Quantitative prediction method of thin layer thickness based on interference of underlying gray strata

Abstract

The present invention provides a method for quantitatively predicting the thickness of thin layers due to interference from underlying limestone formations. The method comprises: using seismic forward modeling to quantitatively analyze the seismic interference characteristics of the underlying limestone formation on thin sandstone layers; determining the dominant tuning frequency of the thin sandstone layers through actual drilling sandbody thickness statistics; performing seismic frequency division processing to extract the optimal stratum slice combination at the dominant tuning frequency; establishing a frequency division slice fusion formula under actual drilling thickness constraints; and using the frequency division slice fusion formula to quantitatively predict the thickness of thin layers due to limestone interference. Based on seismic forward modeling analysis, the present invention optimizes a stratum slice combination that eliminates the influence of interference from the underlying limestone formation and establishes a quantitative formula for thin layer thickness under actual drilling thickness constraints. This significantly improves the accuracy of thin layer thickness prediction and can eliminate the influence of interference from the underlying limestone formation and achieve quantitative prediction of thin layer thickness when prestack seismic inversion is not possible.

Description

Technical Field

[0001] The present invention relates to the field of reservoir thickness prediction of continental complex concealed oil reservoirs, and in particular to a method for quantitatively predicting the thickness of a thin layer of underlying ash stratum interference. Background Art

[0002] Complex, subtle continental reservoirs feature complex and varied lithologies and diverse sedimentary rhythms. With the continued advancement of exploration and development, quantitative prediction of thin reservoir thickness has become a key constraint to efficient exploration and development. Quantitatively predicting the thickness of thin layers due to interference from underlying limestone formations is a challenging issue requiring attention. Prestack seismic inversion techniques can effectively eliminate the influence of this interference, but in practical exploration, the limited availability of prestack seismic data precludes widespread application. Therefore, research is needed to address this issue and quantitatively predict thin layer thicknesses, eliminating the influence of underlying limestone formations when prestack seismic inversion is unavailable.

[0003] Currently, domestic and international scholars have conducted extensive research and discussion on reservoir identification in areas with abundant ash matter. Most of these studies have applied prestack seismic inversion methods to areas with available P- and S-wave data, achieving reservoir identification in areas with abundant ash matter by constructing sensitive lithologic factors.

[0004] Among existing methods, prestack seismic inversion can only be applied in areas with shear-wave logging and prestack seismic data, preventing widespread application. Furthermore, prestack seismic inversion is highly specialized, complex, and time-consuming, making it unsuitable for the fast-paced, efficient exploration and development process. Among the numerous studies on thin-bed thickness prediction, most have focused on the tuning interference effect of the thin layers themselves. Using stratigraphic slices or combinations of stratigraphic slices with different tuning frequencies, these methods have been able to effectively predict the distribution of thin sandstones. However, these methods are applicable to relatively simple geological conditions and do not consider the interference effect of underlying ash layers on thin layers and their impact on thickness prediction. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for quantitatively predicting the thickness of thin layers with underlying gray strata interference, which can eliminate the influence of underlying gray strata interference and realize quantitative prediction of thin layer thickness when prestack seismic inversion cannot be carried out.

[0006] The purpose of the present invention can be achieved by the following technical measures:

[0007] A method for quantitatively predicting the thickness of a thin layer of underlying gray ground stratum interference comprises the following steps:

[0008] Step 110: Seismic forward modeling to quantitatively analyze the seismic interference characteristics of the underlying limestone strata on the thin sandstone layer;

[0009] Step 120, determining the dominant tuning frequency of the thin sandstone layer by statistically analyzing the thickness of the sandstone body during actual drilling;

[0010] Step 130: seismic frequency division processing to extract the best stratum slice combination under the dominant tuning frequency;

[0011] Step 140 , implementing the drilling thickness constraint and establishing a frequency-slice fusion formula;

[0012] Step 150: Quantitatively predict the thickness of the thin layer under gray matter interference using the frequency-division slice fusion formula.

