Pore structure classification and evaluation method and system based on fractal dimension of well logging curves
By combining the fractal dimensions of the well logging curve and core mercury injected data, the fractal dimension boundary range of the pore structure is determined, which solves the problem of the large data requirements for reservoir pore structure evaluation in the prior art and the difficulty of continuous quantitative evaluation, and achieves high-precision classification evaluation of the pore structure of the whole well section.
Patent Information
- Application Number
- CN201910497090.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2019-06-10
- Publication Date
- 2025-04-29
- Estimated Expiration
- 2039-06-10
AI Technical Summary
The prior art has problems such as high data demand, difficulty in continuous quantitative evaluation, difficulty in the whole well section continuous processing and unknown well section prediction in the evaluation of reservoir pore structure, and the price of NMR logging is expensive, which limits its wide application.
The pore structure classification evaluation method based on the fractal dimension of the logging curve is adopted. By combining the fractal dimension of the well logging curve and the core mercury injected data, the fractal dimension of the pore structure is determined, and the fractal dimension of the logging curve of the whole well section is calculated to achieve the classification evaluation of the pore structure of the whole well section.
It realizes the classification evaluation of pore structures of the whole well section using conventional logging data, eliminates the influence of the matrix part on the bilateral direction, and obtains high-precision crack porosity, which is convenient and easy to use.
Smart Images
Figure CN112149341B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of petroleum reservoir exploration, and more specifically, to a pore structure classification evaluation method and system based on fractal dimension of well logging curves. Background Art
[0002] Pore structure refers to the geometric shape, size, distribution, interconnectedness, and configuration relationship between pores and throats of the rock. The pore structure mainly reflects the combination of various pores and throats connecting the pores in the reservoir, and is the overall development of pores and throats. The microscopic pore structure characteristics of reservoir rocks are the main factors affecting the storage capacity of reservoir fluids (oil, gas, water) and the exploitation of oil and gas resources. Therefore, clarifying the pore structure characteristics of reservoir rocks is a key issue in increasing the production of oil and gas layers and improving oil and gas recovery rates.
[0003] The evaluation of reservoir pore structure mainly focuses on four types of methods: 1. Statistical analysis of thin sections, porosity, mercury injection and other data. This method is based on mathematical statistics. The disadvantage is that it requires a lot of experimental data and cannot be continuously quantitatively evaluated or predicted; 2. According to the core capillary pressure experiment, the correlation between the displacement pressure, roar channel mean and other parameters and the logging curve is established, and then the logging curve is used to continuously evaluate the pore structure. The difficulty of this method is that it is generally difficult to establish a fitting relationship with a high compliance rate; 3. Using scanning electron microscopy and other methods combined with pore network models to intuitively analyze the pore structure. This method intuitively reflects the pore structure, but it is difficult to continuously process the entire well section and predict unknown well sections; 4. Using nuclear magnetic resonance logging data to evaluate the pore structure. This method is the most direct logging method to reflect the pore structure, but nuclear magnetic resonance logging is expensive, and its wide application is subject to certain restrictions. Therefore, it is necessary to develop a pore structure classification evaluation method and system based on the fractal dimension of logging curves.
[0004] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention
[0005] The present invention proposes a pore structure classification and evaluation method and system based on the fractal dimension of logging curves, which can classify the pore structure through the fractal dimension of logging curves and core mercury injection data, fully consider the rock physical information reflected by different logging curves and the curve characteristics extracted by different fractal dimension algorithms, and realize the classification and evaluation of the pore structure of the entire well section using conventional logging data, which is convenient and easy to use.
[0006] According to one aspect of the present invention, a pore structure classification and evaluation method based on the fractal dimension of well logging curves is proposed. The method may include: classifying the reservoir pore structure according to the capillary pressure curve of the core; determining the corresponding fractal dimension limit range for each reservoir pore structure; calculating the fractal dimension of the well logging curve of the entire well section according to the fractal dimension limit range corresponding to each pore structure, and then evaluating the pore structure of the entire well section.
