A method of constructing a lithology curve

Abstract

The application discloses a method for constructing a lithology curve, comprising the following steps: S1. classifying, assigning values to and generating a curve of a lithology interpretation result of a well; S2. standardizing a well logging curve reflecting the lithology; S3. taking the curve generated in the step S1 as a low-frequency component; taking a high-frequency component by performing high-pass filtering on the well logging curve standardized in the step S2; and superimposing and fusing the low-frequency component and the high-frequency component after dimensionless processing, and then performing standardization to obtain the lithology curve. According to the method, a parameter curve with well logging characteristics is constructed according to a lithology interpretation result, the number of wells participating in inversion in a research area is increased, and therefore, the reservoir inversion prediction precision is improved, and technical support is provided for exploration and evaluation stages, early development stages and especially unconventional reservoir prediction of a target layer with complex lithology.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology and relates to the construction of lithology curves, specifically a method for constructing lithology curves. Background Technology

[0002] Reservoir prediction technology is a specialized technique that, guided by sequence stratigraphy and sedimentology, uses seismic information as the primary basis and integrates other data (geological, well logging, rock physics, etc.) as constraints to predict the geometric characteristics, geological features, and physical properties of oil and gas reservoirs. Currently, the main technique for reservoir prediction is seismic inversion, which combines high-lateral-resolution seismic data, high-vertical-resolution well logging data, and geological data to perform seismic inversion. Interface reflection seismic data is inverted into stratigraphic parameters such as rock element impedance, and reservoir interpretation is performed targeting the rock formations. From an implementation perspective, seismic inversion can be divided into three categories: direct inversion, model-based inversion, and seismic attribute inversion. Currently, model-based inversion methods generally establish an initial model based on well logging and seismic data. Vertically, they fully utilize the high-resolution information from well logging, and horizontally, they leverage the comparability of seismic data as control, establishing a relatively reliable, high-resolution initial geological model. Forward modeling is then performed on this initial model to calculate a synthetic seismic profile. This profile is then compared with the actual seismic profile to determine the model's modification parameters. The initial model is repeatedly modified and updated until the synthetic seismic profile most closely approximates the actual seismic profile, ultimately yielding a high-resolution inversion profile. Numerous studies have confirmed that, in this process, as the number of wells involved in the inversion increases, the predicted reservoir spatial distribution tends to become more objective and realistic.

[0003] However, during the oilfield exploration and assessment phase, well control is often very low. Problems exist such as different logging ages, logging series, and logging types. In some areas, due to cost and other reasons, only logging lithology data is available without logging curves. This results in even fewer wells available for seismic geological stratigraphic calibration and inversion within the work area, and uneven planar distribution. Consequently, the planar control of inverted wells is low, the predicted sand body distribution does not align well with sedimentary patterns, and the accuracy of reservoir prediction is low.

[0004] According to research, most current methods for improving reservoir prediction accuracy are based on improvements to inversion algorithms, and none of them consider increasing the number of inversion wells to improve reservoir prediction accuracy. Summary of the Invention

[0005] The purpose of this invention is to provide a method for constructing lithology curves to solve the problem of low reservoir inversion prediction accuracy caused by the limited number of wells available for seismic geological horizon calibration and inversion.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for constructing a lithology curve includes the following steps:

[0008] S1. Classify, assign values ​​to, and generate curves for the lithological interpretation results of the well drilling;

[0009] S2. Standardization of logging curves reflecting lithology;

[0010] S3. The curve generated in step S1 is taken as the low-frequency component; the logging curve that has been standardized in step S2 is subjected to high-pass filtering, and the high frequency is taken as the high-frequency component; the low-frequency component and the high-frequency component are dimensionless, superimposed and fused, and then standardized to obtain the lithology curve.

[0011] As a limitation, the classification and assignment of lithological interpretation results from drilling in step S1 specifically includes:

[0012] The lithological interpretation results of the well were divided into two categories: sandstone and mudstone, represented by the numerical values ​​1 and 2, respectively.

[0013] As a further limitation, generating the curve in step S1 specifically includes:

[0014] The assigned discrete interpretation data is used to generate a lithological square wave curve; the lithological square wave curve is then interpolated using a cosine function to obtain the curve in question.

[0015] As a further clarification, the use of cosine function interpolation specifically includes:

[0016] The curve value 2 for the mudstone section remains unchanged. For the square wave of each sandstone section, the minimum value 1 is taken as the midpoint position. The cosine function is used for interpolation between the midpoint position and the upper and lower mudstone boundary sample points.

[0017] As a second limitation, the high-pass filtering performed in step S3 specifically includes:

[0018] In step S2, select the well logging curve that is closest to the current well or the standard well in the study area from all the standardized logging curves and perform high-pass filtering on it.

[0019] By adopting the above technical solution, the technical progress achieved by this invention compared with the prior art is as follows:

[0020] ① The present invention provides a method for constructing lithology curves, which directly uses the lithology interpretation results of wells drilled in the work area as the low-frequency components of the lithology curves after processing. This allows completed wells with only logging lithology data but no logging curves to be used for inversion. This method improves the rationality and accuracy of reservoir prediction spatial distribution in the study area by increasing the number of wells participating in the inversion.

[0021] ②The method for constructing lithology curves provided by this invention can improve the consistency of logging data from different ages and different logging series, highlight reservoirs, weaken non-reservoir areas, and significantly improve the accuracy of thin reservoir identification;

[0022] ③ The present invention provides a method for constructing lithology curves. The algorithm is simple, highly operable, and more suitable for reservoir distribution prediction in the early stages of oil reservoir exploration, evaluation, and development.

