CN113917530A - Oil gas storage condition evaluation method and device, electronic equipment and medium - Google Patents
Oil gas storage condition evaluation method and device, electronic equipment and medium Download PDFInfo
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Abstract
Disclosed are an oil gas storage condition evaluation method, device, electronic equipment and medium. The method can comprise the following steps: carrying out deconvolution generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal; calculating a seismic quality factor Q; determining the intersection relation between the reservoir section pressure coefficient and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor; and judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor. The invention extracts high-resolution seismic quality factors through deconvolution generalized S transformation, evaluates the oil-gas storage conditions through a relational expression of the quality factors and the pressure coefficients, adopts the seismic data as the driving of the algorithm, has high resolution and precision of the prediction result, and provides reliable reference for optimizing favorable targets of the oil-gas storage evaluation level in the initial exploration stage.
Description
Technical Field
The invention relates to the field of petroleum exploration, in particular to an oil gas storage condition evaluation method, an oil gas storage condition evaluation device, electronic equipment and a medium.
Background
Exploration and development practices show that good storage conditions are the key of high-yield enrichment of oil and gas, and the pressure coefficient is a direct parameter reflecting the storage conditions of the reservoir oil and gas and the richness of the gas content. For stratum pressure prediction, scholars at home and abroad make a great deal of research on abnormal pressure cause mechanisms and calculation methods, and provide various calculation models. At present, seismic data are utilized to develop a main graphical method and a formula method for pressure coefficient prediction, wherein the graphical method comprises an equivalent depth graphical method, a ratio method or a difference method and a gauge method; the formula method comprises an equivalent depth method, an Eaton method, a Stone method, a Fillippone method, a Liuzhen method, a Bowers method, a Martinez method, a Zhang method, an Eberhart-Phillips model method and the like. Of these, the Eaton process and the modified filliptone process are the most widespread and relatively technically mature processes. In practical application, however, the stratum deposition does not conform to a normal compaction theory, a normal compaction trend line is difficult to be accurately solved, and the prediction precision of the Eaton method for developing cracks is low; based on the Fillippone method, pressure prediction is carried out by utilizing a single longitudinal wave velocity, the method is obviously not applicable to a complex construction area, aiming at the problem, the Fillippone formula can be continuously optimized and improved by utilizing the longitudinal wave velocity and the transverse wave velocity through repeated fitting of a pressure coefficient result calculated by the Fillippone and an actual test result, so that a relatively accurate pressure coefficient value is obtained, and a good effect is obtained in the complex construction area.
The method for carrying out preservation evaluation based on pressure coefficient prediction at home and abroad mainly has the following two problems in a comprehensive way:
(1) in practical application, the stratum deposition does not accord with a normal compaction theory, a normal compaction trend line is difficult to be accurately solved, and the prediction precision of the Eaton method for developing cracks is low;
(2) based on the Fillippone method, pressure prediction is carried out by using a single longitudinal wave velocity, the pressure prediction is obviously inapplicable in a complex structure area, and the result is inaccurate when the pressure prediction is used for carrying out storage condition evaluation. The Fillippone formula is optimized and improved, the formula is modified mainly in a mathematical fitting mode, the optimization of the formula depends too much on the number of fitted sampling points, and the prediction precision and the storage condition evaluation precision of the pressure coefficient are low.
Therefore, it is necessary to develop a method, an apparatus, an electronic device, and a medium for evaluating hydrocarbon storage conditions for extracting high-resolution seismic quality factors.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention provides an oil gas storage condition evaluation method, an oil gas storage condition evaluation device, electronic equipment and a medium, which can extract a high-resolution seismic quality factor through deconvolution generalized S transformation, evaluate the oil gas storage condition through a relational expression of the quality factor and a pressure coefficient, and have the advantages that an algorithm mainly takes seismic data as driving, the resolution and the precision of a prediction result are high, and reliable reference is provided for optimizing favorable targets of an oil gas storage evaluation level in the initial exploration stage.