[0007] Preferably, for each type of reservoir pore structure, determining the corresponding fractal dimension limit range includes: extracting the logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; and calculating the acoustic fractal dimension D according to the logging data. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; according to the logging data, calculate the deep resistivity R / S fractal dimension D RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; establish an intersection diagram of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension to determine the limit range of the fractal dimension of the pore structure.
[0008] Preferably, the logging data includes sonic curves, neutron curves, density curves and deep and shallow resistivity curves.
[0009] Preferably, the weighted fractal dimension of the porosity curve is calculated by formula (1):
[0010]
[0011] Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
[0012] Preferably, the resistivity weighted fractal dimension is calculated by formula (2):
[0013]
[0014] Among them, D R is the resistivity weighted fractal dimension, D RT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.
[0015] According to another aspect of the present invention, a pore structure classification and evaluation system based on the fractal dimension of logging curves is proposed, characterized in that the system comprises: a memory storing computer executable instructions; a processor running the computer executable instructions in the memory to perform the following steps: classifying the reservoir pore structure according to the capillary pressure curve of the core; determining the corresponding fractal dimension limit range for each reservoir pore structure; calculating the fractal dimension of the logging curve of the entire well section according to the fractal dimension limit range corresponding to each pore structure, and then evaluating the pore structure of the entire well section.
[0016] Preferably, for each type of reservoir pore structure, determining the corresponding fractal dimension limit range includes: extracting the logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; and calculating the acoustic fractal dimension D according to the logging data. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; according to the logging data, calculate the deep resistivity R / S fractal dimension D RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; establish an intersection diagram of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension to determine the limit range of the fractal dimension of the pore structure.
[0017] Preferably, the logging data includes sonic curves, neutron curves, density curves and deep and shallow resistivity curves.
[0018] Preferably, the weighted fractal dimension of the porosity curve is calculated by formula (1):
[0019]
[0020] Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
[0021] Preferably, the resistivity weighted fractal dimension is calculated by formula (2):
[0022]
[0023] Among them, D R is the resistivity weighted fractal dimension, D RT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.
[0024] Its beneficial effects are: by classifying the pore structure through the fractal dimension of the logging curve and the core mercury injection data, eliminating the influence of the matrix part on the dual lateral direction, obtaining the resistivity value of the pure fracture part, obtaining high-precision fracture porosity, and fully considering the rock physical information reflected by different logging curves and the curve characteristics extracted by different fractal dimension algorithms, realizing the classification and evaluation of the pore structure of the entire well section using conventional logging data, which is convenient and easy to use.
[0025] The methods and apparatus of the present invention have other features and advantages that will be apparent from, or will be described in detail in, the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.
[0027] Figure 1 A flow chart showing the steps of the pore structure classification and evaluation method based on the fractal dimension of the well logging curve according to the present invention.
[0028] Figure 2a , Figure 2b , Figure 2c , Figure 2d Schematic diagrams of four pore structures according to an embodiment of the present invention are shown respectively.
[0029] Figure 3 A schematic diagram showing the box dimensions of three porosity curves calculated for a type I reservoir at a certain depth point according to an embodiment of the present invention is shown.
[0030] Figure 4 A schematic diagram showing the resistivity R / S dimension according to an embodiment of the present invention is shown.
[0031] Figure 5 The cross-plots of porosity dimension and resistivity dimension of the four pore structures according to FIG. 2 are shown.
[0032] Figure 6 A diagram showing the processing results of the entire well section according to an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0033] The present invention will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.
[0034] Figure 1 A flow chart showing the steps of the pore structure classification and evaluation method based on the fractal dimension of the well logging curve according to the present invention.
