the conversion from geophysical attribute abnormality to geological abnormality, improves the prediction precision of the ancient buried river reservoir body, and provides powerful technical support for guiding the exploration and development of the deep carbonate reservoir, so that researchers can select the setting position of drilling according to the buried river spreading chart marked with the development thickness of the buried river, improve the oil gas development efficiency and save the exploration cost.

Description

Method and system for predicting thickness of underground river, storage medium and electronic equipment

Technical Field

The invention belongs to the technical field of geological exploration, and particularly relates to a method and a system for predicting the thickness of a river, a storage medium and electronic equipment.

Background

The domestic research on the karst ancient river is mainly focused on the northwest region, and the main research results are focused on the geophysical recognition method of the karst ancient river. The recognition research on the ancient river shows that the earthquake characteristics of the underground river are strong reflection characteristics along the trend of the river, and the transverse continuity is good; in the vertical run of the river, predominantly beaded reflective features, there are relatively weak reflections exhibited by the partial area beaded features being unobvious. The main river of the river has strong energy in various attribute planes and spaces, good continuity and large extension length, and the branch river has weak energy and poor continuity.

Based on the karst cave type reservoir identified by the well points, the corresponding relation between the ancient buried river reservoir and the seismic reflection characteristic can be established through well earthquake calibration. However, for quantitative representation of actual thickness of the hidden river, differences exist between seismic anomalies and geological anomalies represented by the thickness of the hidden river due to the influence of seismic resolution, so that the representation of the development thickness of the hidden river is inaccurate. Therefore, a set of rapid and practical method technology is urgently needed to be established in geological exploration and development, quantitative characterization of the development thickness of the hidden river is achieved, the development scale prediction precision of the hidden river reservoir is improved, and powerful technical support is provided for fine development and increased storage and up-production of the carbonate rock ancient hidden river reservoir in the oil field.

Disclosure of Invention

The invention provides a method, a system, a storage medium and electronic equipment for predicting the thickness of a hidden river, which are based on the technical problems that the thickness characterization of the developed thickness of the hidden river is inaccurate due to the fact that the thickness of the hidden river is different between seismic anomaly and geological anomaly represented by the thickness of the hidden river due to the influence of seismic resolution.

In a first aspect, an embodiment of the present invention provides a method for predicting a thickness of a river, including:

acquiring a frequency attenuation gradient plan of the hidden river in a development layer section thereof;

And obtaining a river development map marked with the river development thickness by marking the corresponding river development thickness on each frequency attenuation gradient in the frequency attenuation gradient plan based on the fitting relation between the frequency attenuation gradient and the river development thickness, so as to analyze the favorable development area of the reservoir body according to the river development map.

Optionally, a fitting relationship between the frequency attenuation gradient and the developed thickness of the river is obtained in advance by:

Acquiring logging data of all logging of the underground river, and obtaining frequency attenuation gradient corresponding to a development interval of the underground river where all logging is located;

determining the development thickness of the river in the river area where the well logging is positioned according to the well logging information;

and fitting each frequency attenuation gradient with the data set of the development thickness of the river corresponding to each frequency attenuation gradient to obtain a fitting relation between the frequency attenuation gradient and the development thickness of the river.

Optionally, obtaining a frequency attenuation gradient plan of the hidden river in the development interval thereof comprises:

Acquiring post-stack seismic data of the hidden river region;

performing time-frequency analysis on the post-stack seismic data to extract each divided frequency-divided energy data volume from the stacked seismic data;

extracting a frequency attenuation gradient based on the frequency division energy data body to obtain a frequency attenuation gradient attribute body of the hidden river region;

and extracting the frequency attenuation gradient in the time window of the development interval of the hidden river from the frequency attenuation gradient attribute body to obtain a frequency attenuation gradient plan view of the hidden river in the development interval of the hidden river.

Optionally, performing time-frequency analysis on the post-stack seismic data to extract each divided energy data volume from the stacked seismic data, including:

And performing time-frequency analysis on the post-stack seismic data by using a matching pursuit algorithm to extract each frequency-divided energy data volume from the stacked seismic data.

Optionally, extracting a frequency attenuation gradient based on the divided energy data volume to obtain a frequency attenuation gradient attribute volume of the river region, including:

Fitting the energy and the frequency corresponding to each frequency division in the frequency division energy data body by using a preset fitting calculation formula to obtain the frequency attenuation gradient corresponding to each frequency division, thereby obtaining a frequency attenuation gradient attribute body of the hidden river region;

wherein the fitting equation is:

y＝a*x+b

Wherein y represents energy corresponding to frequency division, x represents frequency of frequency division, a represents frequency attenuation gradient, and b represents fitting constant.

