Method, device and equipment for selecting well completion mode

Abstract

The invention provides a well completion mode selection method, device and equipment. The method comprises the following steps: acquiring membership degrees of wellbore complexity data corresponding to different well completion modes; a shaft complexity index prediction model is utilized to process the membership degrees of the shaft complexity data corresponding to the different well completion modes, shaft complexity indexes corresponding to the different well completion modes are obtained, and the shaft complexity index prediction model is established by utilizing the membership degrees corresponding to shaft complexity data samples in advance; engineering data corresponding to different well completion modes are obtained, and risk levels corresponding to the different well completion modes are determined according to the wellbore complexity index and the engineering data; and selecting a target well completion mode from the different well completion modes according to the risk levels corresponding to the different well completion modes. Based on the method, the optimal well completion mode can be accurately determined.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas development, and in particular to a method, device and equipment for selecting a completion method. Background Art

[0002] Well completion refers to the establishment of a reasonable connection channel or connection method between the oil and gas layer and the wellbore of the oil and gas well at the bottom of the well. Well completion can ensure good connection between the wellbore and the reservoir, so that the well can produce high and stable production, and maintain the long-term stability of the wellbore. The selection of completion method is the key to well completion operations. Whether the selection of a well completion method is reasonable is directly related to whether the future development and exploitation of the well can proceed smoothly.

[0003] The existing methods for selecting completion methods are relatively single in scope and only apply to a certain type of oil and gas reservoirs, such as carbonate fractured gas reservoirs, low permeability oil and gas reservoirs, etc., and only consider geological factors, and are unable to accurately select the optimal completion method, resulting in poor results and low economic benefits in oil and gas exploration and development.

[0004] Currently, no effective solution has been proposed to the above problems. Summary of the invention

[0005] This specification provides a method, device and equipment for selecting a completion method to solve the problem that the prior art cannot accurately select the optimal completion method, resulting in poor oil and gas exploration and development effects and low economic benefits.

[0006] In a first aspect, an embodiment of this specification provides a method for selecting a completion method, including:

[0007] Obtain the membership of wellbore complexity data corresponding to different completion methods;

[0008] Using a wellbore complexity index prediction model to process the membership of wellbore complexity data corresponding to different completion methods, and obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples;

[0009] Acquire engineering data corresponding to different completion methods, and determine risk levels corresponding to different completion methods according to the wellbore complexity index and the engineering data;

[0010] According to the risk levels corresponding to different completion methods, a target completion method is selected from different completion methods.

[0011] In one embodiment, the wellbore complexity data includes: wellbore trajectory tortuosity index, wellbore temperature, wellbore pressure, leakage, wellbore diameter expansion rate, and gap expansion rate; accordingly, the degree of membership of obtaining wellbore complexity data corresponding to different completion methods includes:

[0012] Obtain the wellbore trajectory tortuosity index membership, wellbore temperature membership, wellbore pressure membership, leakage volume membership, wellbore diameter expansion rate membership, and gap expansion rate membership corresponding to different completion methods.

[0013] In one embodiment, the wellbore complexity data also includes: well inclination and azimuth, the well inclination is used to determine the well inclination arc length, and the azimuth is used to determine the azimuth arc length; the wellbore trajectory tortuosity index is determined based on the well inclination arc length and the azimuth arc length.

[0014] In one embodiment, obtaining the wellbore trajectory tortuosity index membership corresponding to different completion methods includes:

[0015] Acquire an eye trajectory tortuosity, a first target eye trajectory tortuosity, and a second target eye trajectory tortuosity, wherein the first target eye trajectory tortuosity is greater than a preset eye trajectory tortuosity threshold, and the second target eye trajectory tortuosity is less than the preset eye trajectory tortuosity threshold;

[0016] Determine the wellbore trajectory twisting index membership according to the wellbore trajectory tortuosity, the first target wellbore trajectory tortuosity, and the second target wellbore trajectory tortuosity;

[0017] The obtaining of the wellbore temperature membership corresponding to different completion methods includes:

[0018] Establish the membership function corresponding to the wellbore temperature;

[0019] According to the membership function corresponding to the wellbore temperature, the wellbore temperature membership corresponding to different completion methods is determined.

[0020] In one embodiment, the wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples, including:

[0021] According to the following formula, the wellbore complexity index prediction model is established:

[0022] D co =w TI3D *TI 3D +w T *T+w P *P+w η *η+w K *K+w DS *K DS

[0023] Among them, D co is the wellbore complexity index; w TI3D is the weight corresponding to the well trajectory tortuosity index sample; TI 3D is the membership degree corresponding to the wellbore trajectory tortuosity index sample; wT is the weight corresponding to the wellbore temperature sample; T is the membership degree corresponding to the wellbore temperature sample; w P is the weight corresponding to the wellbore pressure sample; P is the membership degree corresponding to the wellbore pressure sample; w η is the weight corresponding to the missing sample; η is the membership degree corresponding to the missing sample; w K is the weight corresponding to the well diameter expansion rate sample; K is the membership degree corresponding to the well diameter expansion rate sample; w DS is the weight corresponding to the gap expansion rate sample; K DS is the membership degree corresponding to the gap expansion rate sample.

