CN114137607A - Layer-sequence stratum dividing method - Google Patents
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Abstract
The invention relates to a sequence stratum partitioning method, which belongs to the field of seismic exploration and seismic data interpretation, and realizes the depth fusion of seismic information and logging information, namely forward modeling is carried out by utilizing a reconstructed wave impedance curve to obtain a seismic synthetic record, the seismic synthetic record and well seismic data are reconstructed, and then a final time frequency spectrum is obtained through generalized S transformation. The sequence stratum dividing method has strong practicability and can be popularized and applied in the sedimentation environment of the continental lake basin.
Description
Technical Field
The invention belongs to the field of seismic data interpretation of seismic exploration, and particularly relates to a sequence stratigraphic division method.
Background
In recent years, with the deep exploration and development of hidden oil and gas reservoirs, sequence stratigraphy is widely applied. The key of the sequence stratum analysis is to divide stratum sequence interfaces of different levels and deposition loops in the stratum sequence interfaces. In actual production, the identification of the stratigraphic sequence interface is generally performed by using data such as outcrop, core, well logging, etc., wherein the most applied is the stratigraphic study of the stratigraphic sequence by using well drilling and well logging data because: the well drilling and logging data is one of geological data with the best continuity and the highest resolution at present, and by using the rock electricity change characteristics and coring characteristics of a logging curve, a very small-level sequence cycle can be marked.
At present, the common methods for carrying out the stratigraphic sequence stratigraphic division by utilizing logging data comprise a logging curve activity analysis method, a wavelet transformation method, a maximum entropy spectrum method and the like, but due to the response of low resolution of the seismic data, the stratigraphic sequence stratigraphic layers divided by the drilling and logging data and the stratigraphic sequence grillwork established by the stratigraphic sequence stratigraphic layers are difficult to be applied to the three-dimensional seismic data, so that the subsequent exploration and development are restricted.
Based on the above consideration, some experts and scholars propose a method for performing sequence-stratum division by comprehensively using two kinds of data of well logging and earthquake, for example, a writer Liu enlightens a paper of well-earthquake combined sequence-stratum division in journal deposition and Tetis geology, volume 39, 3, of 2019, and a well-earthquake combined sequence-stratum division method is proposed.
Although the method takes the synthetic record as a bridge and connects the stratigraphic division by using the seismic stratigraphic sequence and the stratigraphic division by using the well logging, the method still carries out the independent stratigraphic sequence division on the seismic data and the well logging data respectively, carries out the limited optimization on the basis of the results of the two stratigraphic sequence divisions, does not change the essence that the stratigraphic sequence division is carried out on the basis of single data, has certain limitation in application and lower division precision.
Disclosure of Invention
The invention aims to provide a sequence stratigraphic division method, which is used for solving the problem of low accuracy of the conventional method for combining logging and seismic data to carry out sequence stratigraphic division.
Based on the purpose, the technical scheme of the layer-sequence stratum dividing method is as follows:
1) collecting a three-dimensional post-stack seismic data volume of a target work area, and determining the frequency band range of the seismic data volume; collecting the acoustic wave, density and natural gamma ray logging curves of the drilled well of the target work area;
2) calculating a wave impedance curve according to the sound wave and density logging curve obtained in the step 1);
3) performing low-pass filtering on the wave impedance curve obtained by calculation in the step 2), setting the cut-off frequency as the upper limit value of the frequency band range, and obtaining the filtered wave impedance curve;
carrying out high-pass filtering on the natural gamma curve obtained in the step 1), setting the cut-off frequency as the upper limit value of the frequency band range to obtain a filtered natural gamma curve, and carrying out value domain inversion and normalization processing on the curve;
performing product processing on the filtered wave impedance curve and the natural gamma curve after normalization processing to obtain a reconstructed wave impedance curve;
4) forward modeling is carried out by utilizing the wave impedance curve reconstructed in the step 3) to obtain a seismic synthetic record;
5) extracting well-passed seismic data according to the three-dimensional post-stack seismic data volume obtained in the step 1);
6) carrying out high-pass filtering on the seismic synthetic record obtained in the step 4), setting the cut-off frequency as the upper limit value of the frequency band range, and obtaining the filtered seismic synthetic record;
summing the filtered seismic synthetic record and the well-passing seismic data in the step 5) to obtain a reconstructed seismic record;
7) and carrying out generalized S transformation on the reconstructed seismic record to obtain a time frequency spectrum of the seismic record, and carrying out sequence stratigraphic division on the target work area by using the time frequency spectrum.