Optionally, fitting the energy and the frequency corresponding to each frequency division in the frequency division energy data body by using a preset fitting calculation method to obtain a frequency attenuation gradient corresponding to each frequency division, including:

and fitting the energy in the interval from 65% of total energy of each frequency division to 85% of total energy of the frequency division in the frequency division energy data body and the frequency corresponding to the interval by using a preset fitting calculation formula to obtain the frequency attenuation gradient corresponding to each frequency division.

In a second aspect, an embodiment of the present invention further provides a system for predicting a thickness of a river, including:

The acquisition module is used for acquiring a frequency attenuation gradient plan of the hidden river in the development interval of the hidden river;

And the thickness marking module is used for marking the corresponding development thickness of the river on each frequency attenuation gradient in the frequency attenuation gradient plan based on the fitting relation between the frequency attenuation gradient and the development thickness of the river, so as to obtain a development diagram of the river marked with the development thickness of the river, and analyze the favorable development area of the reservoir body according to the development diagram of the river.

Optionally, the thickness marking module includes:

the logging data acquisition unit is used for acquiring logging data of all logging of the underground river and frequency attenuation gradients corresponding to development intervals of the underground river where all logging is located;

The underground river development thickness determining unit is used for determining the underground river development thickness of an underground river area where the logging is located according to the logging information;

And the fitting relation determining unit is used for fitting each frequency attenuation gradient with the data set of the corresponding development thickness of the hidden river to obtain the fitting relation between the frequency attenuation gradient and the development thickness of the hidden river.

Optionally, the acquiring module includes:

the post-stack seismic data acquisition unit is used for acquiring post-stack seismic data of the river region;

The frequency division energy extraction unit is used for carrying out time-frequency analysis on the post-stack seismic data so as to extract each frequency division energy data body from the superimposed seismic data;

the frequency attenuation gradient extraction unit is used for extracting a frequency attenuation gradient based on the frequency division energy data volume and obtaining a frequency attenuation gradient attribute volume of the river region;

and the frequency attenuation gradient plan obtaining unit is used for extracting the frequency attenuation gradient in the time window of the development interval of the hidden river from the frequency attenuation gradient attribute body to obtain the frequency attenuation gradient plan of the hidden river in the development interval of the hidden river.

Optionally, the frequency division energy extraction unit is specifically configured to perform time-frequency analysis on the post-stack seismic data by using a matching pursuit algorithm, so as to extract each frequency division energy data volume from the stacked seismic data.

Optionally, the frequency attenuation gradient extracting unit is specifically configured to fit energy and frequency corresponding to each frequency division in the frequency division energy data body by using a preset fitting calculation, so as to obtain a frequency attenuation gradient corresponding to each frequency division, thereby obtaining a frequency attenuation gradient attribute body of the hidden river area;

wherein the fitting equation is:

y＝a*x+b

Optionally, the frequency attenuation gradient extracting unit is specifically configured to fit, by using a preset fit calculation formula, energy in a range from 65% of total energy of the frequency division to 85% of total energy of each frequency division in the frequency division energy data body and a frequency corresponding to the range, so as to obtain a frequency attenuation gradient corresponding to each frequency division.

In a third aspect, an embodiment of the present invention further provides a storage medium having program code stored thereon, where the program code, when executed by a processor, implements the method for predicting thickness of a river according to any one of the above embodiments.

In a fourth aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes a memory and a processor, where the memory stores program code that can be executed on the processor, and the program code is executed by the processor, to implement the method for predicting thickness of an underground river according to any one of the foregoing embodiments.

According to the method, the system, the storage medium and the electronic equipment for predicting the thickness of the hidden river, disclosed by the embodiment of the invention, the corresponding hidden river development thickness on each frequency attenuation gradient mark in the plan view of the frequency attenuation gradient of the hidden river is given according to the fitting relation between the frequency attenuation gradient and the development thickness of the hidden river, so that the hidden river development plan marked with the hidden river development thickness can be obtained. Therefore, the method for predicting the thickness of the hidden river provided by the embodiment of the invention can realize the conversion from geophysical attribute abnormality to geological abnormality by carrying out thickness characterization on each area of the hidden river, improves the prediction precision of an ancient hidden river reservoir body, and provides powerful technical support for guiding the exploration and development of a deep carbonate reservoir, so that researchers can select the setting position of drilling according to a hidden river spreading chart marked with the development thickness of the hidden river, improve the oil gas development efficiency and save the exploration cost.

