Method for dividing terrigenous clastic rock formations

Abstract

The application provides a method for dividing terrigenous clastic rock strata, which comprises the following steps: analyzing geological and logging data, and selecting logging curves Log which are sensitive to terrigenous clastic rock lithology and sedimentary cycle; using maximum overlap wavelet transform to decompose the logging curves into multiple frequency bands, and establishing a decomposition coefficient matrix based on depth domain and frequency band domain; starting from the depth domain, calculating maximum value and information entropy curves as a basis to divide the geological horizon of typical wells in the work area; taking the maximum value curve as a basis, and taking the adjacent typical well as a reference template, the geological horizon of other wells in the work area is divided by using the combination of the whole curve and the local curve comparison. The application combines the geological principle and the mathematical method, extracts more effective information which can reflect the lithology and the sedimentary cycle, reduces the requirement for the experience of personnel, and further improves the working efficiency of the stratum division by using the similarity of the logging curves in the same sedimentary environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas reservoir description and reservoir evaluation, in particular to a method for dividing terrigenous clastic rock strata. BACKGROUND

[0002] Strata division is a key technology in fine oil and gas reservoir description and is a basic work of oil and gas reservoir geological research. The reason why the strata division by using well logging curves is the most practical way is that, first of all, well logging curves, especially conventional well logging curves (natural gamma ray GR, natural potential SP, acoustic AC and resistivity R, etc.), are the most common data in the process of oil and gas exploration and development, and secondly, well logging curves comprehensively reflect various physical properties of underground geological bodies and record various changes of sedimentary environment in the sedimentary process, which are extremely representative.

[0003] At present, the strata division based on well logging curves mainly uses the curve characteristics (waveform, extreme value, zero-crossing value, etc.) or mathematical statistics values (mean value, variance, etc.) of well logging curves, and is divided into two categories of characteristic analysis method and mathematical statistics method, which takes mathematical method as the entry and mainly relies on mathematical tools and personnel experience. For terrigenous clastic rocks, well logging curves are affected by sedimentary cycles, and well logging curves in the same sedimentary environment often have obvious similarity. Especially in the re-evaluation of oil and gas reservoirs in the later stage of exploration and development, a large amount of data is usually involved, the number of drilled wells is huge, the data span is long, the basic data has large difference, the workload of geological horizon division is increased, the standard is difficult to unify, the division difficulty is increased, and the personnel experience is required to be improved.

[0004] Therefore, how to efficiently and accurately realize strata division has great practical significance. SUMMARY

[0005] The present application aims to solve at least one of the above-mentioned deficiencies in the prior art. For example, one of the purposes of the present application is to provide a method for effectively realizing strata division by combining geological principles and mathematical tools, the second purpose of the present application is to reduce the dependence on personnel experience in the process of strata division, and the third purpose of the present application is to provide a strata division method considering the lithology and sedimentary cycles of terrigenous clastic rock well logging curves.

[0006] In order to achieve the above-mentioned purposes, the present application provides a method for dividing terrigenous clastic rock strata, which comprises the following steps:

[0007] Analyzing geological and well logging data and selecting well logging curves Log sensitive to terrigenous clastic rock lithology and sedimentary cycles;

[0008] Using maximum overlap wavelet transform to decompose the well logging curves Log into multiple frequency bands and establishing a decomposition coefficient matrix based on depth domain and frequency band domain;

[0009] The maximum value curve and the information entropy curve of the decomposition coefficient matrix are calculated from the depth domain, and the calculated curves are used as a basis for geological horizon division of typical wells in the work area.

[0010] The maximum value curve is used as a basis, and the geological horizon division of other wells in the work area is performed by curve comparison using the nearby typical wells as a template.

[0011] Alternatively, the calculation of the maximum value and the information entropy curve includes calculation of the information entropy curve of the decomposition coefficient, the information entropy curve of the absolute value of the decomposition coefficient, and the maximum value curve, respectively.

[0012] Alternatively, the typical well is selected from a typical well set.