In a first aspect, an embodiment of the present disclosure provides a method for evaluating oil and gas storage conditions, including:
carrying out deconvolution generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal;
calculating a seismic quality factor Q;
determining the intersection relation between the reservoir section pressure coefficient and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor;
and judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor.
Preferably, the performing generalized S-transform time-frequency analysis on the seismic data, and obtaining a deconvolution generalized S-transform amplitude spectrum of the seismic signal comprises:
and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
Preferably, calculating the seismic quality factor Q comprises:
according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes;
gamma calculation through seismic dominant frequency and Gaussian window control parameters1；
By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
Preferably, γ is calculated by formula (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdAnd lambda and p are function time-frequency adjusting parameters for the seismic source main frequency.
Preferably, by the amplitude spectral ratio and the parameter gamma1Determining the seismic quality factor Q comprises:
obtaining a deconvolution generalized S domain Q value extraction formula;
for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
Preferably, the Q value extraction formula is:
preferably, determining the threshold value of the seismic quality factor comprises:
determining a threshold value of a reservoir section pressure coefficient;
and determining a threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
As a specific implementation of the embodiments of the present disclosure,
in a second aspect, an embodiment of the present disclosure further provides an oil and gas storage condition evaluation device, including:
the generalized S transformation module is used for carrying out deconvolution generalized S transformation time-frequency analysis on the seismic data to obtain a deconvolution generalized S transformation amplitude spectrum of the seismic signal;
the calculation module is used for calculating a seismic quality factor Q;
the intersection module is used for determining the intersection relation between the pressure coefficient of the reservoir section and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor;
and the evaluation module is used for judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor.
Preferably, the performing generalized S-transform time-frequency analysis on the seismic data, and obtaining a deconvolution generalized S-transform amplitude spectrum of the seismic signal comprises:
and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
Preferably, calculating the seismic quality factor Q comprises:
according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes;
gamma calculation through seismic dominant frequency and Gaussian window control parameters1；
By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
Preferably, γ is calculated by formula (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdAnd lambda and p are function time-frequency adjusting parameters for the seismic source main frequency.
Preferably, by the amplitude spectral ratio and the parameter gamma1Determining the seismic quality factor Q comprises:
obtaining a deconvolution generalized S domain Q value extraction formula;
for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
Preferably, the Q value extraction formula is:
preferably, determining the threshold value of the seismic quality factor comprises:
determining a threshold value of a reservoir section pressure coefficient;
and determining a threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
a memory storing executable instructions;
a processor executing the executable instructions in the memory to implement the hydrocarbon reserve condition evaluation method.
In a fourth aspect, the disclosed embodiments further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for evaluating hydrocarbon preservation conditions is implemented.
The method and apparatus of the present invention have other features and advantages which will be apparent from or are set forth in detail in the accompanying drawings and the following detailed description, which are incorporated herein, and which together serve to explain certain principles of the invention.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts.
FIG. 1 shows a flow chart of the steps of a hydrocarbon reserve evaluation method according to one embodiment of the present invention.
FIG. 2 illustrates a schematic diagram of a anticline geological model according to one embodiment of the present invention.
FIG. 3 shows a schematic diagram of deconvolution generalized S-domain Q values according to one embodiment of the present invention.
FIG. 4 shows a schematic diagram of seismic quality factors for extracting actual data according to a generalized S-domain method of the prior art.
FIG. 5 shows a schematic diagram of seismic quality factors for extracting actual data based on deconvolution generalized S-transforms, according to one embodiment of the invention.
FIG. 6 is a schematic diagram illustrating a plot of the intersection of the pressure coefficient and Q-value of a drilled shale gas formation, according to an embodiment of the present invention.
Fig. 7 shows a schematic diagram of a shale gas preservation condition comprehensive evaluation chart according to an embodiment of the invention.