Drawings

The scope of the present disclosure may be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The drawings included herein are:

Fig. 1 is a schematic flow chart of a method for predicting thickness of a river according to an embodiment of the present invention;

FIG. 2 is a schematic diagram showing a plan view of a frequency attenuation gradient according to a first embodiment of the present invention;

FIG. 3 is a schematic diagram showing a fitting of the divided energy to the divided class using a fitting calculation according to an embodiment of the present invention;

FIG. 4 is a schematic diagram showing forward frequency characteristics of different thicknesses of the same characteristics of the river filling according to the first embodiment of the present invention;

FIG. 5 shows a schematic representation of a development pattern of a river marked with developed thickness of the river;

FIG. 6 is a schematic diagram showing a fitting of a frequency attenuation gradient to a data set of the development thickness of the corresponding river according to the first embodiment of the present invention;

FIG. 7 is a schematic diagram showing an analysis of a frequency attenuation gradient plan view and a cross-section view of a river according to an embodiment of the present invention;

FIG. 8 is a schematic diagram showing error analysis of determining the development thickness of the river by using the frequency attenuation gradient according to the first embodiment of the invention;

fig. 9 is a schematic flow chart of a method for predicting thickness of a river according to a second embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the following detailed description of the implementation method of the present invention will be given with reference to the accompanying drawings and examples, by which the technical means are applied to solve the technical problems, and the implementation process for achieving the technical effects can be fully understood and implemented accordingly.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.

Example 1

According to an embodiment of the present invention, a method for predicting a thickness of a river is provided, and fig. 1 shows a schematic flow chart of a method for predicting a thickness of a river according to an embodiment of the present invention, and as shown in fig. 1, the method for predicting a thickness of a river may include: steps 110 to 120.

In step 110, a frequency attenuation gradient plan of the hidden river within its development interval is acquired.

Here, the frequency attenuation gradient plan refers to a plan of frequency attenuation gradients extracted within a development interval of the hidden river, which reflects the frequency attenuation gradients of different areas of the hidden river.

The frequency attenuation gradient refers to that in the geological exploration process, due to the influence of various factors such as stratum absorption, gaps, fluid and the like, the seismic signals often have nonlinear and non-stationary characteristics, namely, the frequency components of the seismic signals change with time.

Fig. 2 shows a schematic diagram of a frequency attenuation gradient plan according to a first embodiment of the present invention, fig. 2 shows a frequency attenuation gradient plan attribute of a river in a development interval of a certain work area, and it can be seen that, in different areas of the river, the frequency attenuation gradient corresponding to the river area can be represented.

Specifically, step 110 may include steps 111 to 114.

In step 111, post-stack seismic data of the subsurface region is acquired.

Here, the seismic wave signals are acquired by the acquisition device to obtain a seismic data volume, and then the seismic data volume is subjected to superposition processing to obtain post-stack seismic data. By processing post-stack seismic data, data reflecting seismic attributes, which are special measures of geometry, kinematic, dynamic and statistical properties of the seismic waves, can be extracted therefrom.

The seismic wave signals are affected by factors such as formation lithology, physical properties and the like in the process of underground formation propagation to generate corresponding changes, and the method is a complex reflection of the comprehensive characteristics of underground reservoirs. Spatial variations in the physical properties of the subsurface formation rock, etc., necessarily result in variations in the characteristics of the seismic reflection wave, which in turn affect the seismic attributes. Particularly when the reservoir contains oil and gas, the seismic response characteristics of the reservoir can be correspondingly changed, and corresponding seismic attributes can also be reflected. The theoretical basis for predicting oil gas by the seismic attribute technology is as follows: the seismic attributes carry information about the subsurface formations, while some form of inherent association must exist between the seismic attributes and the oil and gas properties of the reservoir.

In step 112, time-frequency analysis is performed on the post-stack seismic data to extract individual divided energy data volumes from the stacked seismic data.

Here, the seismic waves are attenuated by the propagation in the subsurface formation by phenomena such as spherical diffusion, medium scattering, absorption of medium viscoelasticity, etc. The time-frequency analysis can reveal how many frequency components are contained in the seismic signals and the change characteristics of different frequency components along with time, and the purpose of detecting the geological structure can be achieved by extracting the seismic wave energy of different frequency components through the time-frequency analysis. In step 112, the post-stack seismic data is subjected to time-frequency analysis, so that each frequency-divided (frequency) frequency-divided energy data volume is extracted, and the frequency-divided energy data volume is used for performing geologic structure analysis.

In a preferred embodiment, the post-stack seismic data may be time-frequency analyzed using a matching pursuit method to extract individual divided energy data volumes from the stacked seismic data.

The matching pursuit is essentially to adaptively decompose the signal into time-frequency atoms which are as consistent as possible with the local hierarchical structure, and obtain the linear combination of the time-frequency distribution of the atoms to obtain the time-frequency expression of the signal.

The flow of the matching pursuit algorithm is as follows:

1) Constructing a complex analysis signal of the signal, and determining an instantaneous envelope and an instantaneous phase of the signal, wherein S (t) =s (t) + jHT (S (t)):

And determining the delay t _j according to the corresponding moment of the instantaneous envelope extremum and the peak-to-valley position, and solving the instantaneous phase theta at the delay (t _j).