[0024] In one embodiment, the engineering data includes: pipe string running friction, pipe string buckling index and triaxial safety factor. Accordingly, the risk level corresponding to different completion methods is determined according to the wellbore complexity index and the engineering data, including:

[0025] Determine the target string entry friction resistance corresponding to different completion methods from the string entry friction resistance corresponding to different completion methods in turn, and determine the target triaxial safety factor corresponding to different completion methods in turn from the triaxial safety factors corresponding to different completion methods, wherein the target string entry friction group is greater than a preset string entry friction group threshold, and the target triaxial safety factor is less than a preset triaxial safety factor threshold;

[0026] The risk scoring rules corresponding to the wellbore complexity index, the tubing running friction resistance, the tubing buckling index and the triaxial safety factor are retrieved in sequence, and the risk values ​​corresponding to the wellbore complexity index, the target tubing running friction resistance, the tubing buckling index and the target triaxial safety factor are determined in sequence;

[0027] The risk values ​​corresponding to the wellbore complexity index, target string running friction, string buckling index and target triaxial safety factor are summed to obtain the comprehensive risk values ​​corresponding to different completion methods.

[0028] According to the comprehensive risk values ​​corresponding to different completion methods, the risk levels corresponding to different completion methods are determined.

[0029] In one embodiment, selecting a target completion method from different completion methods according to risk levels corresponding to different completion methods includes:

[0030] The risk levels corresponding to different completion methods are compared to determine a target risk level in the risk level and a target completion method corresponding to the target risk level, wherein the target risk level includes an acceptable risk.

[0031] In a second aspect, the embodiments of this specification also provide a device for selecting a completion method, including:

[0032] An acquisition module, used to obtain the membership of wellbore complexity data corresponding to different completion methods;

[0033] A prediction module, used to process the membership of wellbore complexity data corresponding to different completion methods using a wellbore complexity index prediction model to obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples;

[0034] A determination module, used to obtain engineering data corresponding to different completion methods, and determine the risk levels corresponding to the different completion methods according to the wellbore complexity index and the engineering data;

[0035] The selection module is used to select a target completion method from different completion methods according to the risk levels corresponding to the different completion methods.

[0036] In a third aspect, an embodiment of the present specification also provides a device for selecting a completion method, including a processor and a memory for storing instructions executable by the processor, and when the processor executes the instructions, the method for selecting the completion method in the above embodiment is implemented.

[0037] In a fourth aspect, the embodiments of this specification further provide a computer-readable storage medium having computer instructions stored thereon, and when the computer-readable storage medium executes the instructions, the method for selecting the completion method in the above-mentioned embodiment is implemented.

[0038] The embodiments of this specification provide a method, device and equipment for selecting a completion method. First, the membership of the wellbore complexity data corresponding to different completion methods is obtained. Secondly, the membership of the wellbore complexity data corresponding to different completion methods is processed using the wellbore complexity index prediction model to obtain the wellbore complexity index corresponding to the different completion methods. The wellbore complexity index prediction model is pre-established using the membership corresponding to the wellbore complexity data samples. Then, the engineering data corresponding to the different completion methods are obtained, and the risk levels corresponding to the different completion methods are determined based on the wellbore complexity index and the engineering data. Finally, based on the risk levels corresponding to the different completion methods, a target completion method is selected from the different completion methods. In the embodiments of this specification, by using the wellbore complexity index prediction model to process the membership of the wellbore complexity data corresponding to different completion methods, the wellbore complexity index corresponding to the different completion methods can be accurately and quickly obtained. By obtaining the engineering data corresponding to different completion methods, and synthesizing the engineering data corresponding to different completion methods and the wellbore complexity index corresponding to different completion methods, the optimal completion method can be selected. This method takes into account the influence of the complexity of the wellbore itself and the engineering conditions on the selection of the completion method, and can improve the accuracy of the selection of the completion method. By obtaining the risk level corresponding to different completion methods, and selecting the target completion method according to the risk level corresponding to different completion methods, the completion string entry risk of different completion methods can be quantified, so that the completion method with the lowest risk can be quickly selected. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 It is a flow chart of a method for selecting a completion method provided in an embodiment of this specification;

[0041] Figure 2 is a risk score combination diagram provided in the embodiments of this specification;

[0042] Figure 3 It is a risk level classification diagram provided in the embodiments of this specification;

[0043] Figure 4 is a curve diagram of well inclination and azimuth changing with well depth provided in the embodiments of this specification;

[0044] Figure 5 is a curve diagram of the change of wellbore size with well depth provided in the embodiments of this specification;

[0045] Figure 6 is a curve diagram of the variation of the wellbore trajectory torsional index with the well depth provided in the embodiment of this specification;

[0046] Figure 7 is a curve diagram of pressure variation with well depth provided in the embodiments of this specification;

[0047] Figure 8 It is a temperature variation curve diagram provided in the embodiment of this specification with respect to well depth;

[0048] Fig. 9 It is a comprehensive evaluation result diagram of the risk of string running in open hole completion provided in the embodiment of this specification;

[0049] Fig.10 It is a comprehensive evaluation result diagram of the risk of running into the pipe string during the liner completion provided in the embodiment of this specification;

[0050] Fig.11 It is a comprehensive evaluation result diagram of the risk of running the tubing string during perforation completion provided in the embodiment of this specification;

[0051] Fig.12 It is a comparison chart of the comprehensive evaluation results of string running risks of open hole completion, liner completion and perforation completion provided in the embodiments of this specification;