FIG. 8 illustrates a block diagram of an hydrocarbon reserve condition evaluation device, according to an embodiment of the present invention.
Description of reference numerals:
201. a generalized S transform module; 202. a calculation module; 203. a convergence module; 204. and an evaluation module.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein.
The invention provides an oil gas storage condition evaluation method, which comprises the following steps:
carrying out deconvolution generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal; in one example, performing a generalized S-transform time-frequency analysis on the seismic data, obtaining a deconvolved generalized S-transform amplitude spectrum of the seismic signal comprises: and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
Specifically, seismic data generalized S-transform time-frequency analysis is carried out, Wegener distribution of a generalized S-transform spectrum is combined with a Lucy-Richardson deconvolution algorithm, cross term interference caused by the Wegener distribution is suppressed through iterative operation, and a time-frequency analysis result with high resolution and time-frequency focusing performance is obtained.
Aiming at the generalized S transformation applied to the seismic data, the seismic data time-frequency analysis is carried out, and the formula is as follows:
where u (t) is the seismic signal in the time domain, and h (t- τ, f) is a Gaussian window function defined as:
in the above formula, τ is the time position corresponding to the frequency f by the Gaussian window function, and i is the imaginary unit.
The Weigner distribution is used as a nonlinear time frequency analysis method, has higher resolution and time frequency focusing property, and the Weigner distribution of the generalized S transform spectrum of the seismic signal u (t) is as follows:
on the basis, according to the Lucy-Richardson deconvolution algorithm, the optimal original signal time-frequency distribution is obtained through iterative operation, and cross term interference caused by Weigand distribution is suppressed. The expression of the Lucy-Richardson deconvolution algorithm is:
in the formula, Wu(k) For the result of the kth iteration of the Wegener distribution of the seismic signal u (t), WhFor the wigner distribution of its window function h (t, f), the superscript "-" indicates the last iteration result, k is the number of iterations, x is the correlation operator,
for the two-bit convolution operator, the initial boundary condition of equation (6) is:
since | GST (τ, f) & gtis non-luminous>And 0, so τ is t. Optimal result W obtained by several iterationsu(t, f) is the deconvolution generalized S transform amplitude spectrum DGST (t, f) of the seismic signal u (t).
Calculating a seismic quality factor Q; in one example, calculating the seismic quality factor Q includes: according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes; gamma calculation through seismic dominant frequency and Gaussian window control parameters1(ii) a By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
In one example, γ is calculated by equation (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdThe parameters are adjusted for the seismic source main frequency, and lambda and p are functions, so that the Gaussian window can change according to the transformation of different frequency components of the actual non-stationary signal.
In one example, the amplitude spectrum ratio is compared with a parameter gamma1Determining the seismic quality factor Q comprises: obtaining a deconvolution generalized S domain Q value extraction formula; for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
In one example, the Q value extraction formula is:
specifically, the seismic quality factor is usually obtained by a log-spectral ratio method, and the amplitude spectrum is transformed according to the deconvolution generalized S of the seismic signal and aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Is logarithmically compared to obtain the amplitude of Q and Q2The analytical formula (2) is formula (7):
wherein S (f) is the logarithmic ratio of deconvolution generalized S transform amplitude spectrum of the seismic signal, P is amplitude energy independent of seismic frequency, and gamma1In order to be the formula (1),
due to the fact that
And then obtaining the Q value of the deconvolution generalized S domain, wherein the extraction formula is shown as a formula (2). For amplitude spectral ratio and parameter gamma1And performing linear fitting, and according to a Q value extraction formula, obtaining the reciprocal of the slope of the fitted straight line as the Q value.
Determining the intersection relation between the reservoir section pressure coefficient and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor; in one example, determining the threshold value for the seismic quality factor includes: determining a threshold value of a reservoir section pressure coefficient; and determining the threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
And judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor, wherein if the calculated seismic quality factor is smaller than the threshold value, the oil gas storage condition is good, otherwise, the oil gas storage condition is bad.