2) The instantaneous frequency of the signal is obtained, matching wavelets are constructed near the time delay, and the main frequency corresponding to the wavelet W (t _j,f_j,θ_j) with the highest correlation value which is the best match with the signal is selected as the best main frequency of the matching wavelets.

3) Obtaining coefficients of wavelets based on correlation under the condition of wavelet energy normalization

And subtracting the real part of the matched wavelet which is maximally correlated with the signal from the seismic trace to obtain a residual signal, and recursively iterating the residual signal within a certain threshold range.

4) Calculating a two-dimensional spectrum of the signal, carrying out time-frequency analysis on the matched wavelets with different delays, amplitudes and phases which are decomposed by the signal, and superposing the spectrums of the matched wavelets to obtain the spectrum of the initial signal.

Thus, applying a match-trace based spectral inversion technique on post-stack seismic data can directly extract each divided volume of divided energy data. The essence is to continuously perform spectrum analysis on the seismic traces with a series of hours windows, such as Gaussian hours windows, to obtain the energy of each frequency division in the post-stack seismic data.

In this embodiment, it is preferable to perform time-frequency analysis by using a matching pursuit algorithm sensitive to reservoir thickness, so that a frequency-divided energy data volume with high time-frequency resolution can be extracted from post-stack seismic data. Of course, the matching pursuit algorithm is only an optimal embodiment, and the time-frequency analysis method such as short-time fourier transform, wavelet transform, and generalized S transform may be used.

In step 113, a frequency attenuation gradient attribute volume of the river region is obtained based on the divided energy data volume extracting a frequency attenuation gradient.

Here, the frequency division energy data body includes data information of energy of different single frequencies along with frequency change, and after the frequency division energy data body is obtained based on time-frequency analysis of post-stack seismic data, the attribute of the frequency attenuation gradient is extracted for each frequency division in the frequency division energy data body, so that the attribute of the frequency attenuation gradient of the hidden river region is obtained.

Specifically, step 113 may include:

wherein the fitting equation is:

y＝a*x+b

The fitting essence of the energy and frequency corresponding to each frequency division in the frequency division energy data body is to use least square fitting, and a change rule of each frequency division energy { y _f1,y_f2,…,y_fn } along with the frequency { f1, f2, …, fn } is fitted. Wherein, the fit equation is y=a×x+b. The waveform of each frequency division energy along with the change of frequency is fitted through the fitting calculation formula, so that the frequency attenuation gradient of each frequency division frequency spectrum can be obtained, and the frequency attenuation gradient is the slope of the change of the frequency spectrum waveform.

Specifically, in fitting the energy and the frequency corresponding to each frequency division in the divided energy data volume by using the fitting equation, the energy and the frequency corresponding to the interval in which each frequency division in the divided energy data volume is 65% to 85% of the total energy of the frequency division may be fitted.

Wherein, the energy of each frequency division in the interval of 65% to 85% of the total energy of the frequency division and the frequency corresponding to the interval highlight the gradient of the energy change of the high-frequency part along with the frequency, which can be used for identifying the thickness of the river.

Fig. 3 shows a schematic diagram of fitting the divided energy and the divided class by using a fitting calculation formula according to an embodiment of the present invention, as shown in fig. 3, fitting the divided energy and the frequency actually fits the energy in a section of 65% to 85% of the total energy of the frequency division and the corresponding frequency in the section, so as to obtain an attenuation gradient of the divided energy along with the change of the frequency, thereby obtaining a frequency attenuation gradient.

In step 114, extracting the frequency attenuation gradient in the time window of the development interval of the hidden river from the frequency attenuation gradient attribute body, and obtaining a plane diagram of the frequency attenuation gradient of the hidden river in the development interval of the hidden river.

Here, after the frequency attenuation gradient attribute body of the hidden river region is obtained based on the post-stack seismic data, the frequency attenuation gradient plan view of the hidden river in the development interval thereof is obtained by extracting the frequency attenuation gradient plane attribute based on the target layer down within the hidden river spreading time window.

Thus, by performing time-frequency analysis on each trace of seismic records in post-stack seismic data, the detected maximum energy frequency is taken as an initial attenuation frequency on a time-frequency section, and then the frequencies corresponding to 65% and 85% of the seismic wave energy of the frequency spectrum obtained by the time-frequency section are fitted. In the frequency range, according to the energy value corresponding to the frequency, fitting the frequency and energy attenuation gradient to obtain the frequency division frequency attenuation gradient, which can highlight the change gradient of the high-frequency part energy change along with the frequency.

In step 120, based on the fitting relation between the frequency attenuation gradient and the development thickness of the river, corresponding development thickness of the river is marked on each frequency attenuation gradient in the frequency attenuation gradient plan, and a development map marked with the development thickness of the river is obtained, so that the favorable development area of the reservoir is analyzed according to the development map of the river.