[0035] In this embodiment, the pore structure classification and evaluation method based on the fractal dimension of logging curves according to the present invention may include: step 101, classifying the reservoir pore structure according to the capillary pressure curve of the core; step 102, determining the corresponding fractal dimension limit range for each reservoir pore structure; step 103, calculating the fractal dimension of the logging curve of the entire well section according to the fractal dimension limit range corresponding to each pore structure, and then evaluating the pore structure of the entire well section.
[0036] In one example, for each type of reservoir pore structure, determining the corresponding fractal dimension limit range includes: extracting logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; calculating the acoustic wave fractal dimension D according to the logging data. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; according to the logging data, calculate the deep resistivity R / S fractal dimension D RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; establish the intersection diagram of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension to determine the limit range of the fractal dimension of the pore structure.
[0037] In one example, the well logging data includes sonic curves, neutron curves, density curves, and deep and shallow resistivity curves.
[0038] In one example, the porosity curve weighted fractal dimension is calculated by formula (1):
[0039]
[0040] Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
[0041] In one example, the resistivity-weighted fractal dimension is calculated by formula (2):
[0042]
[0043] Among them, D R is the resistivity weighted fractal dimension, D RT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.
[0044] Specifically, the fracture-vuggy carbonate reservoir is composed of a matrix part and fractures. Therefore, both the matrix pores and fractures have a diversion effect on the dual lateral direction, affecting the dual lateral resistivity. Therefore, it is necessary to eliminate the influence of the matrix part on the dual lateral direction, obtain the resistivity value of the pure fracture part, and obtain the fracture porosity with higher accuracy.
[0045] The pore structure classification and evaluation method based on the fractal dimension of the well logging curve according to the present invention may include:
[0046] The reservoir pore structure is classified according to the capillary pressure curve shape, displacement pressure, median roar radius and other parameters of the core. For each reservoir pore structure, the corresponding fractal dimension limit range is determined by using the box dimension calculation principle. The following includes: according to the reservoir pore structure, the logging data of the well section corresponding to the capillary pressure curve is extracted, where the logging data includes sonic wave curve, neutron curve, density curve and deep and shallow resistivity curve; according to the logging data, the sonic fractal dimension D is calculated respectively. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve through formula (1); according to the logging data, the deep resistivity R / S fractal dimension D is calculated by using the R / S fractal dimension calculation principle. RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension through formula (2); establish the intersection diagram of resistivity weighted fractal dimension and porosity curve weighted fractal dimension, and determine the limit range of fractal dimension of pore structure.
[0047] According to the fractal dimension limit range corresponding to each pore structure, the fractal dimension of the logging curve of the entire well section is calculated, and then the pore structure of the entire well section is evaluated.
[0048] This method classifies pore structures through fractal dimensions of logging curves and core mercury injection data, fully considering the rock physical information reflected by different logging curves and the curve characteristics extracted by different fractal dimension algorithms, and realizes the classification and evaluation of pore structures of the entire well section using conventional logging data, which is convenient and easy to use.
[0049] Application Examples
[0050] To facilitate understanding of the solution and effects of the embodiments of the present invention, a specific application example is given below. Those skilled in the art should understand that this example is only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.
[0051] Figure 2a , Figure 2b , Figure 2c , Figure 2d Schematic diagrams of four pore structures according to an embodiment of the present invention are shown respectively.
[0052] According to the shape of the capillary pressure curve of the core, displacement pressure, median roar radius and other parameters, the reservoir pore structure is divided into four categories, namely Figure 2a , Figure 2b , Figure 2c , Figure 2d The specific parameters of each category are shown in Table 1.
[0053] Table 1
[0054]
[0055]
[0056] For each reservoir pore structure, the corresponding fractal dimension limit range is determined as follows:
[0057] According to the reservoir pore structure, the logging data of the well section corresponding to the capillary pressure curve is extracted, wherein the logging data includes the sonic curve, the neutron curve, the density curve and the deep and shallow resistivity curves.