The invention also provides an oil gas preservation condition evaluation device, which comprises:
the generalized S transformation module is used for carrying out deconvolution generalized S transformation time-frequency analysis on the seismic data to obtain a deconvolution generalized S transformation amplitude spectrum of the seismic signal; in one example, performing a generalized S-transform time-frequency analysis on the seismic data, obtaining a deconvolved generalized S-transform amplitude spectrum of the seismic signal comprises: and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
Specifically, seismic data generalized S-transform time-frequency analysis is carried out, Wegener distribution of a generalized S-transform spectrum is combined with a Lucy-Richardson deconvolution algorithm, cross term interference caused by the Wegener distribution is suppressed through iterative operation, and a time-frequency analysis result with high resolution and time-frequency focusing performance is obtained.
Aiming at the generalized S transformation applied to the seismic data, the seismic data time-frequency analysis is carried out, and the formula is as follows:
where u (t) is the seismic signal in the time domain, and h (t- τ, f) is a Gaussian window function defined as:
in the above formula, τ is the time position corresponding to the frequency f by the Gaussian window function, and i is the imaginary unit.
The Weigner distribution is used as a nonlinear time frequency analysis method, has higher resolution and time frequency focusing property, and the Weigner distribution of the generalized S transform spectrum of the seismic signal u (t) is as follows:
on the basis, according to the Lucy-Richardson deconvolution algorithm, the optimal original signal time-frequency distribution is obtained through iterative operation, and cross term interference caused by Weigand distribution is suppressed. The expression of the Lucy-Richardson deconvolution algorithm is:
in the formula, Wu(k) For the result of the kth iteration of the Wegener distribution of the seismic signal u (t), WhFor the wigner distribution of its window function h (t, f), the superscript "-" indicates the last iteration result, k is the number of iterations, x is the correlation operator,
for the two-bit convolution operator, the initial boundary condition of equation (6) is:
since | GST (τ, f) & gtis non-luminous>And 0, so τ is t. Optimal result W obtained by several iterationsu(t, f) is the deconvolution generalized S transform amplitude spectrum DGST (t, f) of the seismic signal u (t).
The calculation module is used for calculating a seismic quality factor Q; in one example, calculating the seismic quality factor Q includes: according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes; gamma calculation through seismic dominant frequency and Gaussian window control parameters1(ii) a By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
In one example, γ is calculated by equation (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdThe parameters are adjusted for the seismic source main frequency, and lambda and p are functions, so that the Gaussian window can change according to the transformation of different frequency components of the actual non-stationary signal.
In one example, the amplitude spectrum ratio is compared with a parameter gamma1Determining the seismic quality factor Q comprises: obtaining a deconvolution generalized S domain Q value extraction formula; for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
In one example, the Q value extraction formula is:
specifically, the seismic quality factor is usually obtained by a log-spectral ratio method, and the amplitude spectrum is transformed according to the deconvolution generalized S of the seismic signal and aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Is logarithmically compared to obtain the amplitude of Q and Q2The analytical formula (2) is formula (7):
wherein S (f) is the logarithmic ratio of deconvolution generalized S transform amplitude spectrum of the seismic signal, P is amplitude energy independent of seismic frequency, and gamma1In order to be the formula (1),
due to the fact that
And then obtaining the Q value of the deconvolution generalized S domain, wherein the extraction formula is shown as a formula (2). For amplitude spectral ratio and parameter gamma1And performing linear fitting, and according to a Q value extraction formula, obtaining the reciprocal of the slope of the fitted straight line as the Q value.
The intersection module is used for determining the intersection relation between the pressure coefficient of the reservoir section and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor; in one example, determining the threshold value for the seismic quality factor includes: determining a threshold value of a reservoir section pressure coefficient; and determining the threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
And the evaluation module is used for judging whether the oil-gas storage condition is good or bad according to the threshold value of the seismic quality factor, if the calculated seismic quality factor is smaller than the threshold value, the oil-gas storage condition is better, otherwise, the oil-gas storage condition is poorer.