Here, when forward modeling is performed on the characteristics of the same filling characteristics and different thicknesses of the underground river, the inventor finds that the frequency division amplitude of the small-scale underground river gradually increases from low frequency to high frequency, and the frequency division amplitude of the large-scale underground river gradually decreases from low frequency to high frequency, so that the frequency attenuation gradient attribute is not influenced by the bead energy, and a certain fitting relation exists between the frequency attenuation gradient attribute and the thickness of the geologic body, and the attribute of the development thickness of the underground river can be effectively represented.

FIG. 4 is a schematic diagram showing forward frequency characteristics of different thicknesses of the same characteristics of the river filling according to the first embodiment of the present invention, as shown in FIG. 4, it can be seen that the frequency attenuation gradient properties can eliminate the influence of amplitude inconsistency, and for thin layers with a thickness of less than 20 meters, the frequency attenuation gradient from low frequency to high frequency of 60Hz presents positive values; for thick layers greater than 20 meters in thickness, the frequency decay gradient assumes negative values. Through forward modeling, a linear fitting relationship exists between the frequency attenuation gradient attribute and the thickness of the geologic body.

Therefore, according to the linear fitting relation between the frequency attenuation gradient and the development thickness of the river, the corresponding development thickness of the river on each frequency attenuation gradient mark in the frequency attenuation gradient plan can be given, so that the development plan of the river marked with the development thickness of the river is obtained.

FIG. 5 shows a schematic representation of a river spread map marked with river development thickness, as shown in FIG. 5, filled with frequency attenuation gradients of different color patches, such as-0.6, -1.256, -1.934, etc. frequency attenuation gradient values and their corresponding color patches, which in turn represent different thicknesses, such as less than 5m, 10.625m, 16.25m, etc. Fig. 5 illustrates the characteristics of the ancient river thickness distribution identified by the typical unit of the work area based on the frequency gradient property. The color code value is converted into a thickness unit, so that the spreading thickness of the river can be intuitively reflected.

The width change of the river can be measured through the point distance based on the developed river spread after the width correction, and the attribute of the frequency attenuation gradient reflects the thickness of the river, so that the frequency attenuation gradient attribute has the concept of width and the concept of thickness in the developed river spread map after the filling of the ancient river, and the distribution area with large width and thickness of the river represents the large development scale of the river, and the oval frame in figure 5 has large development thickness and large width, thereby being a favorable development area of the ancient river reservoir.

In general, along with the flow of the ancient river from north to south, the scale of the river along the river is increased, the development scale of the middle river at the tortuous position of the river and the intersection position of the branch river and the main river is larger, and the development scale of the river from south is more and is relatively smaller.

Specifically, a fitting relationship between the frequency attenuation gradient and the developed thickness of the river may be obtained in advance by:

step 101, acquiring logging data of all logging of the underground river and frequency attenuation gradients corresponding to development intervals of the underground river where all logging is located;

Step 102, determining the development thickness of the river in the river area where the well logging is located according to the well logging information;

and step 103, fitting each frequency attenuation gradient with the data set of the corresponding development thickness of the hidden river to obtain the fitting relation between the frequency attenuation gradient and the development thickness of the hidden river.

Here, logging is a method of measuring geophysical parameters using geophysical properties such as electrochemical properties, conductive properties, acoustic properties, and radioactivity of a rock formation. The well logging data processing and comprehensive interpretation are to process the well logging data by a computer according to preset geological tasks, and to comprehensively analyze and interpret the geology, logging and development data so as to solve the technical problems of stratum division, evaluation of oil and gas reservoirs and useful reservoirs and other geology and engineering in exploration and development.

Therefore, in step 102, the development thickness of the river in the river region where the logging of the river is performed can be determined by interpreting the logging data according to the logging data of the logging of each river. In practice, the obtained logging data is comprehensively analyzed and interpreted, so that the development thickness of the river in the river area where the logging is located is obtained. This technique can be considered as prior art and will not be described in detail here.

In addition, the frequency attenuation gradient corresponding to the development interval of the hidden river in the area where each well is located is obtained, and the frequency attenuation gradient corresponding to the development interval of the hidden river corresponding to the well is actually obtained. The method for obtaining the frequency attenuation gradient may refer to steps 111 to 114.

In step 103, a least square fitting curve fitting method is used to fit each frequency attenuation gradient and the corresponding data set of the development thickness of the hidden river, so as to obtain a fitting relation between the frequency attenuation gradient and the development thickness of the hidden river.

It is worth to say that, the fitting is performed on each frequency attenuation gradient and the corresponding data set of the development thickness of the hidden river, linear regression fitting or nonlinear regression fitting can be used, and different fitting functions can be used for the development conditions of river reservoirs in different working areas. For example, a linear regression function may be used to fit to a river with a thickness greater than 20 meters.

