Quantitative point selection method, system and equipment for cable formation test and medium

Abstract

The invention discloses a cable formation test quantitative point selection method, system, equipment and medium, and the method comprises the steps: calculating a diameter expansion degree coefficient and a well wall smoothness coefficient, multiplying sound wave permeability, sound wave permeability and nuclear magnetic permeability by respective regional empirical weighting coefficients, and adding to obtain a reservoir seepage coefficient; calculating the product of the wellbore diameter environment coefficient and the reservoir seepage coefficient to obtain a point selection coefficient; and selecting a well section with a high point selection coefficient as a selectable point well section. According to the method, cable formation test quantitative point selection can be carried out by comprehensively considering the shaft environment and the reservoir permeability, the point selection success rate can be increased, the point selection times can be effectively reduced, the point selection method is changed from qualitative to quantitative, the defect that the point selection success rate depends on the operation experience of operators to a great extent can be overcome, and the method is suitable for popularization and application. And the success rate and efficiency of cable formation testing operation are improved.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration well technology, specifically relating to a quantitative point selection method, system, equipment and medium for cable formation testing. Background Technology

[0002] Cable formation testing is a logging method that uses a cable-driven formation tester to measure formation pressure and sample fluids. The probe is pushed against the formation by a pusher arm to set, and a certain suction pressure is applied to the probe to obtain formation fluids. The success of cable formation testing is closely related to the suitability of the sampling point selection. The suitability of the sampling point selection is generally assessed from two aspects: first, the wellbore environment; if there are enlarged or elliptical wellbores near the sampling point, the formation tester may fail to set, resulting in no sampling; second, reservoir permeability, which directly determines the probability and speed at which the formation tester pump can extract formation fluids. Currently, cable formation testing site selection is still in the qualitative stage, and the success rate largely depends on the operator's experience. Therefore, proposing a quantitative method for cable formation testing site selection is of practical significance.

[0003] Patent publication number CN105986816B, entitled "A Method for Identifying Sweet Spots in Shale Formations," describes a method for determining kerogen volume content, gas porosity, gas saturation, and total organic matter content in shale formations based on well logging data. It then uses radar chart analysis to obtain a geological sweet spot coefficient. Additionally, it determines the maximum horizontal effective stress, pore structure index, and brittleness index of the shale formation based on well logging data, and uses radar chart analysis to obtain an engineering sweet spot coefficient. Finally, it identifies sweet spots in shale formations based on both the geological and engineering sweet spot coefficients. While this patent application enables quantitative formation analysis, it does not allow for the selection of well sections for cable formation testing. Summary of the Invention

[0004] In order to overcome the problems existing in the prior art, the purpose of this invention is to provide a quantitative point selection method, system, equipment and medium for cable stratum testing. By proposing a quantitative point selection method for cable stratum testing, the invention solves the problem that the success rate of point selection largely depends on the operator's experience, realizes the leap from qualitative to quantitative point selection method, and improves the efficiency and success rate of cable stratum testing.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A quantitative method for cable ground stratum testing includes the following steps:

[0007] S1: Calculate the ratio of the average diameter of the multi-arm well at the same depth to the drill bit size to obtain the enlargement coefficient; calculate the ratio of the minimum diameter of the multi-arm well at the same depth to the maximum diameter of the multi-arm well at the same depth to obtain the elliptical wellbore coefficient; calculate the difference between the maximum average diameter of the multi-arm well within a certain well section and the minimum average diameter of the multi-arm well within that well section to obtain the wellbore smoothness coefficient.

[0008] S2: Determine the wellbore diameter environmental factor based on the enlargement degree coefficient, elliptical wellbore coefficient, wellbore smoothness coefficient, and the average diameter of multi-arm wells at the same depth;

[0009] S3: Multiply the acoustic permeability, acoustic permeability and nuclear magnetic permeability by their respective regional empirical weighting coefficients and then add them together to obtain the reservoir permeability coefficient;

[0010] S4: Calculate the product of the wellbore diameter environmental coefficient and the reservoir seepage coefficient to obtain the site selection coefficient;

[0011] S5: Select well sections with high selection coefficients as selectable well sections.