The present invention also provides an electronic device, comprising: a memory storing executable instructions; and the processor runs the executable instructions in the memory to realize the oil and gas conservation condition evaluation method.
The present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described hydrocarbon saving condition evaluation method.
To facilitate understanding of the scheme of the embodiments of the present invention and the effects thereof, four specific application examples are given below. It will be understood by those skilled in the art that this example is merely for the purpose of facilitating an understanding of the present invention and that any specific details thereof are not intended to limit the invention in any way.
Example 1
FIG. 1 shows a flow chart of the steps of a hydrocarbon reserve evaluation method according to one embodiment of the present invention.
As shown in fig. 1, the hydrocarbon conservation condition evaluation method includes: step 101, performing deconvolution generalized S transform time-frequency analysis on seismic data to obtain a deconvolution generalized S transform amplitude spectrum of a seismic signal; step 102, calculating a seismic quality factor Q; 103, determining the intersection relation between the reservoir section pressure coefficient and the seismic quality factor based on the drilled well result, and further determining the threshold value of the seismic quality factor; and 104, judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor.
FIG. 2 illustrates a schematic diagram of a anticline geological model according to one embodiment of the present invention.
The rationality of the method provided by the invention is verified according to the anticline geological model established in figure 2. The basic parameters of the model are set according to the main marker layer sections of the marine facies shale gas in the Sichuan basin. Wherein, the anticline shaft part is provided with a low-speed gas-containing reservoir with the maximum thickness of 50 meters, the Q value of the reservoir is defined as 30, and the Q values of the top plate and the bottom plate of the reservoir are respectively set as 50 and 40.
FIG. 3 shows a schematic diagram of deconvolution generalized S-domain Q values according to one embodiment of the present invention. The result shows that the Q value extracted from the bottom boundary of the reservoir is reasonable and accurate, the relative relation between the Q values of the top and bottom plates is consistent with the model setting, the section recording resolution is obviously higher, and the rationality of the method for extracting the Q value of the thin reservoir is verified.
FIG. 4 shows a schematic diagram of seismic quality factors for extracting actual data according to a generalized S-domain method of the prior art.
The results in the figure show that the excellent shale sections of the reservoir system in the test area have obvious low Q value abnormality and are continuously distributed in the transverse direction, but the Q value is increased to a certain extent at a position above a DY5 well slope fold zone, namely a DY3 well zone at the top of a nasal structure, along with the shallow burial depth. Because the deposition of the shale rich in organic substances in the region D is stable, and the lithological change is small, the influence of the lithological change on the seismic quality factor is considered to be negligible, and the low Q value abnormality is considered to reflect the gas content of the reservoir. However, the extracted Q-value is lower in resolution both longitudinally and laterally due to the influence of the seismic resolution and the generalized S-transform window function. In the longitudinal direction, the Q value extraction result of the generalized S domain can basically reflect the distribution of high-quality shale in a target layer, but the shale with the low TOC on the top plate does not show reasonable medium-low Q value response and has little integral difference with a stone cowshed group; in addition, the difference of the Q values of the top shallow-buried normal pressure area and the shaft deep-buried high pressure area of the nose-shaped structure is relatively small in the transverse direction, so that the change of the shale gas air-entrapping property along with the influence of the formation pressure and the storage condition cannot be intuitively reflected.
FIG. 5 shows a schematic diagram of seismic quality factors for extracting actual data based on deconvolution generalized S-transforms, according to one embodiment of the invention.