Fig. 6 shows a schematic diagram of fitting a frequency attenuation gradient and a data set of a corresponding development thickness of a river according to an embodiment of the present invention, where, as shown in fig. 6, a plurality of data sets of the frequency attenuation gradient and the development thickness of the river corresponding to the over-river logging are obtained in a river area of a work area, and the data sets are plotted on a graph, where, an ordinate is the development thickness of the river, a unit is meters, and an abscissa is an absolute value of the frequency attenuation gradient.

It can be seen that the depth of development of the river has a fit relationship with the absolute value of the frequency decay gradient, which is a linear relationship, specifically a positive correlation, and a negative correlation with the frequency decay gradient and the depth of development of the river. Fitting the developed thickness of the river corresponding to the logging of the river passing through the working area and the absolute value of the corresponding frequency attenuation gradient to obtain a fitting relation:

y₁＝9.5568x₁-7.29

where y ₁ represents the developed thickness of the river and x ₁ represents the absolute value of the frequency decay gradient.

Therefore, the fitting relation between the frequency attenuation gradient and the development thickness of the river can be obtained through fitting, and after the value of the frequency attenuation gradient of the river region is obtained, the corresponding development thickness of the river can be marked on the river according to the fitting relation.

Fig. 7 shows an analysis schematic diagram of a frequency attenuation gradient plan view and a cross-well cross-section view of a proposed underground river according to an embodiment of the present invention, wherein a graph a in fig. 7 shows the frequency attenuation gradient plan view of the underground river, b shows the cross-well cross-section view of the frequency attenuation gradient, and c shows a well logging interpretation thickness, i.e. a developed thickness of the underground river measured by well logging of the underground river. As shown in fig. 7, the thickness of the THa well river reservoir is 51 meters, and the frequency attenuation gradient value is a relatively low negative value; the thickness of the reservoir layer of the THb well river channel is thin and is 14 meters, and the corresponding frequency attenuation gradient value is relatively high; verification of a river well further proves that the frequency attenuation gradient can accurately reflect the development characteristics of the thickness of the river.

In addition, fig. 8 shows a schematic diagram of performing error analysis on determining the development thickness of the underground river by using the frequency attenuation gradient according to the first embodiment of the present invention, and as shown in fig. 8, the inventor performs error analysis on determining the development thickness of the underground river by using the frequency attenuation gradient, the correlation coefficient is about 80%, the reliability of thickness prediction is 80%, the prediction error exists, the maximum absolute error is about 20m, the average absolute error is about 10m, the absolute value of the frequency gradient is less than 2, the average absolute error is about 5m, the smaller the thickness is, and the larger the relative error is. Therefore, the frequency attenuation gradient can effectively predict the development thickness of the hidden river. And the method is particularly suitable for predicting the thickness of the underground river with the thickness of more than 20 meters, and has higher accuracy.

In this embodiment, the developed pattern of the river marked with the developed thickness of the river may be obtained by marking the developed thickness of the river corresponding to each frequency attenuation gradient in the plan of the frequency attenuation gradient of the river according to the fitting relation between the frequency attenuation gradient and the developed thickness of the river obtained in advance. Therefore, through thickness characterization of each area of the hidden river, conversion from geophysical attribute abnormality to geological abnormality can be realized, prediction precision of an ancient hidden river reservoir body is improved, powerful technical support is provided for guiding exploration and development of a deep carbonate reservoir, and accordingly researchers can select setting positions of drilling according to a hidden river spread map marked with hidden river development thickness, oil gas development efficiency is improved, and exploration cost is saved.

Example two

On the basis of the foregoing embodiment, the second embodiment of the present invention further provides a method for predicting a thickness of a river, and fig. 9 shows a schematic flow chart of the method for predicting a thickness of a river according to the second embodiment of the present invention, as shown in fig. 9, where the method includes steps 210 to 250.

In step 210, post-stack seismic data for a covered river region is acquired.

In step 220, time-frequency analysis is performed on the post-stack seismic data to extract individual divided energy data volumes from the stacked seismic data.

The flow of the matching pursuit algorithm is as follows:

In step 230, a frequency attenuation gradient attribute volume of the river region is obtained based on the divided energy data volume extracting a frequency attenuation gradient.

Specifically, step 230 may include:

wherein the fitting equation is:

y＝a*x+b

As shown in fig. 3, fitting the divided energy and the frequency is actually fitting the energy in the interval of 65% to 85% of the total energy of the frequency division and the corresponding frequency in the interval, so as to obtain the attenuation gradient of the energy of the frequency division along with the change of the frequency, thereby obtaining the frequency attenuation gradient.

In step 240, extracting the frequency attenuation gradient in the time window of the development interval of the hidden river from the frequency attenuation gradient attribute body, and obtaining a plane diagram of the frequency attenuation gradient of the hidden river in the development interval of the hidden river.

