Fracture identification method based on natural gamma and micro-lateral resistivity conventional logging curves

Abstract

The present application relates to the technical field of fracture identification method, and is a fracture identification method based on natural gamma and micro-lateral resistivity conventional logging curves, which comprises the following steps: obtaining a natural gamma logging curve of a fracture section to be identified and a micro-lateral resistivity curve of the fracture section to be identified; selecting a layer section position with low natural gamma and low resistivity, keeping the natural gamma curve scale unchanged, adjusting the micro-lateral resistivity scale to make the natural gamma curve section and the resistivity curve section overlap; positively filling in a curve section with increased natural gamma and decreased micro-lateral resistivity; negatively filling in a curve section with decreased natural gamma and increased micro-lateral resistivity; and obtaining fracture development data of the fracture section to be identified after positive filling and negative filling. The present application is a method for intuitively identifying a fracture development section by simply mirroring and arranging logging multi-parameters, and the method improves the identification degree of the fracture development section in the vertical direction of a single well.

Description

Technical Field

[0001] This invention relates to the field of fracture identification methods, specifically a fracture identification method based on conventional logging curves using natural gamma and microlateral resistivity. Background Technology

[0002] In the current exploration of unconventional oil and gas reservoirs (shale oil and shale gas), fractures are effective storage spaces and main seepage channels for reservoir oil and gas. At the same time, as an important controlling factor for improving reservoir properties (porosity and permeability) and one of the most important bases for fracturing technology in unconventional exploration engineering, fractures are receiving increasing attention.

[0003] Currently, identifying fractures formed during diagenesis in a single well is quite difficult. The current approach mainly focuses on various response characteristics that are sensitive to fractures, including core data, imaging logging data, and radioactive element data. However, these data suffer from problems such as high acquisition costs, low depth coverage, and limited data availability.

[0004] The innovative achievement of this invention is a fracture identification method based on conventional logging curves. Conventional logging data is commonly available during the oilfield exploration and development stage. Although it has lower fracture identification accuracy compared to other fracture identification methods, conventional logging data has advantages such as low acquisition cost, wide data coverage depth range, and simple identification method. It plays a key supporting role in the exploration and development of unconventional oil and gas reservoirs. Summary of the Invention

[0005] This invention provides a method for identifying fractures based on conventional logging curves using natural gamma and micro-lateral resistivity, which overcomes the shortcomings of the prior art and can improve the identification accuracy of fracture development sections in the longitudinal direction of a single well.

[0006] The technical solution of this invention is achieved through the following measures: a method for identifying fractures based on conventional logging curves using natural gamma and micro-lateral resistivity, comprising the following steps:

[0007] (1) Obtain the natural gamma logging curve and the micro lateral resistivity curve of the fracture segment to be identified;

[0008] (2) Select the layer segment position with low natural gamma and low resistance, keep the natural gamma curve scale unchanged, and adjust the micro lateral resistivity scale so that the natural gamma curve segment overlaps with the micro lateral resistivity curve segment.

[0009] (3) In the curve segment where the natural gamma value increases and the micro lateral resistivity value decreases, the natural gamma and micro lateral resistivity are positively filled; in the curve segment where the natural gamma value decreases and the micro lateral resistivity value increases, the natural gamma and micro lateral resistivity are negatively filled; after positive and negative filling, the crack development data of the crack segment to be identified is obtained.

[0010] The following are further optimizations and / or improvements to the above-mentioned technical solution:

[0011] In step (3) above, in the obtained fracture development data, the positive filling curve segment represents the fracture development segment, indicating that the fracture is well developed and the permeability is good; the negative filling or coincident curve segment represents the fracture non-developed segment, indicating that the fracture is non-developed and the permeability is poor.

[0012] In step (2) above, a position with low natural gamma and low resistivity is selected in the curve segment corresponding to the pure sandstone layer.

[0013] In step (2) above, the linear scale of the natural gamma curve is kept unchanged, and the logarithmic scale of the micro-lateral resistivity is adjusted so that the natural gamma curve segment overlaps with the micro-lateral resistivity curve segment.