[0052] Fig.13 It is a prediction result diagram of the tonnage of the open hole completion string encountered resistance provided in the embodiment of this specification;

[0053] Fig.14 It is a schematic diagram of the structure of a completion method selection device provided in an embodiment of this specification;

[0054] Fig.15 It is a schematic diagram of the structural composition of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0055] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0056] Well completion engineering is a vital component in the oil and gas production process. The main task of well completion is to ensure good connectivity between the wellbore and the reservoir, so that the well can maintain high and stable production for a long period of time, and maintain the long-term stability of the wellbore. Well completion operations are directly related to the effects and economic benefits of oil and gas exploration and development. The choice of well completion method is the key to well completion operations. Whether the choice of a well completion method is reasonable is directly related to whether the future development and production of the well can proceed smoothly. The well completion method must match the geological characteristics of the production layer, must meet various engineering requirements in the long-term production process, and adapt to the changes in formation properties during oil and gas development, so as to reduce formation damage, increase oil and gas production, extend the life of oil and gas wells, and achieve the purpose of maximizing the exploitation of oil and gas resources. At present, the common well completion methods for oil and gas wells mainly include open hole completion, perforation completion, liner completion and other methods.

[0057] The selection of conventional completion methods is mainly determined by considering the reservoir type, rock mechanical properties, wellbore stability and sand production of the oil and gas well, combined with oil and gas well productivity analysis, completion operation cost and other factors. Generally, designers make qualitative selections based on field experience and regional conditions. This type of method requires high personal experience of designers and needs to meet the completion design requirements of medium and shallow oil and gas reservoirs.

[0058] With the change of oil and gas exploration and development targets, the burial depth of oil and gas reservoirs is developing towards deep and ultra-deep layers, the wellbore conditions, wellbore structure, and completion operation procedures are becoming more complicated, the procedures and risks faced by completion operations are greater, and the accuracy and scientificity requirements for the selection of completion methods are becoming higher and higher. Through literature research and combined with the actual needs of deep and ultra-deep well completion operations, it is concluded that the existing methods for selecting or determining completion methods have the following limitations:

[0059] (1) The existing completion selection methods are only applicable to a certain type of oil and gas reservoirs, such as carbonate fractured gas reservoirs and low permeability oil and gas reservoirs.

[0060] (2) The wellbore conditions, wellbore structures, and completion procedures of deep and ultra-deep wells are more complex. The existing completion selection methods do not consider the impact of the complexity of the oil and gas wellbore itself (such as changes in wellbore trajectory, temperature and pressure, casing size, and leakage degree) on the selection of completion methods;

[0061] (3) The existing method for selecting completion methods only considers geological factors such as reservoir characteristics, wellbore stability, and formation sand production, but does not consider the impact of engineering conditions, such as the friction resistance of the completion string, buckling, safety factor, and other engineering risks.

[0062] In view of the above-mentioned problems existing in the existing methods and the specific reasons for the above-mentioned problems, this application considers introducing a method, device and equipment for selecting a completion method. By comprehensively considering the wellbore complexity data and engineering data corresponding to different completion methods, the optimal completion method can be selected. This can improve the accuracy of the selection of the completion method and provide guidance for the formulation of risk control measures during the completion operation.

[0063] Based on the above ideas, this specification proposes a method for selecting a completion method. First, the membership of the wellbore complexity data corresponding to different completion methods is obtained. Secondly, the membership of the wellbore complexity data corresponding to different completion methods is processed using the wellbore complexity index prediction model to obtain the wellbore complexity index corresponding to the different completion methods. The wellbore complexity index prediction model is pre-established using the membership corresponding to the wellbore complexity data samples. Then, the engineering data corresponding to the different completion methods is obtained, and the risk levels corresponding to the different completion methods are determined based on the wellbore complexity index and the engineering data. Finally, based on the risk levels corresponding to the different completion methods, the target completion method is selected from the different completion methods. See. Figure 1 As shown, the embodiment of this specification provides a method for selecting a completion method. In specific implementation, the method may include the following contents.

[0064] S101: Obtaining the membership of wellbore complexity data corresponding to different completion methods.

[0065] In some embodiments, the above-mentioned different completion methods may include: open hole completion, perforation completion, liner completion, through-hole completion, gravel liner completion, etc. Of course, the completion methods are not limited to the above examples. Technical personnel in the relevant field may make other changes under the inspiration of the technical essence of the embodiments of this specification, but as long as the functions and effects achieved are the same or similar to those of the embodiments of this specification, they should be covered within the protection scope of the embodiments of this specification.

[0066] In some embodiments, the wellbore complexity data may include: wellbore trajectory tortuosity index, wellbore temperature, wellbore pressure, leakage, wellbore diameter expansion rate, and gap expansion rate. Accordingly, the membership of the wellbore complexity data corresponding to different completion methods may include:

[0067] Obtain the wellbore trajectory tortuosity index membership, wellbore temperature membership, wellbore pressure membership, leakage volume membership, wellbore diameter expansion rate membership, and gap expansion rate membership corresponding to different completion methods.

[0068] In some embodiments, the wellbore complexity data may also include: well inclination and azimuth, wherein the well inclination may be used to determine the well inclination arc length, and the azimuth may be used to determine the azimuth arc length; the wellbore trajectory tortuosity index may be determined based on the well inclination arc length and the azimuth arc length.

