CN112162332A - Deposition evolution analysis method based on time-frequency convolution - Google Patents
Deposition evolution analysis method based on time-frequency convolution Download PDFInfo
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Abstract
The invention relates to a deposition evolution analysis method based on time-frequency convolution. According to the invention, time-frequency characteristic analysis is carried out through a multi-channel frequency scanning technology, well-connected time-frequency convolution comparison is carried out by combining well drilling data, an interface of a layer system is determined to establish an isochronous stratigraphic contrast framework, and time-frequency convolution models corresponding to different deposition environments are established on the basis; and matching the deposition models corresponding to the target interval in blocks according to a multi-channel time-frequency change rule scanned by the seismic data frequency, and performing longitudinal deposition evolution analysis on the non-drilled part. And then comparing the deposition evolution rules of the areas with drilled wells and areas without drilled wells in a transverse connection manner to complete the planar deposition evolution analysis under the control of multi-stage convolution. The invention can effectively utilize the transverse control function of seismic data in the gyroid comparison, thereby improving the analysis precision of the sedimentary evolution and finding a favorable reservoir development area for the exploration and development of oil fields.
Description
Technical Field
The invention relates to the field of petroleum exploration, in particular to a sedimentary evolution analysis method based on time-frequency convolution.
Background
In the process of oil and gas field exploration and development, the research precision of sedimentary facies with different scales plays an important role in searching for favorable reservoir development areas, and indirectly influences the exploration and development production benefits of oil fields.
Conventional depositional evolution analysis methods are generally based on rock combination, depositional structure construction, depositional sequence and logging response of core observation. For example, the convolution contrast method is a method which is widely used. The periodic lifting motion of the crust causes the advance and retreat of seawater on the crust and the similar and repeated change of the sedimentary environment, so that the rock property changes regularly in the longitudinal direction, the phenomenon that the rock property appears regularly and repeatedly is reflected on the stratum section and called the cycle property of sedimentary rock, and the cycle can be divided into a plurality of stages from large to small. Specifically, the gyration comparison method reflects the shale content through a logging curve, increases the shale content and reduces the energy of reaction sediments so as to divide positive and negative gyrations, and then the stratum can be divided according to the positive and negative levels of the gyrations. However, in the prior art, the positive and negative gyrations are divided directly based on the shale content reflected by the logging data, so that the stratum division processing is only applicable to the division of the stratum with obvious sand-shale change, for the areas with thin reservoir thickness, quick transverse change, poor connectivity and unobvious stratum contrast characteristics, the logging response discrimination is low, the stratum cannot be accurately divided, and the stratum is often influenced by the subjective consciousness of people, so that the analysis difficulty is high. Especially in the well area with less drilling data, the accuracy of the analysis result is greatly reduced. Therefore, how to improve the accuracy of the sedimentary evolution analysis result in the well region with less drilling data and fast reservoir transverse change in the production work of the oil field is a problem to be solved urgently in a plurality of continental basins with low exploration degree in China.
Disclosure of Invention
The application aims to provide a deposition evolution analysis method based on time-frequency convolution, which is used for solving the problem of low precision in the prior art.
In order to achieve the purpose, the invention provides a deposition evolution analysis method based on time-frequency convolution, which comprises the following steps:
1) performing time-frequency analysis on the target interval of the multiple single wells by adopting a multi-channel frequency scanning technology;
2) combining well drilling data to carry out well-connecting time-frequency convolution comparison, and determining interfaces among sand groups of the layer system so as to establish an isochronous stratigraphic comparison framework;
3) establishing time-frequency convolution models corresponding to different deposition environments by integrating the data of a plurality of single wells;
4) and matching the deposition models corresponding to the target intervals in blocks according to the seismic time-frequency gyrogram at the non-drilling position, performing longitudinal deposition evolution analysis at the non-drilling position, comparing the deposition evolution rules at the multi-port drilled and non-drilled regions in a transverse connection manner, and completing the planar deposition evolution analysis under the multi-stage gyrogram control.