The beneficial effects of the above technical scheme are:
the sequence stratum dividing method realizes the depth fusion of the seismic information and the logging information, namely forward modeling is carried out by utilizing the reconstructed wave impedance curve to obtain the seismic synthetic record, the seismic synthetic record is reconstructed with the well-passing seismic data, and then the final time frequency spectrum is obtained through generalized S transformation. The sequence stratum dividing method has strong practicability and can be popularized and applied in the sedimentation environment of the continental lake basin.
Further, in step 4), performing forward modeling by using the wave impedance curve reconstructed in step 3) includes:
performing convolution operation on the wave impedance curve reconstructed in the step 3) and the set Rake wavelets to obtain a seismic synthetic record, wherein the dominant frequency of the Rake wavelets is set according to the following steps: dominant frequency f greater than seismic datacAnd less than the sampling frequency f of the seismic data volumeNThe synthetic record is ensured not to be distorted, and the resolution ratio is higher than that of the original seismic data.
Further, in order to obtain high-resolution seismic synthetic record, the dominant frequency of the Rake wavelet is
fNThe sampling frequency of the seismic data volume in step 1).
Further, in order to obtain a reconstructed wave impedance curve, in step 3), a calculation formula of the value range inversion is as follows:
in the formula (I), the compound is shown in the specification,
the natural gamma curve value after the value range inversion, GR' (i) the natural gamma curve value before the value range inversion, and max the maximum value of the natural gamma curve before the value range inversion.
Further, in order to obtain a reconstructed wave impedance curve, in step 3), a calculation formula of the normalization process is as follows:
where GR' (i) is the normalized natural gamma curve value, max is the maximum value of the natural gamma curve after the range inversion, and min is the minimum value of the natural gamma curve after the range inversion.
Drawings
FIG. 1 is a flow chart of a method of stratigraphic hierarchy partitioning in an embodiment of the present invention;
FIG. 2 is a cross-sectional view of a post-stack seismic well bore in an embodiment of the present invention;
FIG. 3 is a post-stack seismic section amplitude spectrum in an embodiment of the invention;
FIG. 4 is a graphical illustration of sonic, density and natural gamma log curves for a well in an embodiment of the present invention;
FIG. 5 is a graphical representation of calculated compressional impedance and reconstructed compressional impedance for a given well in an embodiment of the invention;
FIG. 6 is a graph of constructed Rake wavelets in an embodiment of the invention;
FIG. 7 is a graph of extracted through-well seismic data in an embodiment of the invention;
FIG. 8 is a synthetic seismic record map in an embodiment of the invention;
FIG. 9 is a diagram of reconstructed seismic records in an embodiment of the invention;
FIG. 10 is a reconstructed seismic time spectrum and sequence stratigraphic division diagram in an embodiment of the invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings.
The embodiment provides a method for dividing a stratum into a sequence, the overall process is shown in fig. 1, and the implementation steps of the method are specifically described below by taking a certain depression of a silver-forehead basin as an example:
for seismic data, a three-dimensional post-stack seismic data volume of a depression in the silver frontal basin is collected, the sampling rate (i.e., the sampling interval time) of the data volume is Δ T2 ms, and the frequency is
In Hz, as shown in FIG. 2.
Fourier transforming the three-dimensional post-stack seismic data volume collected above to obtain a spectral characteristic curve of the data volume, as shown in FIG. 3, from which a frequency band range [ f ] of the data volume is obtained1,f2]And main frequency fc. In fig. 3, the abscissa represents Frequency (i.e., Frequency) and the ordinate represents amplitude (amplitude).
For logging information, collecting acoustic, density and natural gamma logging curves of the completed well in the work area, wherein the three logging curves are shown in fig. 4, the first row is an acoustic time difference curve, the second row is a density curve and the third row is a natural gamma curve, and the sampling rates of the logging curves are unified to be delta h which is 0.125 m; setting a sound wave curve as DT (i), wherein i represents the depth, and the value range of the sound wave time difference is 150-; the density curve is RHOB (i), i represents depth, and the density value range is 2-3g/cm3(ii) a The natural gamma curve is GR (i), i represents depth, and the value range of the natural gamma is 10-180 API.