[0069] In some embodiments, since the borehole trajectory is a curve in three-dimensional space, the key parameters of the curve are represented by the well inclination angle and the azimuth angle, and the wellbore trajectory torsion index in three-dimensional space can be obtained by calculating the well inclination torsion index and the azimuth torsion index. Among them, the well inclination torsion index samples and the azimuth torsion index samples can be obtained in advance, and then the wellbore trajectory torsion index prediction model (or the wellbore trajectory torsion index calculation model) is established based on the well inclination torsion index samples and the azimuth torsion index samples. In actual application, the well inclination torsion index and the azimuth torsion index can be processed based on the wellbore trajectory torsion index prediction model established in advance to accurately and quickly obtain the wellbore trajectory torsion index.

[0070] In some embodiments, the wellbore trajectory tortuosity index may be determined based on the well inclination arc length and the azimuth arc length, and may include:

[0071] According to the well inclination arc length and azimuth arc length, the well inclination torsional index is determined according to the following formula:

[0072]

[0073] Among them, TI Inc is the well deviation torsional index; n is the number of curved sections divided in the wellbore trajectory; L IncC is the well inclination arc length, m; L AzmCi is the azimuth arc length of the i-th curve, m; L AzmSi is the arc length of the well inclination of the i-th curve;

[0074] According to the well inclination arc length and azimuth arc length, the azimuth distortion index is determined according to the following formula:

[0075]

[0076] Among them, TI Azmc is the azimuth distortion index; n is the number of curved sections in the wellbore trajectory; L Azmc is the azimuth arc length, m; L AzmCi is the azimuth arc length of the i-th curve, m; L AzmSi is the arc length of the well inclination of the i-th curve;

[0077] According to the well deviation torsional index and the azimuth torsional index, the wellbore trajectory torsional index is determined according to the following formula (which can be the wellbore trajectory torsional index prediction model mentioned above):

[0078]

[0079] Among them, TI 3Dis the wellbore trajectory tortuosity index in three-dimensional space (or wellbore tortuosity index in three-dimensional space); TI Inc is the well inclination torsional index; TI Azmc is the orientation distortion index.

[0080] In some embodiments, the above-mentioned obtaining of the wellbore trajectory tortuosity index membership corresponding to different completion methods may include:

[0081] Acquire an eye trajectory tortuosity, a first target eye trajectory tortuosity, and a second target eye trajectory tortuosity, wherein the first target eye trajectory tortuosity is greater than a preset eye trajectory tortuosity threshold, and the second target eye trajectory tortuosity is less than the preset eye trajectory tortuosity threshold;

[0082] The wellbore trajectory tortuosity index membership is determined according to the wellbore trajectory tortuosity, the first target wellbore trajectory tortuosity and the second target wellbore trajectory tortuosity.

[0083] In some embodiments, the first target eye trajectory tortuosity can be the maximum value of the wellbore trajectory tortuosity, and the second target eye trajectory tortuosity can be the minimum value of the wellbore trajectory tortuosity. The eye trajectory tortuosity can be the wellbore trajectory twist index. The method for obtaining the eye trajectory tortuosity can refer to the method for obtaining the wellbore trajectory twist index, which will not be described in detail in this specification. The preset eye trajectory tortuosity threshold can be set according to actual needs, and this specification does not specifically limit this.

[0084] In some embodiments, determining the wellbore trajectory tortuosity index membership according to the eye trajectory tortuosity, the first target eye trajectory tortuosity, and the second target eye trajectory tortuosity may include:

[0085] According to the following formula, the wellbore trajectory tortuosity index membership (linear processing method) is determined:

[0086]

[0087] Among them, TI 3D is the membership degree of the wellbore trajectory tortuosity index, x ij is the tortuosity of the wellbore trajectory at the depth position j of well i, x j,max is the first target well trajectory tortuosity (i.e. the maximum value of the well trajectory tortuosity), x j,min is the second target borehole trajectory tortuosity (i.e., the minimum value of the wellbore trajectory tortuosity).

[0088] In some embodiments, the above-mentioned obtaining of the wellbore temperature membership corresponding to different completion modes may include:

[0089] Establish the membership function corresponding to the wellbore temperature;

[0090] According to the membership function corresponding to the wellbore temperature, the wellbore temperature membership corresponding to different completion methods is determined.

[0091] In some embodiments, the membership function corresponding to the wellbore temperature may be established according to the following formula (exponential processing method):

[0092]

[0093] Where, T is the wellbore temperature membership; x is the wellbore temperature, °C; exp is an exponential function with the natural constant e as the base.

[0094] In some embodiments, the wellbore temperature membership corresponding to different completion methods can be determined based on the membership function corresponding to the wellbore temperature. The membership function corresponding to the wellbore temperature can be established in the following manner: First, the pre-set temperature division rule can be called. Then, the wellbore temperature can be divided according to the pre-set temperature division rule, such as: when the wellbore temperature <150°C, it can be divided into normal temperature; when the wellbore temperature is 150°C≤t<177°C, it can be divided into high temperature; when the wellbore temperature is 177°C≤t≤200°C, it can be divided into ultra-high temperature. Finally, according to the division result of the wellbore temperature, based on the fuzzy mathematics theory, an exponential processing method can be used to construct the membership function corresponding to the wellbore temperature (the constant in the membership function corresponding to the wellbore temperature can be determined in combination with field experience and the basic type of the fuzzy membership function (such as: exponential type), and this specification does not specifically limit this).