[0058] Figure 3 A schematic diagram of the box dimension of three porosity curves calculated for a type I reservoir at a certain depth point according to an embodiment of the present invention is shown, where the slope is the box dimension value.
[0059] According to the logging data, the acoustic fractal dimension D is calculated by using the box dimension calculation principle. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , according to Figure 3 The box dimension of the three-porosity curve calculated for a type I reservoir at a certain depth point is shown in Figure 3 It can be known that D AC =2.13, D DEN =2.139, D CNL =2.137, and then the weighted fractal dimension of the porosity curve is calculated by formula (1).
[0060] Figure 4 A schematic diagram showing the resistivity R / S dimension according to an embodiment of the present invention is shown.
[0061] According to the logging data, the deep resistivity R / S fractal dimension D is calculated by using the R / S fractal dimension calculation principle. RT and shallow resistivity R / S fractal dimension D RS ,like Figure 4 As shown, the deep resistivity R / S fractal dimension D RT =2.124, shallow resistivity R / S fractal dimension D RS =2.132, and then the resistivity weighted fractal dimension is calculated by formula (2).
[0062] Figure 5 The cross-plots of porosity dimension and resistivity dimension of the four pore structures according to FIG. 2 are shown.
[0063] Establish the cross plot of resistivity weighted fractal dimension and porosity curve weighted fractal dimension to determine the fractal dimension limit range of pore structure. Make a scatter point cross plot with resistivity weighted fractal dimension as the horizontal coordinate and porosity curve weighted fractal dimension as the vertical coordinate to determine the fractal dimension limit range of each type of pore structure, such as Figure 5 As shown, the standard for Type I pore structure reservoir is: D POR ≤2.2, D R ≤2.21; Class II pore structure reservoir standard: 2.2 <D POR ≤2.4,2.21 <D R ≤2.51; Class III pore structure reservoir standard: 2.4 <D POR ≤2.56,2.51 <D R ≤2.55; Class IV pore structure reservoir standard: D POR >2.56, D R >2.55.
[0064] Figure 6 A diagram showing the processing results of the entire well section according to an embodiment of the present invention is shown.
[0065] According to the fractal dimension limit range corresponding to each pore structure, the fractal dimension of the logging curve of the entire well section is calculated, and then the pore structure of the entire well section is evaluated. Figure 6 It is the processing result of the whole well section. The last PORTYPE in the figure is the classification result curve.
[0066] In summary, the present invention classifies pore structures by using the fractal dimension of logging curves and core mercury injection data, fully considering the rock physical information reflected by different logging curves and the curve characteristics extracted by different fractal dimension algorithms, and realizes the classification and evaluation of the pore structure of the entire well section using conventional logging data, which is convenient and easy to use.
[0067] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.
[0068] According to an embodiment of the present invention, a pore structure classification and evaluation system based on the fractal dimension of logging curves is provided, characterized in that the system comprises: a memory storing computer executable instructions; a processor running the computer executable instructions in the memory to perform the following steps: classifying the reservoir pore structure according to the capillary pressure curve of the core; determining the corresponding fractal dimension limit range for each reservoir pore structure; calculating the fractal dimension of the logging curve of the entire well section according to the fractal dimension limit range corresponding to each pore structure, and then evaluating the pore structure of the entire well section.
[0069] In one example, for each type of reservoir pore structure, determining the corresponding fractal dimension limit range includes: extracting logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; calculating the acoustic wave fractal dimension D according to the logging data. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; according to the logging data, calculate the deep resistivity R / S fractal dimension D RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; establish the intersection diagram of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension to determine the limit range of the fractal dimension of the pore structure.
[0070] In one example, the well logging data includes sonic curves, neutron curves, density curves, and deep and shallow resistivity curves.
[0071] In one example, the porosity curve weighted fractal dimension is calculated by formula (1):
[0072]
[0073] Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
[0074] In one example, the resistivity-weighted fractal dimension is calculated by formula (2):
[0075]
[0076] Among them, D R is the resistivity weighted fractal dimension, DRT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.