The high resolution seismic quality factor exhibits more significant variability in the longitudinal direction. The actual drilling shows that the DY2 well has the best gas content and the highest pressure coefficient, the DY5 well is the next time, and the DY3 well is relatively poor. The Q value of the Longmaxi group to the Taurus hurdle group gradually rises, because the mud content of the Longmaxi group is higher than that of the Taurus hurdle group, the reasonable response of 'high mud content and low Q value' is shown, and the longitudinal direction of the response is consistent with the real rock drilling performance; compared with the Longmaxi section and the Longmaxi section, the Longmaxi section with high quality shale development has lower Q value, and shows that the Q values caused by gas content difference are different under the condition that the lithological difference between the Longmaxi section and the Longmaxi section is relatively small, namely the high gas content and the low Q value; in addition, as the buried depth becomes shallower, the DY3 well region closer to the qieyueshan region has a significantly increased Q value, and the gas-containing property is deteriorated as a whole under the conditions of stable transverse deposition and small lithological change, and the storage conditions are general, and the predicted result is well matched with the actual drilling.
FIG. 6 is a schematic diagram illustrating a plot of the intersection of the pressure coefficient and Q-value of a drilled shale gas formation, according to an embodiment of the present invention.
As the southeast area of the Chuandong undergoes multi-stage tectonic movement, the formed large-scale fracture plays an important control role in the preservation of shale gas, and meanwhile, the abnormal seismic quality factor caused by stratum fracture at the developing micro-fracture part can also reflect the transverse change of the gas content. In order to evaluate the shale gas storage conditions of the D region from the aspect of gas content, the intersection relation of the pressure coefficient, the gas content and the Q value of the reservoir section is analyzed on the basis of the drilled well result, and the seismic quality factor is considered to be in a region within 18.
Fig. 7 shows a schematic diagram of a shale gas preservation condition comprehensive evaluation chart according to an embodiment of the invention.
And (3) judging that the region is an oil gas storage condition favorable region when the corresponding formation pressure coefficient is more than 1.2, dividing the storage condition favorable region into three types by taking the burial depths of 4000 meters, 4500 meters and 5000 meters as boundaries, and finally obtaining a comprehensive evaluation chart of the marine phase shale gas storage conditions in the D region, wherein the comprehensive evaluation chart is shown in fig. 7.
Example 2
FIG. 8 illustrates a block diagram of an hydrocarbon reserve condition evaluation device, according to an embodiment of the present invention.
As shown in fig. 8, the hydrocarbon conservation condition evaluation device includes:
the generalized S transform module 201 is used for carrying out deconvolution generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal;
a calculation module 202 for calculating a seismic quality factor Q;
the intersection module 203 determines the intersection relation between the reservoir section pressure coefficient and the seismic quality factor based on the drilled well result, and further determines the threshold value of the seismic quality factor;
and the evaluation module 204 judges whether the oil and gas storage condition is good or bad according to the threshold value of the seismic quality factor.
As an alternative, the performing generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal includes:
and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
Alternatively, calculating the seismic quality factor Q comprises:
according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes;
gamma calculation through seismic dominant frequency and Gaussian window control parameters1；
By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
Alternatively, γ is calculated by formula (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdAnd lambda and p are function time-frequency adjusting parameters for the seismic source main frequency.
Alternatively, by the amplitude spectrum ratio and the parameter gamma1Determining the seismic quality factor Q comprises:
obtaining a deconvolution generalized S domain Q value extraction formula;
for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
Alternatively, the Q value extraction formula is:
alternatively, determining the threshold value of the seismic quality factor comprises:
determining a threshold value of a reservoir section pressure coefficient;
and determining the threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
Example 3
The present disclosure provides an electronic device including: a memory storing executable instructions; and the processor runs the executable instructions in the memory to realize the oil and gas storage condition evaluation method.
An electronic device according to an embodiment of the present disclosure includes a memory and a processor.
The memory is to store non-transitory computer readable instructions. In particular, the memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the disclosure, the processor is configured to execute the computer readable instructions stored in the memory.
Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus, an interface, and the like, and these well-known structures should also be included in the protection scope of the present disclosure.