The sedimentary evolution analysis based on time-frequency convolution can effectively utilize the transverse control function of seismic data in convolution comparison, and analyze the ancient hydrodynamic force change and the sedimentary evolution rule through time-frequency convolution characteristics of different scales of seismic channels. Therefore, the analytical precision of the sedimentary evolution is improved, and a favorable reservoir development area is found for the exploration and development of the oil field.
The sedimentary evolution analysis based on time-frequency convolution combines the frequency characteristics of the seismic data with the actual geologic body, and reflects the structural relationship of the actual geologic body by using the change rule of the frequency characteristics of the seismic data on the space. The method can effectively utilize the transverse control function of the seismic data in the convolution comparison, and analyze hydrodynamic force change and deposition evolution by analyzing time-frequency convolution characteristics of different scales of the seismic channels. The analytical precision of the sedimentary evolution is improved, a favorable reservoir development area is found for the exploration and development of the oil field, and the method is a practical and efficient technical method in the production process of the exploration and development of the oil field. The method solves the problems of less well drilling data and low accuracy of well deposition evolution analysis results of reservoir stratum with rapid transverse change.
Further, the time-frequency analysis method applied in the step 1) is wavelet transformation.
Further, the time-frequency analysis method applied in the step 3) is wavelet transformation.
Further, the time-frequency convolution models corresponding to different deposition environments include: time-frequency convolution models of an accumulation-entering type, an accumulation-removing type and an accumulation-adding type.
Drawings
FIG. 1 is a technical scheme of an embodiment of the method of the present invention;
FIG. 2 is a time-frequency convolution analysis of a single well for well 1 in an embodiment of the present invention;
FIG. 3 is a schematic illustration of a well-to-well stratigraphic comparison grid for wells 1-2 in an embodiment of the present invention;
FIG. 4 is a time-frequency convolution model diagram corresponding to different deposition environments of the exploration area in the embodiment of the present invention.
Detailed Description
The method for analyzing deposition evolution based on time-frequency convolution is specifically described below with reference to the accompanying drawings and examples, as shown in fig. 1, and includes the following steps:
1) and performing time-frequency analysis on the target interval of the multiple single wells by adopting a multi-channel frequency scanning technology.
Firstly, time-frequency analysis is carried out on a plurality of single wells in a exploration area. As shown in fig. 2, the chalk-based formation of the well 1 is taken as an example. The chalk system stratum of the target work area is fine in overall lithology, the interbedded shale and siltstone are mainly used, and the main deposition types are near bank development fan delta, far bank development braided river delta and a beach dam developed at the tail end of the delta. According to lithological combination and well logging curve characteristics of a plurality of drilling data, the interior of a chalk system is correspondingly divided into five sand groups from bottom to top: the sand group I (K1), the sand group II (K2), the sand group III (K3), the sand group IV (K4) and the sand group V (K5). As can be seen from the time-frequency gyrogram of the seismic trace through the well, the chalk line appears as a complete water in-water back-out. Wherein the chalk system I sand group-IV sand group is in the water inlet period and shows the positive gyrus characteristic of the detritus type; the final stage of the sand group IV deposition is the maximum lake flooding period; chalky group V sands are water-receding periods characterized by accumulation-type reverse rotation.
The principle of time-frequency analysis is to reflect the structural relationship of the actual geologic body by using the change rule of the frequency characteristics of the seismic data on the space. The invention adopts a wavelet transform method and a multi-channel frequency scanning technology to carry out time-frequency analysis, and can expand one-dimensional time domain seismic wave signals to a two-dimensional time-frequency domain. The adopted triangular filter can not only highlight the dominant frequency of the scanning area, but also give consideration to the gradual change of the frequency characteristics.
2) And performing well-connecting time-frequency convolution comparison by combining with well drilling data to determine the interface of the layer system and establish an isochronous stratigraphic comparison framework.