[0014] This invention provides a method for intuitively identifying fracture development sections by simply mirroring multiple logging parameters. Based on obtaining natural gamma and micro-lateral resistivity logging values ​​at different depths, the method displays the curves of these two parameters as an overlap. By performing positive and negative filling on fracture development sections and non-developed sections respectively, a single display method for identifying fracture development sections is obtained. This method improves the longitudinal identification accuracy of fracture development sections in a single well and exhibits good consistency with core data and imaging logging data. Furthermore, the parameter selection in this invention is intuitive and reliable, the operation is simple, and no function conversion is required, greatly improving the convenience and objectivity of single-well fracture identification. Attached Figure Description

[0015] Appendix Figure 1 The images show conventional logging curves and fracture identification diagrams using natural gamma and micro-lateral resistivity mirroring methods, representing embodiments of the present invention.

[0016] In the attached figures, the first and third to fourth columns are conventional logging curves, the second column is the depth, the fifth column is the mirror image of natural gamma (GR) and micro lateral resistivity (RXO), the sixth column is the high-angle fracture and oblique fracture, and the seventh column is the bedding fracture. Detailed Implementation

[0017] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0018] The present invention will be further described below with reference to embodiments:

[0019] Example 1: This fracture identification method based on conventional logging curves using natural gamma and micro-lateral resistivity includes the following steps:

[0020] (1) Obtain the natural gamma logging curve and the micro lateral resistivity curve of the fracture segment to be identified;

[0021] (2) Select the layer segment position with low natural gamma and low resistance, keep the natural gamma curve scale unchanged, and adjust the micro lateral resistivity scale so that the natural gamma curve segment overlaps with the micro lateral resistivity curve segment.

[0022] (3) In the curve segment where the natural gamma value increases and the micro lateral resistivity value decreases, the natural gamma and micro lateral resistivity are positively filled; in the curve segment where the natural gamma value decreases and the micro lateral resistivity value increases, the natural gamma and micro lateral resistivity are negatively filled; after positive and negative filling, the crack development data of the crack segment to be identified is obtained.

[0023] Example 2: As an optimization of the above example, in step (3), in the obtained fracture development data, the positive filling curve segment represents the fracture development segment, indicating that the fracture is developed and the permeability is good; the negative filling or coincident curve segment represents the fracture non-development segment, indicating that the fracture is non-development and the permeability is poor.

[0024] Example 3: As an optimization of the above example, in step (2), a position with low natural gamma and low resistivity is selected in the curve segment corresponding to the pure sandstone layer.

[0025] Example 4: As an optimization of the above example, in step (2), the linear scale of the natural gamma curve is kept unchanged, and the logarithmic scale of the micro-lateral resistivity is adjusted so that the natural gamma curve segment overlaps with the micro-lateral resistivity curve segment.

[0026] This invention utilizes a mirrored arrangement of the natural gamma curve (GR) and the micro lateral resistivity curve (RXO), which are highly sensitive to cracks. Compared with the two curves mentioned above individually, this mirrored arrangement can amplify the sensitivity of cracks and intuitively reflect the crack development stage.

[0027] The fundamental reason why the method of this invention can be used to identify shale fractures is that fractures exhibit high gamma and low resistivity, which differs from the low gamma and high resistivity of non-fractured sections, as well as the characteristics of other lithologies such as sandstone (low gamma and low resistivity) and limestone (low gamma and high resistivity). The variations in natural gamma and resistivity are used to distinguish different reservoir characteristics.

[0028] Implementation Case: A case study of Permian Lucaogou Formation shale oil in the Jimsar Depression of the Junggar Basin serves as a verification example.

[0029] (1) Based on the collected core photographs and cast thin section data of the drilled well Ji 174 in the study area, summarize the characteristics of different fractures in the target section on the electrical imaging images.

[0030] (2) Based on the established typical electrical imaging logging chart, the polarity of the electrical imaging data of well Ji 174 was reprocessed and fractures were picked up. The picked fractures were compared with conventional logging curves to establish logging response characteristics for typical fracture types;

[0031] (3) According to the logging response characteristics of typical fracture types, the common characteristics of fracture-developed intervals are as follows: the micro-lateral resistivity shows relatively low resistivity against a high resistivity background; high-angle fractures, bedding fractures, and low-angle fractures show high natural gamma, while cleaved fractures show relatively high natural gamma, but are still much larger than the natural gamma anomaly value of sandstone; high-angle fractures and cleaved fractures show a positive difference in deep and shallow lateral resistivity, while bedding fractures and low-angle fractures show a negative difference or no difference in deep and shallow lateral resistivity. Other logging curves show slight changes, such as well diameter enlargement, but this is not a universal rule.

