CN114594514A - A Quantitative Prediction Method of Thin Layer Thickness Based on Interference of Underlying Limestone - Google Patents

Abstract

The invention provides a method for quantitatively predicting the thickness of a thin layer by interfering with an underlying limestone stratum. The method includes: seismic forward modeling, quantitatively analyzing the seismic interference characteristics of the underlying limestone stratum on the thin sandstone; Determine the dominant tuning frequency of the thin sandstone; Seismic frequency division processing, extract the optimal formation slice combination under the dominant tuning frequency; Constrain the thickness of the actual drilling, establish a frequency division slice fusion formula; Use the frequency division slice fusion formula , quantitative prediction of thin layer thickness under gray matter interference. On the basis of seismic forward modeling simulation analysis, the invention optimizes the combination of strata slices that eliminates the interference effect of the underlying gray strata, and establishes a thin layer thickness quantitative formula under the constraint of actual drilling thickness, which significantly improves the thin layer thickness prediction accuracy. In the case where prestack seismic inversion cannot be performed, the interference effect of the underlying limestone strata can be eliminated, and the quantitative prediction of thin layer thickness can be realized.

Description

A Quantitative Prediction Method of Thin Layer Thickness Based on Interference of Underlying Limestone

technical field

The invention relates to the field of reservoir thickness prediction of complex and hidden oil reservoirs in continental facies, in particular to a thin layer thickness quantitative prediction method with the interference of underlying ash strata.

Background technique

Continental complex and subtle oil reservoirs have complex and changeable lithology and diverse sedimentary rhythms. With the continuous advancement of exploration and development, quantitative prediction of the thickness of thin reservoirs has become the key to restricting efficient exploration and development. Among them, the quantitative prediction of the thin layer thickness of the underlying gray layer interference is a difficult problem that needs to be paid attention to. Pre-stack seismic inversion technology can effectively eliminate the interference effect of gray strata, but in actual exploration, there are few pre-stack seismic data, which cannot be widely applied. Therefore, it is necessary to study a method to achieve quantitative prediction of thin layer thickness by eliminating the interference effect of the underlying limestone strata when pre-stack seismic inversion cannot be carried out.

At present, domestic and foreign scholars have carried out a lot of research and discussion on reservoir identification in grey matter development areas. Among them, most of the application areas in the literature have P and S wave data, and the pre-stack seismic inversion method is used, and the reservoir identification in the gray matter development area is realized by constructing sensitive lithological factors.

Among the existing technical methods, the pre-stack seismic inversion technology can only be applied to areas with shear wave logging and pre-stack seismic data, and cannot be widely applied. The cycle is long and cannot adapt to the fast-paced and efficient exploration and development process. In many studies on thin layer thickness prediction, most of them have paid attention to the tuning interference effect of the thin layer itself. The application of formation slices or combination of formation slices with different tuning frequencies can better predict the distribution range of thin sandstones, but the method is suitable for The geological conditions are relatively simple, and the interference effect on the thin layer and the influence on the thickness prediction of the thin layer when the underlying gray layer is not considered.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method for quantitatively predicting the thickness of the thin layer with the interference of the underlying ash strata, which can eliminate the influence of the interference of the underlying ash strata and realize the quantitative prediction of the thickness of the thin layer when the pre-stack seismic inversion cannot be carried out.

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

A method for quantitatively predicting the thickness of a thin layer by interfering with an underlying grey matter stratum, comprising the following steps:

Step 110, seismic forward modeling, quantitatively analyze the seismic interference characteristics of the underlying limestone strata to the thin sandstone;

Step 120: Determine the dominant tuning frequency of the thin-bed sandstone through the actual drilling sand body thickness statistics;

Step 130, seismic frequency division processing, to extract the best combination of formation slices under the dominant tuning frequency;

Step 140, implementing the drilling thickness constraint, and establishing a frequency division slice fusion formula;

Step 150, using the frequency division slice fusion formula to quantitatively predict the thickness of the thin layer under gray matter interference.