[0095] In some embodiments, the wellbore pressure membership can be determined according to the membership function corresponding to the wellbore pressure, the leakage amount membership can be determined according to the membership function corresponding to the leakage amount, the wellbore diameter expansion rate membership can be determined according to the membership function corresponding to the wellbore diameter expansion rate, and the gap expansion rate membership can be determined according to the membership function corresponding to the gap expansion rate. Among them, the establishment method of the membership function corresponding to the wellbore pressure, the membership function corresponding to the leakage amount, and the membership function corresponding to the wellbore diameter expansion rate can be the same as the establishment method of the membership function corresponding to the wellbore temperature, that is, the pre-set pressure division rule, the pre-set leakage amount division rule, and the pre-set wellbore diameter expansion rate division rule can be called in sequence. Then, the wellbore pressure is divided according to the pre-set pressure division rule, the leakage amount is divided according to the pre-set leakage division rule, and the wellbore diameter expansion rate (wellbore diameter expansion rate can also be called wellbore expansion rate) is divided according to the pre-set wellbore diameter expansion rate division rule. Finally, based on the division results corresponding to wellbore pressure, leakage, and wellbore expansion rate, the exponential processing method was used based on fuzzy mathematics theory to establish the membership functions corresponding to wellbore pressure, leakage, wellbore expansion rate, and gap expansion rate.

[0096] The membership function corresponding to the wellbore pressure can be established according to the following formula:

[0097]

[0098] Where P is the wellbore pressure membership; x 1 is the wellbore pressure; exp is an exponential function with the natural constant e as the base.

[0099] The membership function corresponding to the leakage amount can be established according to the following formula:

[0100]

[0101] Among them, η is the membership degree of the leakage amount; x 2 The amount of leakage.

[0102] The membership function corresponding to the wellbore expansion rate can be established according to the following formula:

[0103]

[0104] Among them, K is the membership degree of well diameter expansion rate; x 3 is the well diameter expansion rate.

[0105] In some embodiments, the gap expansion rate may be a gap expansion rate between tubulars or a gap expansion rate between a downhole tool (such as a drilling tool) and a casing or a gap expansion rate between open hole sections, or may be referred to as a gap value between tubulars or a gap value between a downhole tool (such as a drilling tool) and a casing or a gap value between open hole sections. The membership of the gap expansion rate may be determined according to a membership function corresponding to the gap expansion rate, wherein the membership function corresponding to the gap expansion rate may be established according to the following formula:

[0106]

[0107] Among them, K DS is the membership degree of gap expansion rate; x 4 is the clearance value, mm; exp is an exponential function with the natural constant e as the base; a and b are constants in the fuzzy membership function, which can be determined according to the tubing size and tool size of the specific well in practical application.

[0108] In some embodiments, the membership of the gap expansion rate corresponding to different completion methods can be determined based on the membership function corresponding to the above-mentioned gap expansion rate. The membership function corresponding to the gap expansion rate can be established in the following manner: First, call the pre-set gap expansion rate division rule. Then, the gap expansion rate can be divided according to the pre-set gap expansion rate division rule. The pre-set gap expansion rate division rule is as follows: when the gap value is ≤10mm, the gap degree can be divided into small; when the gap value is 10mm~50mm, the gap degree can be divided into medium; when the gap value is ≥50mm, the gap degree can be divided into large. Finally, according to the division result of the gap expansion rate, based on fuzzy mathematics theory, a small linear processing method is used to construct the membership function corresponding to the gap expansion rate.

[0109] In some embodiments, the above-mentioned preset temperature division rules and preset pressure division rules can be as shown in Table 1, and the above-mentioned preset leakage volume division rules, preset wellbore expansion rate division rules, and preset gap expansion rate division rules can be as shown in Table 2, Table 3, and Table 4, respectively.

[0110] Table 1 Temperature and pressure division rules

[0111]

[0112] Table 2 Rules for dividing the amount of leakage

[0113] Lost circulation type Micro-leakage Small leak Middle leakage Big leak Serious loss Leakage rate (m3 / d) ≤120 120～360 360～720 720～1440 ≥1440

[0114] Table 3 Well diameter expansion rate classification rules

[0115] Grading Small middle big Well diameter expansion rate (%) ≤8 8～15 ≥15

[0116] Table 4 Gap expansion rate division rules

[0117] Clearance Small middle big Clearance value (mm) ≤10 10～50 ≥50

[0118] In some embodiments, membership can refer to a numerical representation of the degree to which an element belongs to a set, usually represented by a real number between 0 and 1. It is a basic concept used to describe fuzzy sets, and can be used to represent the position and degree of belonging of an element in a set. In fuzzy set theory, membership is defined as a similarity measure between an element and a set, that is, a numerical value representing the degree to which an element belongs to a set. By obtaining the membership of the wellbore trajectory torsion index, the wellbore temperature, the wellbore pressure, the leakage volume, the wellbore expansion rate, and the clearance expansion rate corresponding to different completion methods, the foundation can be laid for accurately and quickly calculating the wellbore complexity index corresponding to different completion methods, thereby quantifying the complexity of the oil and gas wellbore itself.

[0119] S102: Using a wellbore complexity index prediction model to process the membership of wellbore complexity data corresponding to different completion methods, and obtain wellbore complexity indices corresponding to different completion methods, wherein the wellbore complexity index prediction model is pre-established using the membership corresponding to the wellbore complexity data samples.