[0023] This invention provides a method for constructing lithology curves, which constructs parametric curves with well logging characteristics based on lithology interpretation results, increases the number of wells participating in the inversion in the study area, thereby improving the accuracy of reservoir inversion prediction, and provides technical support for the exploration and evaluation stage, the early stage of development, and especially for the prediction of unconventional reservoirs with complex target lithology. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the drilling lithology interpretation results in the embodiments;

[0025] Figure 2 The examples show the lithological classification results and their continuous lithological square wave curves, where... Figure 2 'a' represents the lithological classification result. Figure 2 b represents a continuous lithological square wave curve;

[0026] Figure 3 This is a comparison chart of well logging curves before and after standardization in the embodiment. Figure 3 'a' represents the logging curve before standardization. Figure 3 b represents the standardized logging curve;

[0027] Figure 4 This is a schematic diagram of lithology curves constructed at locations without well logging curves in the embodiment, wherein... Figure 4 a represents the lithological square wave curve. Figure 4 b represents the low-frequency components of the lithology curve obtained after processing. Figure 4 c represents the selected logging curve with the closest distance. Figure 4 d represents the high-frequency components of the lithology curve after high-pass filtering. Figure 4 e represents the lithology curve obtained by superimposing and fusing low-frequency and high-frequency components. Figure 4 f is the lithology curve after standardization;

[0028] Figure 5 This is a comparison diagram of the inversion profiles in the embodiment, wherein Figure 5 'a' represents the original inversion profile before adding the inversion well. Figure 5 b represents the inversion profile after adding inversion wells according to the method of this invention. Detailed Implementation

[0029] The present invention will be further described in detail below through specific embodiments. It should be understood that the described embodiments are only for explaining the present invention and do not limit the present invention.

[0030] Example: A method for constructing lithology curves

[0031] (a) Constructing lithology curves

[0032] In a certain work area, this invention was applied to construct lithology curves by combining data from all completed wells within the work area. The specific steps are as follows:

[0033] S1. Classify the lithological interpretation results of completed wells within the work area, such as... Figure 1 As shown, the non-reservoir is mudstone, and the reservoir is sandstone, which is divided into two categories: sandstone and mudstone. Sandstone and mudstone are represented by the values ​​1 and 2, respectively.

[0034] S2. The discrete interpretation data obtained in step 1 is converted into curves to generate continuous lithological square wave curves that vary with depth, such as... Figure 2 As shown, the lithological square wave curve contains only the values ​​1 and 2, where 1 represents sandstone and 2 represents mudstone.

[0035] S3. Standardize the logging curves of all reactive lithologies within the work area to ensure their values ​​are within a uniform range, such as... Figure 3 As shown, after standardization, the value range is unified to between 60 and 165, which generally conforms to a normal distribution, and is relatively concentrated between 80 and 130.

[0036] S4. For wells without logging curves, construct lithology curves for that well location: e.g. Figure 4 As shown, for the continuous lithological square wave curves of the well obtained in step S2, the curve value 2 of the mudstone section remains unchanged. For the square wave of each sandstone section, the minimum value 1 is taken as the midpoint position. The cosine function is used for interpolation between the midpoint position and the upper and lower mudstone boundary sample points. The resulting curve is used as the low-frequency component of the lithological curve. Among all known logging curves after standardization in step S3, the one closest to the current well is selected and high-pass filtered. Its high-frequency component is taken as the high-frequency component of the lithological curve. The above low-frequency and high-frequency components are dimensionless, superimposed and fused, and then standardized according to step S3 to construct the lithological curve at the well.

[0037] S5. For all wells in the work area without logging curves, complete the construction of the corresponding lithology curves according to step S4.

[0038] (ii) Verify its rationality by inverting the constructed lithology curve.

[0039] The lithology curves of all wells drilled within the work area, including both existing and constructed wells, were inverted, and the results are as follows: Figure 5As shown, this invention constructs lithology curves at wells without logging curves, and since it is independent of the age, series, type, etc. of the logging curves, all logging curves can be applied, thus increasing the number of wells participating in the inversion. As can be seen from the comparison, after adding inversion wells according to the curve construction method described in this invention, the prediction trend of sand bodies between wells changes significantly, and the vertical resolution is also improved, which significantly improves the prediction accuracy of reservoir inversion.

Claims

1. A method for constructing a lithology curve, characterized in that, Includes the following steps: S1. Classify and assign values ​​to the lithological interpretation results of the well drilling, and generate lithological square wave curves from the assigned discrete interpretation conclusion data; interpolate the lithological square wave curves using cosine functions to obtain the logging curves that reflect the lithology; S2. Standardization of logging curves reflecting lithology; S3. Take the curve generated in step S1 as the low-frequency component; select the one closest to the current well from all known logging curves after standardization in step S2 and perform high-pass filtering on it, taking its high-frequency component as the high-frequency component for constructing the lithology curve; after dimensionless transformation of the low-frequency and high-frequency components, superimpose and fuse them, and perform standardization to obtain the lithology curve.

2. The method for constructing a lithology curve according to claim 1, characterized in that, The classification and assignment of lithological interpretation results from drilling in step S1 specifically includes: The lithological interpretation results of the well were divided into two categories: sandstone and mudstone, represented by the numerical values ​​1 and 2, respectively.

3. The method for constructing a lithology curve according to claim 2, characterized in that, The cosine function interpolation specifically includes: The curve value 2 for the mudstone section remains unchanged. For the square wave of each sandstone section, the minimum value 1 is taken as the midpoint position. The cosine function is used for interpolation between the midpoint position and the upper and lower mudstone boundary sample points.

4. The method for constructing a lithology curve according to claim 3, characterized in that, In step S2, the logging curves of all reactive lithologies in the work area are standardized so that their value range is within a uniform range and the overall value range conforms to a normal distribution.

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