[0013] Furthermore, the seismic forward modeling described in step 1 quantitatively analyzes the seismic interference characteristics of the underlying gray stratum on the thin layer, specifically including:

[0014] Through actual drilling analysis, the rock physical characteristics of the thickness, velocity and density of the underlying limestone formation and thin-bed sandstone were clarified, and a seismic forward model of the thin-bed sandstone of the underlying limestone formation was established;

[0015] Through wave equation seismic forward simulation, the seismic response characteristics of the underlying limestone stratum when it begins to interfere with the thin sandstone are determined, and the relationship between the thickness of the thin sandstone and the amplitude of the stratum slices at different positions is quantitatively calculated.

[0016] Furthermore, a combination of stratigraphic slices that can better reflect the thickness changes of thin-layer sandstone is selected. The adjacent peak amplitude ratio method is used, that is, the ratio of the amplitude of the peak slice of the underlying graystone stratum to the amplitude of the peak slice of the sandstone stratum is used to statistically analyze the relationship between the thickness of the thin-layer sandstone and the amplitude of the stratigraphic slices at different positions.

[0017] Furthermore, in step 2, the dominant tuning frequency of the thin sandstone is determined by counting the thickness of the actual drilled sandstone body, specifically including:

[0018] According to the thickness tuning principle, under the premise of determining the formation velocity, when the sandstone thickness is equal to one-quarter wavelength, the corresponding frequency is calculated according to the seismic longitudinal wave propagation velocity formula:

[0019] f=v / λ=v / 4h

[0020] Where v is the P-wave velocity, f is the dominant frequency of the seismic data, λ is the wavelength of the seismic P-wave, and h is the tuning thickness. Let h be equal to the thickness of the target sand body. The f calculated using the above formula is the dominant tuning frequency reflecting the target sand body.

[0021] Furthermore, in the seismic frequency division processing of step 3, the optimal stratigraphic slice combination at the dominant tuning frequency is extracted, specifically including: performing frequency division processing on the seismic data, selecting S transform as the time-frequency analysis algorithm, and calculating according to the following formula:

[0022]

[0023] Where t represents time, f represents frequency, τ represents the position of the Gaussian window on the time axis, the window width changes with frequency, and the reciprocal of the frequency determines the size of the window. s(t) represents the time domain input signal, exp represents the natural logarithm function, π represents the circumference of pi, i represents the imaginary unit, and dt represents the integral function.

[0024] After frequency division processing of the seismic data, a dominant tuning frequency body is generated, and the amplitude attributes of the target sand body stratum slice are extracted to obtain the optimal stratum slice combination under the dominant tuning frequency.

[0025] Furthermore, the seismic frequency division processing in step 3 specifically includes: performing frequency division processing on the seismic data using Fourier transform and wavelet transform time-frequency analysis algorithms.

[0026] Furthermore, extracting the amplitude attribute of the target sand body stratum slice specifically includes extracting the adjacent peak amplitude ratio of the optimal stratum slice combination, that is, the ratio of the underlying limestone stratum peak slice amplitude to the sandstone peak slice amplitude.

[0027] Furthermore, in step 4, the actual drilling thickness constraint is used to establish a frequency-slice fusion formula, which specifically includes the following steps:

[0028] The adjacent peak amplitude ratio method is used to process the formation slices within the dominant frequency range. Based on the statistical fitting relationship between the actual drilling sand body thickness and the frequency-divided slices, the frequency-divided slices after the ratio are subjected to weighted linear regression to establish a frequency-divided slice fusion formula to obtain the thickness of the target sand body:

[0029] Thickness=A1k1+A2k2+A3k3+……+A n k n +C

[0030] Among them, Thickness is the predicted thickness of thin sandstone; A is the optimal stratum slice combination of the dominant tuning frequency, that is, the adjacent peak amplitude ratio; A1 is the stratum slice combination of the first dominant frequency, and A n is the stratigraphic slice combination with the nth dominant frequency; k1 is the weighted coefficient value of the first stratigraphic slice combination, k n is the weighting coefficient value of the nth stratigraphic slice combination; C is the weighting constant.