[0032] Therefore, based on the response chart of conventional well logging-imaging fracture interpretation results, natural gamma and micro lateral resistivity were selected as the sensitive curves.

[0033] The natural gamma curve and micro-lateral resistivity curve were processed according to the method described in the above embodiments as follows:

[0034] Locations with low natural gamma and low resistivity in pure sandstone formations were selected. Maintaining the linear scale of the natural gamma curve, the logarithmic scale of the micro-lateral resistivity was adjusted to overlap the natural gamma curve segment with the resistivity curve segment. In curve segments where natural gamma increases and micro-lateral resistivity decreases, the natural gamma and resistivity curves were positively filled. In curve segments where natural gamma decreases and micro-lateral resistivity increases, the natural gamma curve and micro-lateral resistivity curves were negatively filled. The characteristics of the positively filled curve segments are consistent with the fracture development segment characteristics in the aforementioned study of logging response characteristics for typical fracture types. (See...) Figure 1 .

[0035] Figure 1 In the middle, the characteristics of the positive filling (black filling part) curve segment in the fifth column correspond one-to-one with the following two columns (sixth and seventh columns), and the crack identification effect is good, achieving the purpose of crack identification.

[0036] This invention proposes an intuitive method for displaying fracture development, namely the natural gamma and micro-lateral resistivity mirror method, which enables the identification of fractures through conventional logging curves. It solves the problems of unclear response relationship between conventional single logging parameters and fractures, as well as the complexity of identifying multiple logging parameters.

[0037] The above technical features constitute the embodiments of the present invention, which have strong adaptability and implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the needs of different situations.

Claims

1. A method for fracture identification based on conventional logging curves using natural gamma and micro-lateral resistivity, characterized in that... Includes the following steps: (1) Obtain the natural gamma logging curve and the micro lateral resistivity curve of the fracture segment to be identified; (2) Select the layer segment position with low natural gamma and low resistance, keep the natural gamma curve scale unchanged, and adjust the micro-lateral resistivity scale so that the natural gamma curve segment overlaps with the micro-lateral resistivity curve segment. (3) In the curve segment where the natural gamma value increases and the micro lateral resistivity value decreases, the natural gamma and micro lateral resistivity are positively filled; in the curve segment where the natural gamma value decreases and the micro lateral resistivity value increases, the natural gamma and micro lateral resistivity are negatively filled; after positive and negative filling, the crack development data of the crack segment to be identified is obtained.

2. The fracture identification method based on conventional logging curves using natural gamma and micro-lateral resistivity as described in claim 1, characterized in that... In step (3), in the obtained fracture development data, the positive filling curve segment represents the fracture development segment, indicating that the fracture is well developed and the permeability is good; the negative filling or coincident curve segment represents the fracture undeveloped segment, indicating that the fracture is undeveloped and the permeability is poor.

3. The fracture identification method based on conventional logging curves using natural gamma and micro-lateral resistivity as described in claim 1 or 2, characterized in that... In step (2), a position with low natural gamma and low resistivity is selected in the curve segment corresponding to the pure sandstone layer.

4. The fracture identification method based on conventional logging curves using natural gamma and micro-lateral resistivity as described in claim 1 or 2, characterized in that... In step (2), keep the linear scale of the natural gamma curve unchanged, and adjust the logarithmic scale of the micro-lateral resistivity so that the natural gamma curve segment overlaps with the micro-lateral resistivity curve segment.

5. The fracture identification method based on conventional logging curves using natural gamma and micro-lateral resistivity as described in claim 3, characterized in that... In step (2), keep the linear scale of the natural gamma curve unchanged, and adjust the logarithmic scale of the micro-lateral resistivity so that the natural gamma curve segment overlaps with the micro-lateral resistivity curve segment.

Images