And performing transverse comparison according to a time-frequency gyrogram of a plurality of drilled seismic channels passing through the well and well data, and determining interfaces among sand groups among the layer series so as to establish a stratum framework of a chalk system of the area. And analyzing the main corresponding lithological structural characteristics and seismic reflection characteristics (figure 3). The chalk-V sand group in the area mainly develops a large set of gray and variegated mudstone with a thin layer of gray siltstone, and locally develops brown gray and gray conglomerate with a thin layer of green mudstone near the stratum pinch-out line; the seismic profile exhibits medium amplitude features of medium continuity. The chalky line IV sand group mainly develops a gray, variegated mudstone and siltstone interbedded layer, and a large set of light gray grave-containing fine sandstone sandstones and gray-containing green mudstone locally develops near a stratum pinch-out line; the seismic section shows a relatively continuous medium-strength amplitude characteristic. The chalky system III sand group mainly develops gray, variegated mudstone and siltstone interbedded layers, locally develops a large set of gray brown and gray gravelly-containing fine sandstone and gritty rock laminated layer gray green mudstone near a stratum pinch-out line, and shows weak continuous medium-amplitude characteristics on an earthquake section. The chalky line ii sand group developed primarily a gray, variegated mudstone and siltstone interbedded layer, exhibiting a weakly continuous weak amplitude characteristic on seismic sections. The chalky system I sand group mainly develops a gray green mudstone and siltstone interbedded, and locally develops a thin layer of dark gray glutenite, which shows weak continuous medium amplitude characteristics on an earthquake section.
3) And synthesizing the data of a plurality of single wells, analyzing the change rule of seismic signal time-frequency graphs corresponding to different deposition models, and respectively establishing time-frequency convolution models.
The different deposition environments determine the difference of the change trend of the rock structure, and three main deposition modes of volume advancing, volume receding and volume adding are summarized. The time-frequency cycle template can be established by utilizing the characteristic that the moving direction of the energy group in the time-frequency graph has the same change trend with the rock structure, so that the corresponding relation between different deposition models and the time-frequency cycle characteristic is realized. Therefore, the relation between the energy mass and the deposition model is established according to the change of the amplitude energy mass in the time-frequency gyrogram. Thereby obtaining time-frequency convolution models in three main deposition environments in the work area. As shown in FIG. 4, (a), (b), (c) and (d) are time-frequency convolution features of inverse product type, inverse product-inverse product type and additive product type, respectively.
When the analysis frequency changes from left to right from low frequency to high frequency, the amplitude energy mass in each deposition period gradually moves towards the right with high frequency, which represents that the thickness of the stratum becomes thinner gradually from bottom to top in the deposition period, the deposition cycle reflecting positive rhythm represents the process that the hydrodynamic condition is from strong to weak, and the sediment granularity is from coarse to fine. When the analysis frequency changes from left to right from high frequency to low frequency, the amplitude energy mass in each deposition period gradually moves to the low frequency at the right side, which represents that the thickness of the stratum gradually thickens from bottom to top in the deposition period, and the deposition cycle of the reaction counter rhythm represents the process that the hydrodynamic condition is from weak to strong and the granularity of the sediment is from thin to thick.
Step 1), in step 3), the time frequency transformation applies wavelet transformation technology, mainly because it overcomes the defects of poor locality of Fourier time frequency domain and fixed time frequency resolution, and can perform time frequency analysis on signals under the condition of multi-scale and multi-resolution. Thereby more clearly depicting the convolution structure characteristics inside the sediment body in the frequency spectrum diagram. There is also an oscillatory secondary convolution process throughout the primary convolution.
4) And matching the deposition models corresponding to the target intervals in blocks according to the seismic time-frequency gyrogram at the non-drilling position, performing longitudinal deposition evolution analysis at the non-drilling position, comparing the deposition evolution rules at the multi-port drilled and non-drilled regions in a transverse connection manner, and completing the planar deposition evolution analysis under the multi-stage gyrogram control.