[0031] Beneficial effects:

[0032] The present invention provides a quantitative prediction method for the thin layer thickness due to interference from underlying gray formations. Based on seismic forward simulation analysis, a combination of stratigraphic slices that eliminates the influence of interference from underlying gray formations is optimized, and a quantitative formula for thin layer thickness is established under the constraint of actual drilled thickness. This significantly improves the accuracy of thin layer thickness prediction and can eliminate the influence of interference from underlying gray formations when pre-stack seismic inversion cannot be performed, thereby achieving quantitative prediction of thin layer thickness. This further enriches the reservoir thickness prediction technology for complex continental concealed oil reservoirs and has good application effects and promotion prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of a method for quantitatively predicting the thickness of a thin layer of underlying gray ground stratum interference according to an embodiment of the present invention;

[0034] Figure 2 It is a seismic forward model diagram of the underlying gray soil strata and thin layers;

[0035] Figure 3 It is the cross analysis diagram of the thickness of thin-bed sandstone and the amplitude ratio of adjacent peaks;

[0036] Figure 4 It is the reservoir thickness prediction map after the fusion of frequency-divided stratigraphic slices. DETAILED DESCRIPTION

[0037] This section will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the accompanying drawings. The purpose of the accompanying drawings is to supplement the description of the text part of the specification with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of the present invention, but it should not be understood as a limitation on the scope of protection of the present invention.

[0038] like Figure 1 As shown, Figure 1 This is a flow chart of a method for quantitatively predicting the thickness of a thin layer of underlying gray ground stratum interference according to the present invention, which specifically includes the following steps:

[0039] Step 110 , seismic forward modeling, quantitatively analyzing the seismic interference characteristics of the underlying limestone strata on the thin sandstone layer.

[0040] In a specific embodiment of the present invention, actual drilling analysis is performed to clarify the rock physical characteristics such as thickness, velocity and density of the underlying limestone formation and thin sandstone. In the embodiment of the present invention, the lithologic combination types are mainly thin layers and underlying limestone formations.

[0041] For example, the thickness of thin sandstone ranges from 0 to 16 meters, with an average of about 10 meters and a velocity of 3500 m / s. The thickness of the underlying limestone stratum ranges from 0 to 30 meters, with an average of 15 meters. It is mainly composed of high-speed gray-calcareous mudstone and sandstone, with a large velocity variation of approximately 2900-4200 m / s. Based on this, a forward model of thin sandstone in three underlying limestone strata was established. Through wave equation seismic forward simulation, the relationship between the thickness of thin sandstone and the amplitude of stratum slices at different locations was quantitatively calculated. The stratum slice combination that best reflects the thickness variation of thin sandstone was selected, and the adjacent peak amplitude ratio was calculated, that is, the ratio of the peak slice amplitude of the underlying limestone stratum to the peak slice amplitude of the sandstone stratum. This achieves the purpose of eliminating the interference effect of the underlying limestone stratum and better reflecting the thickness of thin sandstone.

[0042] Step 120 : determining the dominant tuning frequency of the thin layer of sandstone by counting the thickness of the sandstone body actually drilled.

[0043] In the embodiment of the present invention, according to the thickness tuning principle, under the premise of determining the formation velocity, when the sandstone thickness is equal to one-quarter wavelength, the corresponding frequency is calculated according to the seismic longitudinal wave propagation velocity formula:

[0044] f=v / λ=v / 4h

[0045] Where v is the P-wave velocity, f is the dominant frequency of the seismic data, λ is the P-wave wavelength, and h is the tuning thickness. Let h be equal to the thickness of the target sand body. Using the above formula, we can calculate f as the dominant tuning frequency of the target sand body.

[0046] Through actual drilling statistical analysis, it was found that the thickness of thin sandstone is mainly distributed between 0-10m and 10-15m. According to the statistical sandstone velocity of 3500m / s, the dominant tuning frequency of this sand group is mainly 50Hz and 55Hz.

[0047] Step 130: seismic frequency division processing to extract the best stratum slice combination under the dominant tuning frequency.