In step 250, based on the fitting relation between the frequency attenuation gradient and the development thickness of the river, corresponding development thickness of the river is marked on each frequency attenuation gradient in the frequency attenuation gradient plan, and a development map marked with the development thickness of the river is obtained, so that the favorable development area of the reservoir is analyzed according to the development map of the river.

As shown in fig. 4, it can be seen that the frequency-decaying gradient properties can eliminate the effect of amplitude non-uniformity, with a positive value for the frequency-decaying gradient from low frequency to high frequency of 60Hz for thin layers less than 20 meters thick; for thick layers greater than 20 meters in thickness, the frequency decay gradient assumes negative values. Through forward modeling, a certain fitting relation exists between the frequency attenuation gradient attribute and the thickness of the geologic body.

Therefore, according to the fitting relation between the frequency attenuation gradient and the development thickness of the river, the corresponding development thickness of the river on each frequency attenuation gradient mark in the frequency attenuation gradient plan can be given, so that the development plan of the river marked with the development thickness of the river is obtained.

As shown in FIG. 5, the river course is filled with frequency attenuation gradients of different color patches, such as-0.6, -1.256, -1.934, etc., and their corresponding color patches, which in turn represent different thicknesses, such as less than 5m, 10.625m, 16.25m, etc. Fig. 5 illustrates the characteristics of the ancient river thickness distribution identified by the typical unit of the work area based on the frequency gradient property. The color code value is converted into a thickness unit, so that the spreading thickness of the river can be intuitively reflected.

Therefore, the developed pattern of the hidden river marked with the developed thickness of the hidden river can be obtained by marking the corresponding developed thickness of the hidden river on each frequency attenuation gradient in the plan view of the frequency attenuation gradient of the hidden river according to the fitting relation between the frequency attenuation gradient and the developed thickness of the hidden river, which is obtained in advance. Therefore, through thickness characterization of each area of the hidden river, conversion from geophysical attribute abnormality to geological abnormality can be realized, prediction precision of an ancient hidden river reservoir body is improved, powerful technical support is provided for guiding exploration and development of a deep carbonate reservoir, and accordingly researchers can select setting positions of drilling according to a hidden river spread map marked with hidden river development thickness, oil gas development efficiency is improved, and exploration cost is saved.

Specifically, prior to step 210, a fitted relationship between the frequency decay gradient and the developed thickness of the underdrain may be obtained in advance by:

step 201, acquiring logging data of each logging passing through the underground river and frequency attenuation gradient corresponding to an underground river development interval where each logging is located;

Step 202, determining the development thickness of the river in the river area where the well logging is located according to the well logging information;

And 203, fitting each frequency attenuation gradient with the data set of the corresponding developed thickness of the hidden river to obtain a fitting relation between the frequency attenuation gradient and the developed thickness of the hidden river.

Therefore, in step 202, the development thickness of the river in the river region where the logging of the river is performed can be determined by interpreting the logging data according to the logging data of the logging of each river. In practice, the obtained logging data is comprehensively analyzed and interpreted, so that the development thickness of the river in the river area where the logging is located is obtained. This technique can be considered as prior art and will not be described in detail here.

In addition, the frequency attenuation gradient corresponding to the development interval of the hidden river in the area where each well is located is obtained, and the frequency attenuation gradient corresponding to the development interval of the hidden river corresponding to the well is actually obtained. The method for obtaining the frequency attenuation gradient may refer to steps 210 to 240.

In step 203, a fitting relationship between the frequency attenuation gradient and the developed thickness of the river is obtained by fitting each of the frequency attenuation gradients to the corresponding data set of the developed thickness of the river.

As shown in fig. 6, a plurality of data sets of frequency attenuation gradients and the development thickness of the river corresponding to the logging of the river are obtained in the river region of the work area, and the data sets are plotted on a graph, wherein the ordinate represents the development thickness of the river, the unit is meters, and the abscissa represents the absolute value of the frequency attenuation gradients.

It can be seen that the developed thickness of the river has a fitting relationship, in particular a positive correlation, with the absolute value of the frequency decay gradient, whereas it has a negative correlation with the frequency decay gradient and the developed thickness of the river. Fitting the developed thickness of the river corresponding to the logging of the river passing through the working area and the absolute value of the corresponding frequency attenuation gradient to obtain a fitting relation:

y₁＝9.5568x₁-7.29

Therefore, the fitting relation between the frequency attenuation gradient and the development thickness of the hidden river can be obtained by fitting the data set through a least square curve method, and the corresponding development thickness of the hidden river can be marked on the hidden river according to the fitting relation after the value of the frequency attenuation gradient of the hidden river area is obtained.