[0012] Optionally, in step S2, when the enlargement coefficient is greater than 105%, the elliptical borehole coefficient is less than 80%, the well wall smoothness coefficient is greater than 0.5, or the average diameter of the multi-arm well at the same depth is greater than 21, the wellbore diameter environmental coefficient is taken as 0; when the enlargement coefficient is less than or equal to 105%, the elliptical borehole coefficient is greater than or equal to 80%, the well wall smoothness coefficient is less than or equal to 0.5, and the average diameter of the multi-arm well at the same depth is less than or equal to 21, the wellbore diameter environmental coefficient is taken as 1.

[0013] Optionally, in step S3, the regional empirical weighting coefficient for acoustic permeability is 0.15; the regional empirical weighting coefficient for radioactive permeability is 0.25; and the regional empirical weighting coefficient for nuclear magnetic resonance permeability is 0.6.

[0014] Optionally, in step S5, well sections with a selection coefficient less than or equal to 0.1 are not recommended well sections, and well sections with a selection coefficient greater than 0.1 are recommended well sections.

[0015] Optionally, in step S4, the selection coefficients for all working well segments are calculated, and the selection coefficients for all working well segments are plotted as curves.

[0016] Optionally, the calculation formula for step S1 is:

[0017] Q kj =CAL / BIT

[0018] Q ty =CAL min-h / CAL max-h

[0019] Qgh =CAL max -CAL min

[0020] In the formula, Q kj Q is the diameter expansion coefficient. ty Q is the elliptic wellbore coefficient. gh CAL is the wellbore smoothness coefficient; CAL is the average diameter of a multi-arm well at the same depth; CAL max-h The maximum diameter of a multi-arm well at the same depth; CAL min-h The minimum diameter value for multi-arm wells at the same depth; CAL max The maximum average diameter of the multi-arm well within a 1m well section; CAL min This represents the minimum average diameter of the multi-arm well within a 1m well section.

[0021] Optionally, the calculation formula for step S3 is:

[0022] Q sl =A·K SB +B·K FS +C·K HC

[0023] In the formula, Q sl K is the reservoir permeability coefficient; SB K represents the sound wave permeability value. FS K represents the radioactive permeability value. HC , where is the nuclear magnetic permeability value; A, B, and C are regional empirical weighting coefficients.

[0024] A quantitative point selection system for cable ground testing includes:

[0025] The first calculation module is used to calculate the ratio of the average diameter of the multi-arm well at the same depth to the drill bit size to obtain the enlargement coefficient; to calculate the ratio of the minimum diameter of the multi-arm well at the same depth to the maximum diameter of the multi-arm well at the same depth to obtain the elliptical wellbore coefficient; and to calculate the difference between the maximum average diameter of the multi-arm well within a certain well section and the minimum average diameter of the multi-arm well within that well section to obtain the well wall smoothness coefficient.

[0026] The second calculation module is used to determine the wellbore diameter environmental coefficient based on the enlargement degree coefficient, elliptical wellbore coefficient, wellbore smoothness coefficient, and the average diameter of multi-arm wells at the same depth.

[0027] The third calculation module is used to multiply the acoustic permeability, acoustic permeability and nuclear magnetic permeability by their respective regional empirical weighting coefficients and then add them together to obtain the reservoir permeability coefficient.

[0028] The fourth calculation module is used to calculate the product of the wellbore diameter environmental coefficient and the reservoir seepage coefficient to obtain the site selection coefficient;

[0029] The selection module is used to select well sections with high selection coefficients as selectable well sections.

[0030] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the quantitative point selection method for cable stratum testing.

[0031] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the quantitative point selection method for cable stratum testing.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] This invention proposes a quantitative method, system, equipment, and medium for cable formation testing. It can comprehensively consider both the wellbore environment and reservoir permeability to quantitatively select cable formation testing sites, thereby improving the success rate of site selection, effectively reducing the number of site selection trips, and realizing the leap from qualitative to quantitative site selection methods. It can make up for the deficiency that the success rate of site selection largely depends on the operator's experience, and improve the success rate and efficiency of cable formation testing operations. Attached Figure Description

[0034] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way.