[0048] In this embodiment of the present invention, seismic data is subjected to frequency division processing, and the S transform is selected as the time-frequency analysis algorithm. The S transform combines the advantages of the window Fourier transform and the wavelet transform. It can transform the signal from the time domain to the time-frequency domain, and can also convert from the time-frequency domain to the time domain through the inverse transform without losing any information. It has the characteristics of locality, lossless reversibility, and high resolution. Calculation is based on the following formula:

[0049]

[0050] Where t represents time, f represents frequency, τ represents the position of the Gaussian window on the time axis, the window width changes with frequency, and the reciprocal of the frequency determines the size of the window. s(t) represents the time domain input signal, exp represents the natural logarithm function, π represents the circumference of pi, i represents the imaginary unit, and dt represents the integral function.

[0051] In this specific example, the seismic data was divided into five frequency-divided data volumes at 35 Hz, 40 Hz, 45 Hz, 50 Hz, and 55 Hz, reflecting information about sand bodies of varying thicknesses. Furthermore, the optimal stratigraphic slice combination—the adjacent peak amplitude ratio, defined as the ratio of the underlying limestone slice amplitude to the sandstone slice amplitude—was extracted for the two dominant tuning frequencies of 50 Hz and 55 Hz in thin layers.

[0052] Step 140: Implement drilling thickness constraints and establish a frequency-slice fusion formula.

[0053] As a preferred embodiment of the present invention, the sand body thickness of 40 wells was selected and the adjacent peak amplitude ratio of the two dominant tuning frequencies of 50 Hz and 55 Hz was used for weighted linear regression to establish the frequency-divided stratigraphic slice fusion formula for thin layer thickness:

[0054] Thickness=8.15*A1+6.04*A2-9.14

[0055] Wherein, Thickness is the predicted thin layer thickness; A is the adjacent peak amplitude ratio of the optimal stratum slice combination of the dominant tuning frequency, A1 is the adjacent peak amplitude ratio of the dominant frequency of 50 Hz, and A2 is the adjacent peak amplitude ratio of the dominant frequency of 55 Hz.

[0056] Step 150: Quantitatively predict the thickness of the thin layer under gray matter interference using the frequency-division slice fusion formula.

[0057] In the embodiment of the present invention, the quantitative formula of frequency-divided stratum slices is promoted and applied to obtain a plane prediction map of thin layer thickness, thereby achieving quantitative prediction of the thin layer thickness of the underlying gray ground stratum interference.

[0058] Figure 2 It is a seismic forward model diagram of the underlying gray soil strata and thin layers. Figure 3 It is an intersection analysis diagram of the ratio of the effective reservoir thickness to the peak amplitude value of the reservoir top boundary at different frequencies. The diagram shows that the thin layer thickness is proportional to the adjacent peak amplitude ratio (the ratio of the peak slice amplitude of the underlying graystone formation to the peak slice amplitude of the sandstone formation), and has a good linear relationship. Figure 4This is a thin layer thickness prediction map obtained through the formation frequency slice fusion technology. Analysis shows that the prediction results are highly consistent with the actual drilled sand body thickness. The average thickness prediction error of the participating wells is 9.7%, and the average thickness prediction error of the verification wells is 18.2%, realizing the quantification of the thin layer thickness of the underlying gray formation interference.

[0059] The representation methods used in this specification are customary usages by those skilled in the art, which are well known to those skilled in the art and will not be explained in further detail.

[0060] As described above, the embodiments of the present invention have been described in detail and are not intended to limit the scope of protection of the present invention. As long as they do not substantially deviate from the inventive aspects and effects of the present invention, many variations are possible, which will be apparent to those skilled in the art. Therefore, all such variations are also included in the scope of protection of the present invention.