Example III

According to an embodiment of the present invention, there is also provided a system for predicting a thickness of a river, including:

Optionally, the thickness marking module includes:

Optionally, the acquiring module includes:

wherein the fitting equation is:

y＝a*x+b

Specific embodiments of the method for performing the prediction of the thickness of the river based on the above modules are described in detail in the above embodiments, and are not described herein again.

Example IV

According to an embodiment of the present invention, there is also provided a storage medium having stored thereon program code which, when executed by a processor, implements the method for predicting thickness of a covered river according to any one of the above embodiments.

The storage medium may be, for example, flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, server, app application mall, etc.

Example five

According to an embodiment of the present invention, there is further provided an electronic device including a memory and a processor, where the memory stores program code executable on the processor, and when the program code is executed by the processor, the method for predicting thickness of an underground river according to any one of the above embodiments is implemented.

It is to be appreciated that the electronic device can also include an input/output (I/O) interface, as well as a communication component.

Wherein the processor is configured to perform all or part of the steps of the method for predicting thickness of a river as in any one of the embodiments. The memory is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.

The Processor may be an Application SPECIFIC INTEGRATED Circuit (ASIC), a digital signal Processor (DIGITAL SIGNAL Processor, DSP), a digital signal processing device (DIGITAL SIGNAL Processing Device, DSPD), a programmable logic device (Programmable Logic Device, PLD), a field programmable gate array (Field Programmable GATE ARRAY, FPGA), a controller, a microcontroller, a microprocessor or other electronic component implementation for performing the method for predicting thickness of a river according to any of the embodiments.

The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk or optical disk.

The technical scheme of the invention is described in detail by combining the drawings, and the fact that differences exist between earthquake abnormal thickness and geological abnormal thickness represented by the thickness of the hidden river due to the influence of earthquake resolution in the related technology is considered, so that the characterization of the development thickness of the hidden river is inaccurate. The invention provides a method, a system, a storage medium and electronic equipment for predicting the thickness of a river, which can obtain a river display map marked with the development thickness of the river by marking the development thickness of the river corresponding to each frequency attenuation gradient in a plan view of the frequency attenuation gradient of the river according to a fitting relation between the frequency attenuation gradient and the development thickness of the river, which are obtained in advance. Therefore, through thickness characterization of each area of the hidden river, conversion from geophysical attribute abnormality to geological abnormality can be realized, prediction precision of an ancient hidden river reservoir body is improved, powerful technical support is provided for guiding exploration and development of a deep carbonate reservoir, and accordingly researchers can select setting positions of drilling according to a hidden river spread map marked with hidden river development thickness, oil gas development efficiency is improved, and exploration cost is saved.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing an electronic device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Although the embodiments of the present invention are disclosed above, the embodiments are only used for the convenience of understanding the present invention, and are not intended to limit the present invention. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the present disclosure as defined by the appended claims.

Claims

1. The method for predicting the thickness of the hidden river is characterized by comprising the following steps of:

based on a fitting relation between a frequency attenuation gradient and a river development thickness which are obtained in advance, corresponding river development thicknesses on all frequency attenuation gradient marks in the frequency attenuation gradient plan are given, and a river development diagram marked with the river development thickness is obtained, so that an advantageous development area of an accumulator body is analyzed according to the river development diagram;

The fitting relation between the frequency attenuation gradient and the development thickness of the hidden river is obtained in advance through the following steps:

2. The method of claim 1, wherein obtaining a plan of frequency attenuation gradients of the river within its development interval comprises:

Acquiring post-stack seismic data of the hidden river region;

3. The method of claim 2, wherein performing a time-frequency analysis on the post-stack seismic data to extract each divided energy data volume from the stacked seismic data comprises:

4. The method according to claim 2, wherein extracting a frequency attenuation gradient based on the divided energy data volume, obtaining a frequency attenuation gradient attribute volume of the river region, comprises:

wherein the fitting equation is:

y＝a*x+b

5. The method according to claim 4, wherein fitting the energy and the frequency corresponding to each frequency division in the divided energy data volume by using a preset fitting calculation to obtain a frequency attenuation gradient corresponding to each frequency division comprises:

6. A system for predicting thickness of a river, comprising:

The thickness marking module is used for marking the corresponding development thickness of the river on each frequency attenuation gradient in the frequency attenuation gradient plan based on the fitting relation between the frequency attenuation gradient and the development thickness of the river, so as to obtain a development-beneficial area of the river marked with the development thickness of the river, and analyze the reservoir according to the development-beneficial area of the river;

The thickness marking module includes:

7. A storage medium having program code stored thereon, which when executed by a processor, implements the method of predicting a thickness of a river as claimed in any one of claims 1 to 5.

8. An electronic device comprising a memory, a processor, the memory having stored thereon program code executable on the processor, the program code, when executed by the processor, implementing the method of predicting a thickness of a river as claimed in any one of claims 1 to 5.