[0035] In the attached diagram:

[0036] Figure 1 This is a flowchart of the quantitative point selection method for cable stratum testing according to the present invention;

[0037] Figure 2 This is a schematic diagram of Embodiment 1 of the present invention;

[0038] Figure 3 This is a schematic diagram of Embodiment 2 of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0041] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. This application can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0042] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0043] The present invention will now be described in detail with reference to the accompanying drawings.

[0044] like Figure 1 As shown, the present invention provides a quantitative point selection method for cable stratum testing, comprising the following steps:

[0045] S1: Collect data on well diameter, acoustic permeability, radioactive permeability, and nuclear magnetic resonance permeability. Calculate the ratio of the average diameter of the multi-arm well at the same depth to the bit size (BIT) to obtain the enlargement coefficient; calculate the ratio of the minimum diameter of the multi-arm well at the same depth to the maximum diameter of the multi-arm well at the same depth to obtain the elliptical borehole coefficient; calculate the difference between the maximum average diameter of the multi-arm well within a certain well section and the minimum average diameter of the multi-arm well within that well section to obtain the wellbore smoothness coefficient; specifically, calculate the difference between the maximum average diameter of the multi-arm well within a 1m well section and the minimum average diameter of the multi-arm well within a 1m well section to obtain the wellbore smoothness coefficient.

[0046] S2: Determine the wellbore diameter environmental factor based on the enlargement coefficient, elliptical borehole coefficient, wellwall smoothness coefficient, and the average diameter of multiple arms at the same depth. Specifically, when the enlargement coefficient is greater than 105%, the elliptical borehole coefficient is less than 80%, the wellwall smoothness coefficient is greater than 0.5, or the average diameter of multiple arms at the same depth (CAL) is greater than 21, the wellbore diameter environmental factor is taken as 0; when the enlargement coefficient is less than or equal to 105%, the elliptical borehole coefficient is greater than or equal to 80%, the wellwall smoothness coefficient is less than or equal to 0.5, and the average diameter of multiple arms at the same depth (CAL) is less than or equal to 21, the wellbore diameter environmental factor is taken as 1.

[0047] S3: Multiply the acoustic permeability, acoustic permeability and nuclear magnetic permeability by their respective regional empirical weighting coefficients and then add them together to obtain the reservoir permeability coefficient;

[0048] S4: Calculate the product of the wellbore diameter environmental coefficient and the reservoir seepage coefficient to obtain the site selection coefficient;

[0049] S5: Select well sections with high selection coefficients as selectable well sections.

[0050] Specifically, the calculation formula is as follows:

[0051] Calculate the enlargement factor, elliptic wellbore factor, and wellbore smoothness factor:

[0052] Q kj =CAL / BIT

[0053] Q ty =CAL min-h / CAL max-h

[0054] Q gh =CAL max -CAL min

[0055] In the formula, Q kj Q is the diameter expansion coefficient. ty Q is the elliptic wellbore coefficient. gh CAL is the wellbore smoothness coefficient, dimensionless; CAL is the average diameter of multiple booms at the same depth, dimensionless. max-h The maximum diameter of a multi-arm well at the same depth, dimensionless; CAL min-h The minimum diameter of a multi-arm well at the same depth, dimensionless; CAL max The maximum average diameter of a multi-arm well within a 1m well section, dimensionless; CAL min The minimum average value of the diameter of a multi-arm well within a 1m well section is dimensionless.

[0056] Calculate the environmental factor of the wellbore diameter:

[0057]

[0058] In the formula, Q jt The wellbore diameter environmental coefficient is dimensionless.

[0059] Calculate the reservoir permeability coefficient Q sl :

[0060] Q sl =A·K SB +B·K FS +C·K HC

[0061] In the formula, Q sl K is the reservoir permeability coefficient, dimensionless; SB K represents the numerical value of acoustic permeability, which is dimensionless. FS K represents the radioactive permeability value, which is dimensionless. HC The values ​​represent nuclear magnetic permeability, which are dimensionless; A, B, and C are regional empirical weighting coefficients.

[0062] Calculate the selection coefficient Q:

[0063] Q = Q jt *Q sl

[0064] In the formula, Q is the selection coefficient, which is dimensionless; well sections with a high selection coefficient Q are selected as the selectable well sections.