For the detailed description of the present embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, which are not repeated herein.
Example 4
The disclosed embodiments provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the hydrocarbon storage condition evaluation method.
A computer-readable storage medium according to an embodiment of the present disclosure has non-transitory computer-readable instructions stored thereon. The non-transitory computer readable instructions, when executed by a processor, perform all or a portion of the steps of the methods of the embodiments of the disclosure previously described.
The computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or removable disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROMs (e.g., ROM cartridges).
It will be appreciated by persons skilled in the art that the above description of embodiments of the invention is intended only to illustrate the benefits of embodiments of the invention and is not intended to limit embodiments of the invention to any examples given.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (10)
1. An oil and gas storage condition evaluation method is characterized by comprising the following steps:
carrying out deconvolution generalized S transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S transform amplitude spectrum of the seismic signal;
calculating a seismic quality factor Q;
determining the intersection relation between the reservoir section pressure coefficient and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor;
and judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor.
2. The hydrocarbon conservation condition evaluation method of claim 1, wherein performing generalized S-transform time-frequency analysis on the seismic data to obtain a deconvolution generalized S-transform amplitude spectrum of the seismic signal comprises:
and aiming at the seismic data, obtaining a deconvolution generalized S transformation amplitude spectrum of the seismic signal through Weiganan distribution of the generalized S transformation spectrum and a Lucy-Richardson deconvolution algorithm.
3. The hydrocarbon preservation condition evaluation method of claim 1, wherein calculating the seismic quality factor Q comprises:
according to the deconvolution generalized S transformation amplitude spectrum of the seismic signal, aiming at the corresponding time t of the top and the bottom of the reservoir1、t2Making logarithmic ratio of the amplitudes;
gamma calculation through seismic dominant frequency and Gaussian window control parameters1；
By amplitude spectral ratio and parameter gamma1And determining the seismic quality factor Q.
4. The hydrocarbon preservation condition evaluation method of claim 3, wherein γ is calculated by formula (1)1：
Where f is the seismic frequency, and Δ t ═ t2-t1，t1、t2Respectively the seismic reflection time corresponding to the top and bottom of the reservoir, m is the seismic source bandwidth parameter, fdAnd lambda and p are function time-frequency adjusting parameters for the seismic source main frequency.
5. The hydrocarbon reserve condition evaluation method of claim 3, wherein the amplitude spectral ratio is compared to a parameter γ1Determining the seismic quality factor Q comprises:
obtaining a deconvolution generalized S domain Q value extraction formula;
for amplitude spectral ratio and parameter gamma1And performing linear fitting, and determining a seismic quality factor Q according to a Q value extraction formula.
6. The hydrocarbon preservation condition evaluation method of claim 5, wherein the Q-value extraction formula is:
7. the hydrocarbon preserving condition evaluation method of claim 1, wherein determining the threshold value of the seismic quality factor comprises:
determining a threshold value of a reservoir section pressure coefficient;
and determining a threshold value of the corresponding seismic quality factor according to the intersection relation between the reservoir section pressure coefficient and the seismic quality factor.
8. An oil and gas conservation condition evaluation device, characterized by comprising:
the generalized S transformation module is used for carrying out deconvolution generalized S transformation time-frequency analysis on the seismic data to obtain a deconvolution generalized S transformation amplitude spectrum of the seismic signal;
the calculation module is used for calculating a seismic quality factor Q;
the intersection module is used for determining the intersection relation between the pressure coefficient of the reservoir section and the seismic quality factor on the basis of the drilled well result, and further determining the threshold value of the seismic quality factor;
and the evaluation module is used for judging whether the oil gas storage condition is good or bad according to the threshold value of the seismic quality factor.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing executable instructions;
a processor executing the executable instructions in the memory to implement the hydrocarbon reserve condition evaluation method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the hydrocarbon preserving condition evaluation method as defined in any one of claims 1-7.
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