Further, the seismic forward modeling described in step 1 quantitatively analyzes the seismic interference characteristics of the underlying limestone strata to the thin layer, specifically including:

Through the analysis of actual drilling, the petrophysical characteristics of the thickness, velocity and density of the underlying calcareous strata and thin sandstones were clarified, and the thin sandstone seismic forward modeling model of the underlying calcareous strata was established;

Through the wave equation seismic forward modeling, the seismic response characteristics of the underlying limestone strata when the thin sandstone 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 slice at different positions is quantitatively calculated.

Further, the combination of formation slices that can better reflect the thickness variation of thin-bed sandstone is selected, and processed by the adjacent wave peak amplitude ratio method, that is, the ratio of the amplitude of the wave crest slice of the underlying limestone stratum to the amplitude of the sandstone wave crest slice, and the statistical difference between the thickness of the thin-bed sandstone and the difference is calculated. Variation relationship of the amplitude of the position stratigraphic slice.

Further, as described in step 2, the dominant tuning frequency of the thin sandstone is determined through the actual drilling sand body thickness statistics, which specifically includes:

According to the principle of thickness tuning, on the premise that the formation velocity is determined, when the sandstone thickness is equal to one-quarter wavelength, the corresponding frequency can be obtained according to the seismic longitudinal wave propagation velocity formula:

f=v/λ=v/4h

Among them, v is the P-wave velocity, f is the dominant frequency of the seismic data, λ is the seismic 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, f is the dominant tuning frequency that reflects the target sand body.

Further, in the seismic frequency division processing described in step 3, the optimal formation slice combination under the advantageous tuning frequency is extracted, which specifically includes: performing frequency division processing on the seismic data, selecting S transform as the time-frequency analysis algorithm, according to the following: Formula to calculate:

Among them, t represents time, f represents frequency, τ is the position of the Gaussian window on the time axis, the width of the time window changes with the frequency, the inverse of the frequency determines the size of the time window, and s(t) represents the time domain input signal, exp is the natural logarithmic function, π is the pi, i is the imaginary unit, and dt is the integral function.

After frequency division processing of the seismic data, a dominant tuning frequency volume is generated, and the amplitude attribute of the target sand body formation slice is extracted to obtain the optimal formation slice combination under the dominant tuning frequency.

Further, the seismic frequency division processing in step 3 specifically includes: using Fourier transform and wavelet transform time-frequency analysis algorithms to perform frequency division processing on the seismic data.

Further, the extracting the amplitude attribute of the target sand body formation slice specifically includes: extracting the adjacent wave crest amplitude ratio of the optimal formation slice combination, that is, the ratio of the wave crest slice amplitude of the underlying limestone formation to the sandstone wave crest slice amplitude.

Further, in step 4, the actual drilling thickness constraint is established, and the frequency division slice fusion formula is established, which specifically includes the following steps:

The adjacent wave peak amplitude ratio method is performed on the formation slices in the dominant frequency range. According to the statistical fitting relationship between the actual drilling sand body thickness and the frequency division slices, the frequency division slices after the ratio are subjected to weighted linear regression to establish the frequency division. Slice fusion formula to obtain the thickness value of the target sand body:

Thickness=A ₁ k ₁ +A ₂ k ₂ +A ₃ k ₃ +……+A _n k _n +C

Among them, Thickness is the predicted thickness of thin sandstone; A is the optimal formation slice combination of the dominant tuning frequency, that is, the adjacent peak amplitude ratio, A1 is the formation slice combination of the _first dominant frequency, and An is the _nth dominant frequency. The combination of formation slices; k ₁ is the weighting coefficient value of the first formation slice combination, k _n is the weighting coefficient value of the nth formation slice combination; C is the weighting constant.