[0065] The present invention provides a quantitative point selection system for cable stratum testing, comprising:

[0066] The first calculation module is used to calculate the ratio of the average diameter of the multi-arm well at the same depth to the drill bit size to obtain the enlargement coefficient; to calculate the ratio of the minimum diameter of the multi-arm well at the same depth to the maximum diameter of the multi-arm well at the same depth to obtain the elliptical wellbore coefficient; and to calculate the difference between the maximum average diameter of the multi-arm well within a certain well section and the minimum average diameter of the multi-arm well within that well section to obtain the well wall smoothness coefficient.

[0067] The second calculation module is used to determine the wellbore diameter environmental coefficient based on the enlargement degree coefficient, elliptical wellbore coefficient, wellbore smoothness coefficient, and the average diameter of multi-arm wells at the same depth.

[0068] The third calculation module is used to multiply the acoustic permeability, acoustic permeability and nuclear magnetic permeability by their respective regional empirical weighting coefficients and then add them together to obtain the reservoir permeability coefficient.

[0069] The fourth calculation module is used to calculate the product of the wellbore diameter environmental coefficient and the reservoir seepage coefficient to obtain the site selection coefficient;

[0070] The selection module is used to select well sections with high selection coefficients as selectable well sections.

[0071] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the quantitative point selection method for cable stratum testing.

[0072] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the quantitative point selection method for cable stratum testing.

[0073] Example 1

[0074] like Figure 2 As shown, well A, with a depth range of 4858–4886 m, is taken as an example.

[0075] First, calculate the wellbore diameter environmental factor Q. jt The wellbore conditions in this section are relatively good, and the wellbore environmental coefficient is calculated to be 1.

[0076] Based on well logging interpretation using nuclear magnetic permeability as the primary factor, the reservoir permeability coefficient, Q, is calculated. sl .

[0077] According to the formula Q = Q jt *Q sl Calculate the final selection coefficient;

[0078] Pressure measurements were performed at points with relatively high Q values, with five points of low Q values ​​selected for cross-validation. As shown in the example, points selected at locations with NMR permeability greater than 0.1 mD yielded relatively high Q values ​​and good pressure measurement results. Points selected at locations with lower Q values ​​showed only dense points, failing to provide formation pressure data. This demonstrates the practical effectiveness of this method.

[0079] Example 2

[0080] like Figure 3 As shown, well B in this embodiment has an enlarged diameter, resulting in a wellbore diameter environmental coefficient of 0, which in turn leads to a final selection point coefficient of 0, meaning a well should not be located at that position. For comparative testing purposes, a trial pressure test was conducted, and the actual result was a failed setting of the seal.

[0081] As can be seen from the above cases, the calculated selection coefficient Q is highly consistent with the selection success rate. This shows that the method of the present invention is effective and can improve the efficiency and success rate of cable stratum testing.

[0082] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] Unless otherwise specified, the working methods or control methods involved in the above embodiments are conventional working methods or control methods in the art.

[0087] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Any other modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention, as long as they do not depart from the spirit and scope of the technical solutions of the present invention, should be covered within the scope of the claims of the present invention.

Claims

1. A quantitative selectivity method for wireline formation testing, characterized in that, The method comprises the following steps: S1: calculating the ratio of the average value of the multi-arm caliper at the same depth to the drill bit size to obtain a gauge extent coefficient; calculating the ratio of the minimum value of the multi-arm caliper at the same depth to the maximum value of the multi-arm caliper at the same depth to obtain an elliptical hole coefficient; and calculating the difference between the maximum average value of the multi-arm caliper in a certain well section range and the minimum average value of the multi-arm caliper in the well section range to obtain a well wall smoothness coefficient; S2: judging the wellbore caliper environment coefficient according to the gauge extent coefficient, the elliptical hole coefficient, the well wall smoothness coefficient and the average value of the multi-arm caliper at the same depth; S3: multiplying the acoustic permeability, the acoustic permeability and the nuclear magnetic permeability by the respective regional empirical weighting coefficients and then adding them to obtain a reservoir percolation coefficient; S4: calculating the product of the wellbore caliper environment coefficient and the reservoir percolation coefficient to obtain a point selection coefficient; S5: selecting a well section with a high point selection coefficient as a selectable point well section.