[0077] This system classifies pore structures through the fractal dimension of logging curves and core mercury injection data, fully considering the rock physical information reflected by different logging curves and the curve characteristics extracted by different fractal dimension algorithms, and realizes the classification and evaluation of pore structure of the entire well section using conventional logging data, which is convenient and easy to use.
[0078] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.
[0079] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.
Claims
1. A pore structure classification and evaluation method based on the fractal dimension of well logging curves, characterized in that: include: Classify reservoir pore structure based on capillary pressure curves of cores; For each reservoir pore structure, determine the corresponding fractal dimension limit range; According to the fractal dimension limit range corresponding to each pore structure, the fractal dimension of the logging curve of the whole well section is calculated, and then the pore structure of the whole well section is evaluated; Wherein, for each reservoir pore structure, determining the corresponding fractal dimension limit range includes: Extracting the logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; According to the logging data, the acoustic fractal dimension D is calculated respectively. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; According to the logging data, the deep resistivity R / S fractal dimension D is calculated respectively. RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; A cross plot of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension is established to determine the limit range of the fractal dimension of the pore structure.
2. The pore structure classification and evaluation method based on the fractal dimension of well logging curve according to claim 1, wherein: The logging data include sonic curves, neutron curves, density curves and deep and shallow resistivity curves.
3. The pore structure classification and evaluation method based on the fractal dimension of well logging curve according to claim 1, wherein: The weighted fractal dimension of the porosity curve is calculated by formula (1): Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
4. The pore structure classification and evaluation method based on the fractal dimension of well logging curve according to claim 1, wherein: The resistivity weighted fractal dimension is calculated by formula (2): Among them, D R is the resistivity weighted fractal dimension, D RT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.
5. A pore structure classification and evaluation system based on the fractal dimension of well logging curves, characterized in that: The system includes: a memory storing computer executable instructions; A processor, wherein the processor runs the computer executable instructions in the memory to perform the following steps: Classify reservoir pore structure based on capillary pressure curves of cores; For each reservoir pore structure, determine the corresponding fractal dimension limit range; According to the fractal dimension limit range corresponding to each pore structure, the fractal dimension of the logging curve of the whole well section is calculated, and then the pore structure of the whole well section is evaluated; Wherein, for each reservoir pore structure, determining the corresponding fractal dimension limit range includes: Extracting the logging data of the well section corresponding to the capillary pressure curve according to the reservoir pore structure type; According to the logging data, the acoustic fractal dimension D is calculated respectively. AC , density fractal dimension D DEN Neutron Fractal Dimension D CNL , and then calculate the weighted fractal dimension of the porosity curve; According to the logging data, the deep resistivity R / S fractal dimension D is calculated respectively. RT and shallow resistivity R / S fractal dimension D RS , and then calculate the resistivity weighted fractal dimension; A cross plot of the resistivity weighted fractal dimension and the porosity curve weighted fractal dimension is established to determine the limit range of the fractal dimension of the pore structure.
6. The pore structure classification and evaluation system based on the fractal dimension of well logging curves according to claim 5, wherein: The logging data include sonic curves, neutron curves, density curves and deep and shallow resistivity curves.
7. The pore structure classification and evaluation system based on the fractal dimension of well logging curves according to claim 5, wherein: The weighted fractal dimension of the porosity curve is calculated by formula (1): Among them, D POR is the weighted fractal dimension of the porosity curve, D AC is the fractal dimension of the sound wave, D DEN is the density fractal dimension, D CNL is the neutron fractal dimension.
8. The pore structure classification and evaluation system based on the fractal dimension of well logging curves according to claim 5, wherein: The resistivity weighted fractal dimension is calculated by formula (2): Among them, D R is the resistivity weighted fractal dimension, D RT is the deep resistivity R / S fractal dimension, D RS is the fractal dimension of shallow resistivity R / S.