Step 3, obtaining a reconstructed wave impedance curve Pimp _ GR (i), and the specific steps are as follows:
3.1 low-pass filtering the wave impedance curve Pimp (i) calculated in the step 2, wherein the cut-off frequency of a low-pass filtering operator is f2(i.e., the upper limit of the band range of the data volume in step 1), a filtered wave impedance curve Pimp' (i) is obtained.
3.2 carrying out high-pass filtering on the natural gamma curve GR (i) obtained in the step 1, wherein the cutoff frequency of a high-pass filtering operator is f2Obtaining a filtered natural gamma curve GR' (i), and performing value domain inversion on the filtered natural gamma according to the following formula to obtain a value domain inverted natural gamma curve
Where max is the maximum value in the filtered natural gamma curve GR' (i).
Normalizing the natural gamma curve after the value range inversion according to the following calculation formula to obtain a final curve GR' (i);
in the formula, min is the minimum value in the natural gamma curve after the value range inversion, and max is the maximum value in the natural gamma curve after the value range inversion.
3.3 multiplying the Pimp' (i) obtained in the step 3.1 by the GR "(i) obtained in the step 3.2 to obtain a reconstructed wave impedance curve Pimp _ GR (i), as shown in the second column of FIG. 5, the value range is 2500-.
In the step, because the wave impedance of general mudstone is less than that of sandstone, and the natural gamma value of the mudstone is higher than that of sandstone, if the natural gamma value domain inversion is not performed, the reconstructed wave impedance can cause the condition that the wave impedance of the mudstone is greater than that of the sandstone; in addition, the purpose and significance of reconstructing the wave impedance curve are that the difference of impedance values between the sandstone and the mudstone is improved, the capability of describing the sandstone and the mudstone is improved, and the stratum of different sequence can be conveniently identified.
Step 4, forward modeling to obtain the earthquake synthetic record y (j), and the specific steps are as follows:
4.1 constructing a Ricker wavelet (Ricker) as shown in FIG. 6 with a dominant frequency of Ricker wavelet
Here, the dominant frequency of the Rake wavelet is selected to be larger than the dominant frequency f of the seismic datacAnd is smaller than
The purpose of being greater than fc is to obtain a synthetic record with a resolution greater than the original seismic data, less than fNThe purpose of the method is to ensure that the synthesized record is not distorted and spurious frequency does not occur; here get
The purpose of the method is to obtain high-resolution synthesis record and ensure that the signal does not generate spurious; in fig. 6, the abscissa represents Time (Time) and the ordinate represents amplitude (Amp).
4.2, performing convolution operation on the wave impedance curve Pimp _ GR (i) obtained in the step 3 and the Rake wavelets in the step to obtain a seismic synthetic record y (j), as shown in FIG. 7.
And 5, extracting the seismic data of the well passing along the drilling track (indicated by an arrow in the figure 2) according to the three-dimensional post-stack seismic data volume obtained in the step 1, setting the seismic data as x (j), and obtaining an extraction result as shown in figure 8.
Step 6, reconstructing a seismic record X (j), specifically:
6.1 high-pass filtering is carried out on the seismic synthetic record y (j) obtained in the step 4, and the low cut-off frequency of the high-pass filtering is f2Filtered summationTo be recorded as y' (j).
6.2 summing the filtered synthetic record y' (j) obtained in step 6.1 with the seismic data x (j) obtained in step 5 to obtain a reconstructed seismic record x (j), as shown in fig. 9.
In the step, the purpose of performing high-pass filtering on the synthetic record is to eliminate the synthetic record information in the seismic frequency band range, because the original earthquake is strictly kept by the part of the information, the seismic original information is in the seismic frequency band range and reflects the horizontal variation characteristics of the stratum more truly, but the high-frequency information of the original earthquake information is lost, and the sandstone and the mudstone cannot be well distinguished vertically, the high-frequency part of the synthetic record obtained by the forward calculation of the logging information needs to be supplemented, and therefore the purpose of reconstructing the synthetic record is to obtain the seismic record which not only accords with the geological rule but also can well distinguish the sandstone and the mudstone.