[0120] In some embodiments, the wellbore complexity data samples may be obtained first, that is, the wellbore trajectory tortuosity index samples, wellbore temperature samples, wellbore pressure samples, leakage samples, wellbore diameter expansion rate samples, and gap expansion rate samples. Then, the membership corresponding to the wellbore complexity data samples may be obtained, that is, the membership corresponding to the wellbore trajectory tortuosity index samples, the membership corresponding to the wellbore temperature samples, the membership corresponding to the wellbore pressure samples, the membership corresponding to the leakage samples, the membership corresponding to the wellbore diameter expansion rate samples, and the membership corresponding to the gap expansion rate samples. Finally, according to the membership corresponding to the wellbore trajectory tortuosity index samples, the membership corresponding to the wellbore temperature samples, the membership corresponding to the wellbore pressure samples, the membership corresponding to the leakage samples, the membership corresponding to the wellbore diameter expansion rate samples, and the membership corresponding to the gap expansion rate samples, a wellbore complexity index prediction model may be established according to the following formula:

[0121] D co =w TI3D *TI 3D +w T *T+w P *P+w η *η+w K *K+w DS *K DS

[0122] Among them, D co is the wellbore complexity index; w TI3D is the weight corresponding to the well trajectory tortuosity index sample; TI 3D is the membership degree corresponding to the wellbore trajectory tortuosity index sample; w T is the weight corresponding to the wellbore temperature sample; T is the membership degree corresponding to the wellbore temperature sample; w P is the weight corresponding to the wellbore pressure sample; P is the membership degree corresponding to the wellbore pressure sample; w η is the weight corresponding to the missing sample; η is the membership degree corresponding to the missing sample; w K is the weight corresponding to the well diameter expansion rate sample; K is the membership degree corresponding to the well diameter expansion rate sample; w DS is the weight corresponding to the gap expansion rate sample; K DS is the membership degree corresponding to the gap expansion rate sample.

[0123] Among them, the weights corresponding to the wellbore complexity data samples can be determined by statistics of the on-site downhole complexity and combined with the expert system scoring. Of course, the method of determining the weights is not limited to the above examples. Technical personnel in the relevant field may make other changes under the inspiration of the technical essence of the embodiments of this specification, but as long as the functions and effects achieved are the same or similar to the embodiments of this specification, they should be covered within the protection scope of the embodiments of this specification.

[0124] By establishing a wellbore complexity index prediction model, the efficiency and accuracy of obtaining the wellbore complexity index can be improved. In specific implementation, it is only necessary to input the membership of the wellbore complexity data corresponding to different completion methods into the wellbore complexity index prediction model to obtain the wellbore complexity index corresponding to different completion methods. Before selecting the optimal completion method, by considering the complexity of the oil and gas wellbore itself, that is, considering the wellbore complexity index obtained by data such as eye trajectory distortion index, wellbore temperature, wellbore pressure, leakage, wellbore expansion rate, and gap expansion rate, it can lay the foundation for the subsequent establishment of a comprehensive and reliable risk assessment system, quantify the completion string entry risk of different completion methods, and select the optimal completion method.

[0125] S103: Acquire engineering data corresponding to different completion methods, and determine risk levels corresponding to different completion methods according to the wellbore complexity index and the engineering data.

[0126] In some embodiments, the engineering data may include: pipe string running friction, pipe string buckling index and triaxial safety factor. Accordingly, the risk level corresponding to different completion methods is determined according to the wellbore complexity index and the engineering data. In specific implementation, it may include:

[0127] Determine the target string entry friction resistance corresponding to different completion methods from the string entry friction resistance corresponding to different completion methods in turn, and determine the target triaxial safety factor corresponding to different completion methods in turn from the triaxial safety factors corresponding to different completion methods, wherein the target string entry friction group is greater than a preset string entry friction group threshold, and the target triaxial safety factor is less than a preset triaxial safety factor threshold;

[0128] The risk scoring rules corresponding to the wellbore complexity index, the tubing running friction resistance, the tubing buckling index and the triaxial safety factor are retrieved in sequence, and the risk values ​​corresponding to the wellbore complexity index, the target tubing running friction resistance, the tubing buckling index and the target triaxial safety factor are determined in sequence;

[0129] The risk values ​​of wellbore complexity index, target string running friction, string buckling index and target triaxial safety factor are summed to obtain the comprehensive risk values ​​corresponding to different completion methods.

[0130] According to the comprehensive risk values ​​corresponding to different completion methods, the risk levels corresponding to different completion methods are determined.

[0131] In some embodiments, the above-mentioned pipe string running friction resistance may be the friction resistance generated when the completion pipe string is run in different completion methods (the completion pipe string can be run in as part of the completion operation). The pipe string running friction resistance and the triaxial safety factor can be calculated using mature mechanical related theoretical models, which will not be elaborated in this specification. The above-mentioned pipe string buckling index can be defined as describing whether the pipe string has buckled and the degree of buckling, and the buckling index can be determined based on the axial force and the buckling imminent load (the calculation of the axial force and the buckling imminent load can refer to the existing calculation formula, which will not be elaborated in this specification). Specifically, the above-mentioned pipe string buckling index can be determined according to the axial force and the buckling imminent load according to the following formula:

[0132]

[0133] Where b is the pipe string buckling index. If the axial force is less than the critical buckling load, the pipe string buckling index is 1, which means that the pipe string has not buckled. If the axial force is greater than the critical buckling load, the pipe string buckling index is the ratio of the axial force to the critical buckling load, which means that the pipe string has buckled.