Chalk is the deposition period, the area begins to settle rapidly, and the lake range gradually expands. The I sand group mainly takes lake facies deposition as main, west develops fan delta deposition, east and north develops small braided river delta deposition, the rest develops small beach dam deposition along the bank, and the sand body trend is parallel to the lake shoreline. And when the sand group II and the sand group III are in the period, the lake range is continuously expanded, and the east braided river delta range is expanded. IV, the lake range reaches the maximum in the sand group period, three fandelta bodies and a braided river delta body mainly develop, the fandelta is developed in the northeast, the braided river delta is developed in the east and south, and the sweep range extends to the underwater ancient raised area in the south. And V, in the sand group deposition period, the range of the lake basin begins to shrink, the underwater ancient heaves disappear, the range of the two fan bodies in the northwest part is further expanded, and the fan delta bodies in the southwest part are pushed towards the east part. Therefore, the south of the exploration area is a favorable reservoir development area in the period of the Chalkbrook series III sand group, lithologic trap of sand deposit type of the beach dam is identified by combining a geophysical prospecting technology, and three wells drilled in later period deployment all obtain high-yield industrial oil flow in the target layer.
The method solves the problems of less well drilling data and low accuracy of well deposition evolution analysis results of reservoir stratum with rapid transverse change. The analysis precision of the sedimentary evolution is improved by effectively utilizing the transverse control action of the seismic data in the gyroid comparison, a favorable reservoir development area can be found for the exploration and development of an oil field, and a well position deployment basis is provided.
Claims (4)
1. A sedimentary evolution analysis method based on time-frequency convolution is characterized by comprising the following steps:
1) performing time-frequency analysis on the target interval of the multiple single wells by adopting a multi-channel frequency scanning technology;
2) combining well drilling data to carry out well-connecting time-frequency convolution comparison, and determining interfaces among sand groups of the layer system so as to establish an isochronous stratigraphic comparison framework;
3) establishing time-frequency convolution models corresponding to different deposition environments by integrating the data of a plurality of single wells;
4) and matching the deposition models corresponding to the target intervals in blocks according to the seismic time-frequency gyrogram at the non-drilling position, performing longitudinal deposition evolution analysis at the non-drilling position, comparing the deposition evolution rules at the multi-port drilled and non-drilled regions in a transverse connection manner, and completing the planar deposition evolution analysis under the multi-stage gyrogram control.
2. The time-frequency convolution-based depositional evolution analysis method of claim 1, wherein the time-frequency analysis method applied in step 1) is wavelet transform.
3. The time-frequency convolution-based depositional evolution analysis method of claim 1, wherein the time-frequency analysis method applied in step 3) is wavelet transform.
4. The method for time-frequency convolution-based depositional evolution analysis of claim 1, wherein the time-frequency convolution models corresponding to different depositional environments comprise: time-frequency convolution models of an accumulation-entering type, an accumulation-removing type and an accumulation-adding type.
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Citations (3)
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| CN102520448A (en) * | 2012-01-06 | 2012-06-27 | 中国石油化工股份有限公司胜利油田分公司西部新区研究中心 | System for calibrating well earthquakes in chronostratigraphic cycle domain |
| US20140297188A1 (en) * | 2013-03-29 | 2014-10-02 | Cgg Services Sa | Time-frequency representations of seismic traces using wigner-ville distributions |
| CN111665567A (en) * | 2019-03-05 | 2020-09-15 | 中国石油化工股份有限公司 | Logging site beach dam facies sand body fine prediction method |
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| CN102520448A (en) * | 2012-01-06 | 2012-06-27 | 中国石油化工股份有限公司胜利油田分公司西部新区研究中心 | System for calibrating well earthquakes in chronostratigraphic cycle domain |
| US20140297188A1 (en) * | 2013-03-29 | 2014-10-02 | Cgg Services Sa | Time-frequency representations of seismic traces using wigner-ville distributions |
| CN111665567A (en) * | 2019-03-05 | 2020-09-15 | 中国石油化工股份有限公司 | Logging site beach dam facies sand body fine prediction method |
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