[0013] Alternatively, the typical well set establishment parameters include plane position and logging curve quality.

[0014] Alternatively, the plane position parameter includes a plane uniform distribution parameter.

[0015] Alternatively, the typical well geological horizon division basis includes the maximum value curve, the information entropy curve, and the stratum sedimentary cycle.

[0016] Alternatively, the curve comparison method includes curve overall comparison and local scaling comparison methods.

[0017] Alternatively, the other well geological horizon division basis also includes layer thickness relationship and stratum isochronism.

[0018] Compared with the prior art, the beneficial effects of the present application include at least one of the following:

[0019] 1) The present application combines geological principles with mathematical methods to extract more effective information that can reflect lithology and sedimentary cycles.

[0020] 2) The present application highlights the features in the original curve related to stratum division, which can reduce the requirement for personnel experience to a certain extent, and has a positive significance for terrigenous clastic rock stratum division.

[0021] 3) The present application radiates from the typical well to the surrounding wells, expands to the entire work area, and makes greater use of the similarity of logging curves in the same sedimentary environment, further improving the working efficiency of stratum division. BRIEF DESCRIPTION OF DRAWINGS

[0022] The above and other objects and / or characteristics of the present application will become more apparent by describing the present application with reference to the accompanying drawings, wherein:

[0023] Figure 1 A flowchart of the stratum division method in Example 1 of the present application is shown.

[0024] Figure 2 The GR curve, the decomposition coefficient of the maximum overlap wavelet transform of the GR curve, the information entropy of the decomposition coefficient absolute value, the information entropy of the decomposition coefficient and the maximum value curve of the decomposition coefficient absolute value in Example 1 of the present application are shown in the graph.

[0025] Figure 3 The stratigraphic division scheme of a typical well in Example 1 is shown in the graph.

[0026] Figure 4 The stratigraphic division scheme of other new wells in Example 1 in reference to the adjacent typical well is shown in the graph. DETAILED DESCRIPTION

[0027] In the following, the method for dividing terrigenous clastic rock strata of the present application will be described in detail in combination with exemplary embodiments.

[0028] Exemplary Embodiments

[0029] The exemplary embodiments provide a method for dividing terrigenous clastic rock strata, which comprises the following steps:

[0030] S10: Analyzing geological and logging data and selecting logging curves Log sensitive to terrigenous clastic rock lithology and sedimentary cycle.

[0031] In the present embodiment, based on the analysis of geological and logging data, logging curves Log sensitive to terrigenous clastic rock lithology and sedimentary cycle are selected.

[0032] S20: Decomposing the logging curves Log into multiple frequency bands by using maximum overlap wavelet transform and establishing a decomposition coefficient matrix based on depth domain and frequency band domain.

[0033] In the present embodiment, the logging curves Log are decomposed into multiple frequency bands by using maximum overlap wavelet transform (MODWT) and a decomposition coefficient matrix based on depth domain and frequency band domain is established. The feature of this step is to improve the accuracy of frequency analysis and reduce the influence of boundary effect while maintaining the depth and frequency resolution.

[0034] S30: Starting from the depth domain, calculating the maximum value and information entropy curve of the decomposition coefficient matrix and using the calculated curve as the basis to divide the geological horizon of the typical well in the work area.

[0035] In the present embodiment, starting from the depth domain, the information entropy curve of the decomposition coefficient, the information entropy curve of the decomposition coefficient absolute value and the maximum value curve of the decomposition coefficient absolute value are calculated respectively by using the decomposition coefficient matrix. From the perspective of plane position and curve quality, the principle of plane uniform distribution and excellent logging curve quality is taken into account to establish a typical well set A = {A1, A2, …, An} and a reference well set B = {B1, B2, …, Bn}. M}(M≥1), using the maximum curve and the information entropy curve, combined with the stratum sedimentary cycle, single well geological horizon division is carried out, and single well geological horizon division of a typical well set is realized.

[0036] S40: Based on the maximum curve, using the curve correlation method, the geological horizon division of other wells in the work area is carried out by taking the adjacent typical well as a template.