[0134] In some embodiments, after obtaining engineering data such as tubing friction resistance, tubing buckling index and triaxial safety factor, the above-mentioned wellbore complexity index, tubing friction resistance, tubing buckling index and triaxial safety factor can be combined to explore the influence of the wellbore complexity and engineering conditions on the selection of completion methods, so as to improve the accuracy of the selection of completion methods. Specifically, first, the target tubing friction resistance corresponding to different completion methods can be determined in turn from the tubing friction resistance corresponding to different completion methods, that is, the maximum tubing friction resistance corresponding to different completion methods can be determined, and the target triaxial safety factor corresponding to different completion methods can also be determined in turn from the triaxial safety factors corresponding to different completion methods, that is, the minimum triaxial safety factor corresponding to different completion methods can be determined. Then, the risk scoring rules corresponding to the wellbore complexity index, tubing friction resistance, tubing buckling index and triaxial safety factor can be retrieved in turn, and the risk values ​​corresponding to the wellbore complexity index, target tubing friction resistance, tubing buckling index and target triaxial safety factor can be determined in turn. That is, the risk scoring rules corresponding to the wellbore complexity index can be retrieved to determine the risk value corresponding to the wellbore complexity index; the risk scoring rules corresponding to the pipe string entry friction resistance can be retrieved to determine the risk value corresponding to the target pipe string entry friction resistance; the risk scoring rules corresponding to the pipe string buckling index can be retrieved to determine the risk value corresponding to the pipe string buckling index; the risk scoring rules corresponding to the triaxial safety factor can be retrieved to determine the risk value corresponding to the target triaxial safety factor. Finally, the sum of the risk values ​​corresponding to the wellbore complexity index, the target pipe string entry friction resistance, the pipe string buckling index, and the target triaxial safety factor can be determined as the comprehensive risk value, and the risk level corresponding to different completion methods can be determined according to the comprehensive risk values ​​corresponding to different completion methods.

[0135] Among them, the risk scoring rule corresponding to the wellbore complexity index can be: when the wellbore complexity index is ≤200, the risk value corresponding to the wellbore complexity index can be determined to be 1, and the risk rating is L (low); when 200<wellbore complexity index≤400, the risk value corresponding to the wellbore complexity index can be determined to be 3, and the risk rating is M (medium); when the wellbore complexity index is >400, the risk value corresponding to the wellbore complexity index can be determined to be 5, and the risk rating is H (high). The risk scoring rule corresponding to the wellbore complexity index can be referred to as shown in Table 5.

[0136] The risk scoring rules corresponding to the friction resistance of the pipe string can be: when the friction resistance tonnage is ≤3t (30KN), the risk value corresponding to the friction resistance of the pipe string can be determined to be 1, and the risk rating is L (low); when 3t (30KN) < friction resistance tonnage ≤5t (50KN), the risk value corresponding to the friction resistance of the pipe string can be determined to be 3, and the risk rating is M (medium); when the friction resistance tonnage is >5t (50KN), the risk value corresponding to the friction resistance of the pipe string can be determined to be 5, and the risk rating is H (high). The risk scoring rules corresponding to the friction resistance of the pipe string can be shown in Table 6.

[0137] The risk scoring rule corresponding to the pipe string buckling index can be: when the buckling index = 1, the risk value corresponding to the pipe string buckling index can be determined to be 1, and the risk rating is L (low); when 1 < buckling index < 2, the risk value corresponding to the pipe string buckling index can be determined to be 3, and the risk rating is M (medium); when the buckling index is ≥ 2, the risk value corresponding to the pipe string buckling index can be determined to be 5, and the risk rating is H (high). The risk scoring rule corresponding to the pipe string buckling index can be shown in Table 7.

[0138] The risk scoring rules corresponding to the three-axis safety factor can be: when the three-axis safety factor is ≥1.5, the risk value corresponding to the three-axis safety factor can be determined to be 1, and the risk rating is L (low); when 1.0≤three-axis safety factor<1.5, the risk value corresponding to the three-axis safety factor can be determined to be 3, and the risk rating is M (medium); when the three-axis safety factor is <1.0, the risk value corresponding to the three-axis safety factor can be determined to be 5, and the risk rating is H (high). The risk scoring rules corresponding to the three-axis safety factor can be referred to as shown in Table 8.