2. The quantitative selectivity method for a wireline formation test according to claim 1, wherein, In step S2, when the gauge extent coefficient is greater than 105%, or the elliptical hole coefficient is less than 80%, or the well wall smoothness coefficient is greater than 0.5, or the average value of the multi-arm caliper at the same depth is greater than 21, the wellbore caliper environment coefficient is 0; when the gauge extent coefficient is less than or equal to 105%, the elliptical hole coefficient is greater than or equal to 80%, the well wall smoothness coefficient is less than or equal to 0.5, and the average value of the multi-arm caliper at the same depth is less than or equal to 21, the wellbore caliper environment coefficient is 1.

3. The quantitative selectivity method for a wireline formation test according to claim 1, wherein, In step S3, the regional empirical weighting coefficient of the acoustic permeability is 0.15; the regional empirical weighting coefficient of the radioactive permeability is 0.25; and the regional empirical weighting coefficient of the nuclear magnetic permeability is 0.

6.

4. The quantitative selectivity method of a wireline formation test according to claim 1, wherein, In step S5, a well section with a point selection coefficient less than or equal to 0.1 is a non-recommended point selection well section, and a well section with a point selection coefficient greater than 0.1 is a selectable point well section.

5. The quantitative selectivity method of a wireline formation test according to claim 1, wherein, In step S4, the point selection coefficients of all operation well sections are calculated, and the point selection coefficients of all operation well sections are plotted as a curve.

6. The quantitative selectivity method of a wireline formation test according to claim 1, wherein, The calculation formula of step S1 is: Q kj = CAL / BIT Q ty = CAL min-h / CAL max-h Q gh = CAL max - CAL min wherein Q kj is the expansion degree coefficient, Q ty is the elliptical hole coefficient, Q gh is the smooth wall coefficient; CAL is the average value of multi-arm caliper at the same depth; CAL max-h is the maximum value of multi-arm caliper at the same depth; CAL min-h is the minimum value of multi-arm caliper at the same depth; CAL max is the maximum average value of multi-arm caliper within a 1 m section; CAL min is the minimum average value of multi-arm caliper within a 1 m section.

7. The quantitative selectivity method of a wireline formation test according to claim 1, wherein, The calculation formula of step S3 is: Q sl = A · K SB + B · K FS + C · K HC where Q sl is the reservoir permeability coefficient; K SB is the sonic permeability value; K FS is the radioactive permeability value; K HC is the nuclear magnetic permeability value; A, B, C are regional empirical weighting coefficients.

8. A quantitative selectivity spotting system for electrical cable formation testing, characterized by, It comprises: A first calculation module for calculating the ratio of the average value of the multi-arm caliper at the same depth to the drill bit size to obtain a gauge extent coefficient; calculating the ratio of the minimum value of the multi-arm caliper at the same depth to the maximum value of the multi-arm caliper at the same depth to obtain an elliptical hole coefficient; and calculating the difference between the maximum average value of the multi-arm caliper in a certain well section range and the minimum average value of the multi-arm caliper in the well section range to obtain a well wall smoothness coefficient; A second calculation module for judging the wellbore caliper environment coefficient according to the gauge extent coefficient, the elliptical hole coefficient, the well wall smoothness coefficient and the average value of the multi-arm caliper at the same depth; A third calculation module for multiplying the acoustic permeability, the acoustic permeability and the nuclear magnetic permeability by the respective regional empirical weighting coefficients and then adding them to obtain a reservoir percolation coefficient; A fourth calculation module for calculating the product of the wellbore caliper environment coefficient and the reservoir percolation coefficient to obtain a point selection coefficient; A selection module for selecting a well section with a high point selection coefficient as a selectable point well section.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method for quantitative selection of a point in a wireline formation test according to any one of claims 1 to 7 when executing the computer program.

10. A computer readable storage medium storing a computer program, the computer program implementing the steps of the method for quantitative selection of a point in a wireline formation test according to any one of claims 1 to 7 when executed by a processor.

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