[0037] In the embodiment, for other wells in the work area, the nearby typical well A i Based on the maximum curve, combined with the layer thickness relationship and the stratum isochronism, the curve overall correlation and the local scaling correlation are combined, and the full-area geological horizon division is completed.

[0038] The key of the embodiment is to analyze the geological and logging data, select the logging curve sensitive to the lithology and sedimentary cycle of the terrigenous clastic rock, decompose the curve into multiple frequency bands by using the maximum overlap wavelet transform, calculate the maximum value and information entropy curve from the depth domain; based on this, the geological horizon division of the typical well in the work area is implemented, and for other wells in the work area, the maximum curve is taken as the reference template, and the curve correlation method is used to complete the geological horizon division.

[0039] In order to better understand the above-mentioned exemplary embodiments of the present application, the following further illustrates them with specific examples.

[0040] Example 1

[0041] The present example provides a terrigenous clastic rock stratum division method, which is applied to an actual work area, such as Figure 1 As shown in the figure, it is a flowchart of the terrigenous clastic rock stratum division method.

[0042] Collect the geological and logging data in the work area, determine the target layer and the main lithology of the stratum division. The stratum in the area is mainly composed of sandstone and mudstone, and accordingly the natural gamma (GR) is selected as the basis curve for the stratum division.

[0043] The maximum overlap wavelet transform is used to decompose the GR curve into multiple frequency bands {W 1 ,W 2 ,…W L}, and a 2D decomposition coefficient matrix based on the depth domain and the frequency domain is constructed Wherein N is the number of GR curve samples, L is the number of frequency bands, L≤log2(N), L value is large, which represents high frequency, and L value is small, which represents low frequency.

[0044] The decomposition coefficient matrix W is used to calculate the information entropy along the matrix row, and the decomposition coefficient absolute value matrix |W| is used to calculate the information entropy and the maximum value curve along the matrix row, which is used for later stratum division. Figure 2is the test curve of a well in the work area, as shown in Figure 2 , which respectively shows the marked MD as the depth, the marked GR as the original GR curve, the marked MODWT as the maximum overlap wavelet transform decomposition coefficient of the GR curve, the frequency is lower from left to right, the marked EnM GR as the information entropy of the decomposition coefficient absolute value, the marked EnR GR as the information entropy of the decomposition coefficient, and the marked ABS GR as the maximum value of the decomposition coefficient absolute value. The maximum value curve ABS GR is divided into a low frequency band (black curve) and a full frequency band (gray filling), that is, the maximum value is calculated in the low frequency band (1-5) and the full frequency band (1-L) respectively.

[0045] In this example, Shannon entropy is selected as the information entropy calculation, that is,

[0046]

[0047] , where p represents the probability of occurrence of x i .

[0048] Considering the factors such as stratum collapse of drilling, taking into account the principle of uniform distribution in the plane, screening multiple wells with excellent curve quality, establishing a typical well set A = {A1, A2, …, A M} (M≥1), using the maximum value and information entropy curve, combining with the stratum sedimentary cycle, realizing the single well geological horizon division of the typical well. Figure 3 is a stratum division scheme diagram of a typical well, as shown in Figure 3 , in which A area is divided into 4 rock stratum groups according to the absolute value maximum value curve, which shows the depth, original GR curve, information entropy of decomposition coefficient absolute value, information entropy of decomposition coefficient, maximum value of decomposition coefficient absolute value and stratum group division result of each stratum group.

[0049] The maximum value of the decomposition coefficient absolute value contains two types of low frequency band and full frequency band. The change rule of the maximum value curve in each stratum group is consistent, and it is obviously different between different stratum groups, which is similar to the concept of geological sedimentary cycle. Figure 3 In area B, ③ and ④ in area A are taken as the main target stratum groups according to the research target of the area, and according to the information entropy and maximum value curve, stratum group ③ is further subdivided into 4 stratum sections, and stratum group ④ is further subdivided into 5 stratum sections, so as to meet the requirements of later reservoir description and reserve calculation. Figure 3 In area B, it can be seen that the interfaces of each stratum section basically correspond to the obvious information entropy curve change interface, and the change rule of the maximum value curve in the same section is similar.