Beneficial effects:

The method for quantitatively predicting the thin layer thickness of the underlying limestone stratum interference in the present invention, on the basis of the seismic forward modeling analysis, optimizes the formation slice combination that eliminates the influence of the underlying limestone stratum interference, and under the constraint of the actual drilling thickness, A quantitative formula for thin layer thickness is established, which significantly improves the prediction accuracy of thin layer thickness. It can eliminate the interference effect of the underlying limestone strata and realize the quantitative prediction of thin layer thickness when pre-stack seismic inversion cannot be carried out, which further enriches the complexity of continental facies. The reservoir thickness prediction technology for hidden oil reservoirs has good application effects and promotion prospects.

Description of drawings

1 is a flow chart of a method for quantitatively predicting the thickness of a thin layer with interference of underlying ash strata according to an embodiment of the present invention;

Fig. 2 is the seismic forward modeling model diagram of the underlying limestone strata and thin layers;

Fig. 3 is the intersection analysis diagram of the thickness of thin sandstone and the amplitude ratio of adjacent wave peaks;

Fig. 4 is a prediction diagram of reservoir thickness after fusion of frequency-division formation slices.

Detailed ways

This part will describe the specific embodiments of the present invention in detail, and the preferred embodiments of the present invention are shown in the accompanying drawings. Each technical feature and overall technical solution of the invention should not be construed as limiting the protection scope of the invention.

As shown in FIG. 1, FIG. 1 is a flowchart of a method for quantitatively predicting the thickness of a thin layer by interference of an underlying ash stratum of the present invention, which specifically includes the following steps:

In step 110, seismic forward modeling is performed to quantitatively analyze the seismic interference characteristics of the underlying calcareous strata to the thin sandstone.

In a specific embodiment of the present invention, through actual drilling analysis, the petrophysical characteristics such as the thickness, velocity and density of the underlying calcareous strata and thin sandstone are clarified. Volatile ash strata.

Exemplarily, the thickness range of thin sandstone is 0-16m, with an average of about 10m, and the speed is 3500m/s; the thickness of the underlying calcareous layer is 0-30m, with an average of 15m, mainly high-speed lime-calcareous mudstone and sandstone, with a speed of 3500m/s. The change is large, about 2900-4200m/s. Based on this, three thin-bed sandstone forward modeling models of the underlying limestone strata were established. Through the wave equation seismic forward modeling, the relationship between the thickness of thin-bed sandstone and the amplitude of the stratum slices at different positions was quantitatively calculated, and the thin-bed sandstone thickness was calculated quantitatively. For the combination of strata slices with varying sandstone thickness, the amplitude ratio of adjacent wave crests is calculated, that is, the ratio of the amplitude of the wave crest slices of the underlying limestone stratum to the amplitude of the sandstone wave crest slices. .

Step 120: Determine the dominant tuning frequency of the thin layer of sandstone through the actual drilling sand body thickness statistics.

In the embodiment of the present invention, according to the thickness tuning principle, under the premise that the formation velocity is determined, when the sandstone thickness value is equal to a quarter wavelength, the corresponding frequency is obtained according to the seismic longitudinal wave propagation velocity formula:

f=v/λ=v/4h

Among them, v is the longitudinal wave velocity, f is the dominant frequency of the seismic data, λ is the seismic longitudinal wave wavelength, and h is the tuning thickness. Let h be equal to the thickness of the target sand body, and f calculated from the above formula is the dominant tuning frequency reflecting the target sand body.

Through the statistical analysis of actual drilling, it is concluded that the thickness of sandstone in the thin layer 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.

Step 130: Seismic frequency division processing to extract the best combination of formation slices at the dominant tuning frequency.

In the embodiment of the present invention, frequency division processing is performed on seismic data, and 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 inverse transformation without losing any information. Features of lossless reversibility and high resolution. Calculated according to the following formula:

Among them, t represents time, f represents frequency, τ is the position of the Gaussian window on the time axis, the width of the time window changes with the change of frequency, the inverse of the frequency determines the size of the time window, and s(t) represents the time domain input signal , exp is the natural logarithmic function, π is the pi, i is the imaginary unit, and dt is the integral function.