Claims

1. A quantitative prediction method for the thickness of a thin layer of underlying gray ground stratum interference, characterized in that The following steps are involved: Step 110: Seismic forward modeling to quantitatively analyze the seismic interference characteristics of the underlying limestone strata on the thin sandstone layer; Step 120, determining the dominant tuning frequency of the thin sandstone layer by statistically analyzing the thickness of the sandstone body during actual drilling; Step 130: seismic frequency division processing to extract the best stratum slice combination under the dominant tuning frequency; Step 140 , implementing the drilling thickness constraint and establishing a frequency-slice fusion formula; Step 150, using the frequency-division slice fusion formula, quantitatively predicting the thickness of the thin layer under gray matter interference; The seismic forward modeling in step 110 quantitatively analyzes the seismic interference characteristics of the underlying gray stratum on the thin layer, specifically including: Through actual drilling analysis, the rock physical characteristics of the thickness, velocity and density of the underlying limestone formation and thin-bed sandstone were clarified, and a seismic forward model of the thin-bed sandstone of the underlying limestone formation was established; Through wave equation seismic forward modeling, the seismic response characteristics of the underlying limestone strata when they begin to interfere with the thin sandstone layer are determined, and the relationship between the thickness of the thin sandstone layer and the amplitude of the stratigraphic slices at different locations is quantitatively analyzed. The method further includes: selecting a combination of stratum slices that can better reflect the thickness change of the thin sandstone layer; performing statistical analysis on the relationship between the thickness of the thin sandstone layer and the amplitude of stratum slices at different positions by using the adjacent peak amplitude ratio method, i.e., the ratio of the amplitude of the peak slice of the underlying limestone layer to the amplitude of the peak slice of the sandstone layer; and determining the dominant tuning frequency of the thin sandstone layer by the actual drilling sand body thickness statistics in step 120, specifically including: According to the thickness tuning principle, under the premise of determining the formation velocity, when the sandstone thickness is equal to one-quarter wavelength, the corresponding frequency is calculated according to the seismic longitudinal wave propagation velocity formula: f=v / λ=v / 4h Where v is the P-wave velocity, f is the main frequency of the seismic data, λ is the wavelength of the seismic P-wave, and h is the tuning thickness. Let h be equal to the thickness of the target sand body. The f calculated using the above formula is the dominant tuning frequency reflecting the target sand body. In step 130, the seismic frequency division processing is performed to extract the optimal stratigraphic slice combination at the dominant tuning frequency, specifically including: performing frequency division processing on the seismic data, selecting S transform as the time-frequency analysis algorithm, and performing calculation according to the following formula: Where t represents time, f represents frequency, τ represents the position of the Gaussian window on the time axis, the window width changes with the frequency, and the reciprocal of the frequency determines the size of the window, s(t) represents the time domain input signal, exp represents the natural logarithm function, π represents the circumference of pi, i represents the imaginary unit, and dt represents the integral function; After frequency division processing of the seismic data, a dominant tuning frequency volume is generated, and the amplitude attributes of the target sand body stratum slice are extracted to obtain the optimal stratum slice combination under the dominant tuning frequency; The seismic frequency division processing in step 130 specifically includes: performing frequency division processing on the seismic data using Fourier transform and wavelet transform time-frequency analysis algorithms.

2. The method for quantitatively predicting the thickness of the underlying gray ground stratum interference according to claim 1 is characterized in that: The extracting of the amplitude attribute of the target sand body stratum slice specifically includes extracting the adjacent peak amplitude ratio of the optimal stratum slice combination, that is, the ratio of the amplitude of the underlying limestone stratum peak slice to the amplitude of the sandstone peak slice.

3. The method for quantitatively predicting the thickness of the underlying gray ground stratum interference according to claim 2, characterized in that: In step 140, the actual drilling thickness constraint is used to establish a frequency-slice fusion formula, which specifically includes the following steps: The adjacent peak amplitude ratio method is used to process the formation slices within the dominant frequency range. Based on the statistical fitting relationship between the actual drilling sand body thickness and the frequency-divided slices, the frequency-divided slices after the ratio are subjected to weighted linear regression to establish a frequency-divided slice fusion formula to obtain the thickness of the target sand body: Thickness=A1k1+A2k2+A3k3+……+A n k n +C Among them, Thickness is the predicted thickness of thin sandstone; A is the optimal stratum slice combination of the dominant tuning frequency, that is, the adjacent peak amplitude ratio; A1 is the stratum slice combination of the first dominant frequency, and A n is the stratigraphic slice combination with the nth dominant frequency; k1 is the weighted coefficient value of the first stratigraphic slice combination, k n is the weighting coefficient value of the nth stratigraphic slice combination; C is the weighting constant.

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