And 7, performing generalized S transformation on the seismic record X (j) reconstructed in the step 6 to obtain a time frequency spectrum of the record, wherein the ordinate is time, the abscissa is a frequency range of 0-80Hz (the abscissa is frequency but has no effect, and the basis for dividing the sequence is comparing the high frequency and the low frequency), the left frequency and the right frequency are high frequencies, and the sequence stratum can be divided through the time frequency spectrum, as shown in FIG. 10.
In this step, the stratigraphic layers are divided according to the following criteria: from bottom to top, from low frequency to high frequency, corresponding to a positive convolution, as shown by the solid arrow in fig. 10; from bottom to top, from high frequency to low frequency, corresponding to a reverse rotation, as shown by the dashed arrow in fig. 10.
The sequence stratum dividing method realizes the depth fusion of the seismic information and the logging information, namely, the reconstructed wave impedance curve is used for forward modeling to obtain the seismic synthetic record, the seismic synthetic record is reconstructed with the well-crossing seismic data, the final time frequency spectrum is obtained through wavelet transformation, the sequence stratum can be divided by using the time frequency spectrum, the dividing precision is higher, and the fifth level can be divided.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (5)
1. A method of stratigraphic stratigraphy partitioning, comprising the steps of:
1) collecting a three-dimensional post-stack seismic data volume of a target work area, and determining the frequency band range of the seismic data volume; collecting the acoustic wave, density and natural gamma ray logging curves of the drilled well of the target work area;
2) calculating a wave impedance curve according to the sound wave and density logging curve obtained in the step 1);
3) performing low-pass filtering on the wave impedance curve obtained by calculation in the step 2), setting the cut-off frequency as the upper limit value of the frequency band range, and obtaining the filtered wave impedance curve;
carrying out high-pass filtering on the natural gamma curve obtained in the step 1), setting the cut-off frequency as the upper limit value of the frequency band range to obtain a filtered natural gamma curve, and carrying out value domain inversion and normalization processing on the curve;
performing product processing on the filtered wave impedance curve and the natural gamma curve after normalization processing to obtain a reconstructed wave impedance curve;
4) forward modeling is carried out by utilizing the wave impedance curve reconstructed in the step 3) to obtain a seismic synthetic record;
5) extracting well-passed seismic data according to the three-dimensional post-stack seismic data volume obtained in the step 1);
6) carrying out high-pass filtering on the seismic synthetic record obtained in the step 4), setting the cut-off frequency as the upper limit value of the frequency band range, and obtaining the filtered seismic synthetic record;
summing the filtered seismic synthetic record and the well-passing seismic data in the step 5) to obtain a reconstructed seismic record;
7) and carrying out generalized S transformation on the reconstructed seismic record to obtain a time frequency spectrum of the seismic record, and carrying out sequence stratigraphic division on the target work area by using the time frequency spectrum.
2. The method for layer-sequential stratigraphic division according to claim 1, wherein the forward modeling using the wave impedance curve reconstructed in step 3) in step 4) comprises:
performing convolution operation on the wave impedance curve reconstructed in the step 3) and the set Rake wavelets to obtain a seismic synthetic record, wherein the dominant frequency of the Rake wavelets is set according to the following steps: dominant frequency f greater than seismic datacAnd less than the sampling frequency f of the seismic data volumeN。
3. The method of stratigraphic hierarchy partitioning of claim 2, wherein the Ricker wavelets have a dominant frequency of
4. The sequence stratigraphic division method according to claim 1, characterized in that in step 3), the calculation formula of the value range inversion is as follows:
in the formula (I), the compound is shown in the specification,
the natural gamma curve value after the value range inversion, GR' (i) the natural gamma curve value before the value range inversion, and max the maximum value of the natural gamma curve before the value range inversion.
5. The sequence stratigraphic division method according to claim 4, characterized in that in step 3), the calculation formula of the normalization process is as follows:
where GR' (i) is the normalized natural gamma curve value, max is the maximum value of the natural gamma curve after the range inversion, and min is the minimum value of the natural gamma curve after the range inversion.
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