In a specific embodiment, the seismic data is divided into 5 frequency division data volumes of 35Hz, 40Hz, 45Hz, 50Hz and 55Hz, reflecting sand body information of different thicknesses. Furthermore, the optimal stratum slice combination-adjacent wave crest amplitude ratio was extracted from the two dominant tuning frequencies of 50Hz and 55Hz in the thin layer, that is, the ratio of the crest slice amplitude of the underlying limestone formation to the sandstone crest slice amplitude.

Step 140 , implementing the drilling thickness constraint, and establishing a frequency division slice fusion formula.

As a preferred embodiment of the present invention, the weighted linear regression is performed by selecting the sand body thickness of 40 real wells and the adjacent peak amplitude ratios of the two dominant tuning frequencies of 50 Hz and 55 Hz, and establishing the frequency division formation slice fusion formula of thin layer thickness. :

Thickness=8.15*A ₁ +6.04*A ₂ -9.14

Among them, Thickness is the predicted thickness of the thin layer; A is the adjacent peak amplitude ratio of the optimal formation slice combination of the dominant tuning frequency, A ₁ is the adjacent peak amplitude ratio of the 50 Hz dominant frequency, and A ₂ is the adjacent 55 Hz dominant frequency. Crest Amplitude Ratio.

Step 150, using the frequency division slice fusion formula to quantitatively predict the thickness of the thin layer under gray matter interference.

In the embodiment of the present invention, the quantitative formula of frequency-division formation slices is popularized and applied to obtain a plane prediction map of the thickness of the thin layer, so as to realize the quantitative prediction of the thickness of the thin layer due to the interference of the underlying calcareous strata.

Fig. 2 is the seismic forward modeling model diagram of the underlying limestone strata and thin layers. Fig. 3 is the intersection analysis diagram of the effective reservoir thickness and the ratio of the peak amplitude value at the top of the reservoir at different frequencies. ratio) is proportional to, and has a better linear relationship. Figure 4 is the thin layer thickness prediction map obtained by the formation frequency slice fusion technology. The analysis shows that the prediction results are in good agreement with the actual drilling sand body thickness. The thickness prediction error of the participating wells is 9.7% on average, and the thickness prediction error of the verification wells At an average of 18.2%, a thin layer thickness quantification of the underlying ash strata interference was achieved.

The representation methods used in this specification are commonly used by those skilled in the art, and are well known to those skilled in the art, and will not be explained in more detail.

As described above, the embodiments of the present invention have been described in detail, but are not intended to limit the protection scope of the present invention. It will be apparent to those skilled in the art that many modifications can be made without substantially departing from the invention and effect of the present invention. Therefore, all such modifications are also included in the scope of the present invention.

Claims (8)