[0050] In this example, the formation section division takes into account the inflection point of information entropy curve, the maximum value curve change and the relationship between formation thickness. For example, the bottom boundary of the first section of the formation group ③ is located at the inflection point of the decomposition coefficient information entropy, the information entropy below it changes from small to large, the information entropy above it changes from large to small, and the maximum value in this section basically changes from large to small.

[0051] In this example, other wells in the work area need to be referenced from the typical well, and then spread from point to surface. Based on the maximum value curve, combined with the change of formation thickness and the isochronism of formation, the curve comparison method is used to realize the division of geological horizon in the whole area. Figure 4 The formation division scheme of a new well without geological horizon is shown. First, the adjacent typical well is referenced, and the maximum value curves (ABS_GR) of the two wells are directly compared to roughly determine the geological stratification; second, the ABS_GR curve of the reference well is segmented and scaled, and then compared with the ABS_GR curve of the new well to refine and adjust the geological stratification; finally, the geological stratification scheme of the new well is determined.

[0052] Figure 4 The GR curve of the new well in the middle A area and the calculated curve are shown. Figure 4 The black curve in the middle B area is the ABS_GR curve of the new well, and the light gray is the ABS_GR curve of the known typical well (the superimposed horizontal line is the geological stratification of the typical well). The two curves correspond well as a whole, especially in the 3695m-3770m section. Figure 4 The ABS_GR curve of the typical well in the middle C area is scaled and compared with the ABS_GR curve of the new well. For example, the characteristics of the two curves are highly similar in the 3741m section, but there is still a significant thickness difference. At this time, the ABS_GR curve segment of the reference well is appropriately compressed, which can improve the comparability of the two curves and better meet the consistency of the local geological stratification. Figure 4 The final geological scheme of the new well is shown in the middle D area. The original GR curve does not change significantly in the 3695m-3730m section, showing a large section of mudstone, which is not easy to determine the specific horizon interface position. However, through the GR curve calculation and reference well comparison method, the specific position of the geological stratification can be quickly located. Through such a geological division method, both geological principles and mathematical methods are considered, and the characteristics of the original logging curve related to the geological horizon are highlighted.

[0053] Although the present application has been described above with reference to the example embodiments and the accompanying drawings, it should be clear to those skilled in the art that various modifications can be made to the above embodiments without departing from the spirit and scope of the claims.

Claims

1. A method of dividing a terrigenous clastic formation, characterized by, The method comprises the following steps: analyzing geological and logging data to select logging curves sensitive to lithology and sedimentary cycle of terrigenous clastic rocks; decomposing the logging curves into multiple frequency bands by using maximum overlap wavelet transform to establish a decomposition coefficient matrix based on depth domain and frequency band domain; starting from the depth domain, calculating a maximum value curve and an information entropy curve of the decomposition coefficient matrix, and taking the calculated curves as a basis to divide geological horizons of typical wells in the work area; based on the maximum value curve, taking into account the maximum turning point of the information entropy curve, and taking the nearby typical wells as templates, dividing geological horizons of other wells in the work area by using curve comparison; the calculation of the maximum value curve and the information entropy curve comprises respectively calculating an information entropy curve of the decomposition coefficient, an information entropy curve of the absolute value of the decomposition coefficient, and a maximum value curve; the division of the geological horizons of the typical wells is based on the maximum value curve, the information entropy curve, and the sedimentary cycle of the strata; the curve comparison mode comprises overall curve comparison and local scaling comparison.

2. The method of claim 1, wherein, The typical wells are selected from a typical well set.

3. The method of claim 2, wherein, The establishment parameters of the typical well set include plane position and logging curve quality.

4. The method of claim 3, wherein, The parameters of the plane position include plane uniform distribution parameters.

5. The method of claim 1, wherein, The division of the geological horizons of the other wells is also based on layer thickness relationship and strata isochronism.

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