1. a method for quantitatively predicting the thickness of a thin layer of the interference of underlying ash strata, is characterized in that comprising the following steps: Step 110, seismic forward modeling, quantitatively analyze the seismic interference characteristics of the underlying limestone strata to the thin sandstone; Step 120: Determine the dominant tuning frequency of the thin-bed sandstone through the actual drilling sand body thickness statistics; Step 130, seismic frequency division processing, to extract the best combination of formation slices under the dominant tuning frequency; Step 140, implementing the drilling thickness constraint, and establishing a frequency division slice fusion formula; Step 150, using the frequency division slice fusion formula to quantitatively predict the thickness of the thin layer under gray matter interference. 2. The method for quantitatively predicting the thickness of a thin layer by the interference of an underlying limestone stratum according to claim 1, wherein the seismic forward modeling described in step 110 quantitatively analyzes the seismic interference of the underlying limestone strata to the thin layer Features, including: Through the analysis of actual drilling, the petrophysical characteristics of the thickness, velocity and density of the underlying calcareous strata and thin sandstones were clarified, and the thin sandstone seismic forward modeling model of the underlying calcareous strata was established; Through the wave equation seismic forward modeling, the seismic response characteristics of the underlying limestone strata when the thin sandstone 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 slice at different positions is quantitatively calculated. 3. The method for quantitatively predicting the thickness of a thin layer based on the interference of an underlying limestone stratum according to claim 2, wherein the method further comprises: selecting a combination of strata slices that can better reflect the thickness variation of the thin-bed sandstone, through adjacent wave crests Amplitude ratio method processing, that is, the ratio of the amplitude of the wave crest slice of the underlying limestone stratum to the amplitude of the sandstone wave crest slice, and the relationship between the thickness of the thin sandstone and the slice amplitude of the stratum at different positions is calculated. 4 . The method for quantitatively predicting the thickness of thin layers by interference of underlying limestone strata according to claim 2 , wherein in step 120 , the predominant tuning frequency of the thin layer sandstone is determined according to the thickness statistics of the actual drilling sand body. 5 . , including: According to the principle of thickness tuning, on the premise that the formation velocity is determined, when the sandstone thickness is equal to one-quarter wavelength, the corresponding frequency can be obtained according to the seismic longitudinal wave propagation velocity formula: f=v/λ=v/4h Among them, v is the P-wave velocity, f is the dominant frequency of the seismic data, λ is the seismic 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, f is the dominant tuning frequency that reflects the target sand body. 5. The method for quantitatively predicting the thin layer thickness of the underlying limestone formation interference according to claim 3, wherein, in the seismic frequency division processing in step 130, the optimal formation slice combination under the dominant tuning frequency is extracted, Specifically, in the frequency division processing of seismic data, S-transform is selected as the time-frequency analysis algorithm, and the calculation is performed according to the following formula:

Among them, t represents time, f represents frequency, τ is the position of the Gaussian window on the time axis, the width of the time window changes with the frequency, the inverse of the frequency determines the size of the time window, and s(t) represents the time domain input signal, exp is the natural logarithmic function, π is the pi, i is the imaginary unit, and dt is the integral function. After frequency division processing of the seismic data, a dominant tuning frequency volume is generated, and the amplitude attribute of the target sand body formation slice is extracted to obtain the optimal formation slice combination under the dominant tuning frequency. 6. The method for quantitatively predicting the thickness of the thin layer by the interference of the underlying limestone strata according to claim 3, wherein the seismic frequency division processing in step 130 specifically comprises: using Fourier transform, wavelet transform time-frequency analysis algorithm , frequency division processing of seismic data. 7 . The method for quantitatively predicting the thickness of thin layers by interfering with underlying limestone formations according to claim 5 , wherein the extracting the amplitude attribute of the target sand body formation slices specifically comprises: extracting adjacent wave crests of an optimal formation slice combination. 8 . Amplitude ratio, that is, the ratio of the wave crest slice amplitude of the underlying limestone stratum to the sandstone wave crest slice amplitude. 8. The method for quantitatively predicting the thin layer thickness of underlying limestone strata interference according to claim 4, characterized in that, in step 140, the actual drilling thickness constraint is established, and a frequency division slice fusion formula is established, specifically comprising the following steps: The adjacent wave peak amplitude ratio method is performed on the formation slices in the dominant frequency range. According to the statistical fitting relationship between the actual drilling sand body thickness and the frequency division slices, the frequency division slices after the ratio are subjected to weighted linear regression to establish the frequency division. Slice fusion formula to obtain the thickness value of the target sand body: Thickness=A ₁ k ₁ +A ₂ k ₂ +A ₃ k ₃ +……+A _n k _n +C Among them, Thickness is the predicted thickness of thin sandstone; A is the optimal formation slice combination of the dominant tuning frequency, that is, the adjacent peak amplitude ratio, A1 is the formation slice combination of the _first dominant frequency, and An is the _nth dominant frequency. The combination of formation slices; k ₁ is the weighting coefficient value of the first formation slice combination, k _n is the weighting coefficient value of the nth formation slice combination; C is the weighting constant.

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