[0139] Table 5 Wellbore complexity index scoring table

[0140]

[0141]

[0142] Table 6 Pipe string entry friction score table

[0143]

[0144] Table 7 Pipe string buckling index score table

[0145] scope Flexion index = 1 1 < buckling index < 2 Flexion index ≥ 2 Risk Rating L(Low) M(Medium) H(High) Score (points) 1 3 5

[0146] Table 8 Three-axis safety factor table

[0147]

[0148] In some embodiments, a risk score combination chart (or table) can be established in advance based on the risk values ​​corresponding to the wellbore complexity index, string running friction, string buckling index and triaxial safety factor by superimposing 81 grid scores, such as Figure 2 As shown, Figure 2In the example, the risk values ​​of the wellbore complexity index can be set to 1, 3, and 5 respectively. Then, when the risk value of the wellbore complexity index is 1, the risk value of the friction resistance of the tubing is set to one group of 1, 3, and 5, the risk value of the tubing buckling index is set to three groups of 1, 3, and 5, and the risk value of the triaxial safety factor is set to 9 groups of 1, 3, and 5. When the risk value of the wellbore complexity index is 3 or 5, the same is true as above, and so on. Finally, a risk score combination chart (or table) is obtained. After establishing the risk score combination chart (or table), a risk level division chart (or table) can be further established based on the total score (i.e., comprehensive risk value) in the risk score combination chart (or table), such as Figure 3 As shown, Figure 3 Medium: If the comprehensive risk value is in the range of 4-6, the risk level of the completion method can be determined as an acceptable risk; if the comprehensive risk value is in the range of 8-10, the risk level of the completion method can be determined as a critical risk; if the comprehensive risk value is in the range of 12-20, the risk level of the completion method can be determined as an unacceptable risk. Among them, acceptable risk means that the risk of the completion method is low when the string is lowered, adjacent risk means that the risk of the completion method is moderate when the string is lowered, and unacceptable risk means that the risk of the completion method is high when the string is lowered.

[0149] In some embodiments, the risk levels corresponding to different completion methods are determined according to the comprehensive risk values ​​corresponding to different completion methods, that is, the risk level classification diagram (or table) pre-established above can be used to determine the risk range of the comprehensive risk value, and finally, the risk levels corresponding to different completion methods are determined. For example: the comprehensive risk value for open hole completion is 8, the comprehensive risk value for liner completion is 6, and the comprehensive risk value for perforation completion is 6. It can be determined that the risk range of the comprehensive risk values ​​of liner completion and perforation completion is within the range of 4-6, and the risk level of liner completion and perforation completion is an acceptable risk, which means that the risk of string running in liner completion and perforation completion is low, and the risk range of the comprehensive risk value of open hole completion is 8, which is within the range of 8-10. It can be determined that the risk level of open hole completion is critical risk, that is, the risk of string running in open hole completion is moderate.

[0150] By establishing a risk scoring combination diagram (or table) in advance based on the wellbore complexity index, tubing running friction, tubing buckling index and triaxial safety factor, and then further establishing a risk level classification diagram (or table), the risk levels corresponding to different completion methods can be accurately and quickly determined based on the comprehensive risk values ​​of different completion methods, thereby laying the foundation for subsequently screening out the optimal completion method based on the risk levels of different completion methods.

[0151] S104: Selecting a target completion method from different completion methods according to risk levels corresponding to different completion methods.

[0152] In some embodiments, the above-mentioned selecting a target completion method from different completion methods according to the risk levels corresponding to different completion methods may include:

[0153] The risk levels corresponding to different completion methods are compared to determine a target risk level in the risk level and a target completion method corresponding to the target risk level, wherein the target risk level includes an acceptable risk.

[0154] In some embodiments, after determining the risk levels corresponding to different completion methods, such as determining that the risk level of open hole completion is a critical risk and the risk levels of liner completion and perforation completion are acceptable risks, the risk levels corresponding to different completion methods can be compared, and then the acceptable risks among the risk levels are selected, and the target completion method corresponding to the acceptable risks is determined. The target completion method can be used as the optimal completion method, that is, the completion method with the lowest risk of tubing running. For example, the risk levels of open hole completion, liner completion, and perforation completion can be compared. Since the risk levels of liner completion and perforation completion are acceptable risks, liner completion and perforation completion can be used as the optimal completion methods.

[0155] In some embodiments, after selecting the target completion method from different completion methods, the specific implementation may also include:

[0156] According to the risk levels corresponding to different completion methods, risk control measures corresponding to different completion methods are formed;

[0157] Based on the risk control measures, different degrees of risk control are performed on completion operations under different completion methods.

[0158] In some embodiments, after selecting the optimal completion method, guidance can also be provided for the formulation of risk management measures during the completion operation. That is, different risk management measures can be formed according to the risk levels of different completion methods. For completion methods that are at imminent risk and unacceptable risk, risk management can be strengthened during the completion operation, thereby achieving the purpose of ensuring the safety of the completion operation.

[0159] The above method is described below in conjunction with a specific embodiment. However, it should be noted that this specific embodiment is only for better illustrating the present application and does not constitute an improper limitation on the present application.

[0160] Before specific implementation, data samples such as well depth, well inclination, azimuth, leakage, borehole diameter expansion rate, and gap expansion rate can be collected during the actual drilling of oil and gas wells. The well inclination arc length sample and azimuth arc length sample can also be determined using the well inclination and azimuth data samples, and then the well inclination torsion index sample and azimuth torsion index sample can be determined based on the well inclination arc length sample and azimuth arc length sample, and then the wellbore trajectory torsion index prediction model can be established based on the wellbore trajectory torsion index sample and azimuth torsion index sample, and the wellbore trajectory torsion index sample can be obtained based on the wellbore trajectory torsion index prediction model. The wellbore temperature sample and wellbore pressure sample can also be calculated using the existing mature theoretical model. The membership corresponding to the leakage sample, borehole diameter expansion rate sample, gap expansion rate sample, wellbore trajectory torsion index sample, wellbore temperature sample, and wellbore pressure sample can also be determined, and then the wellbore complexity index prediction model can be established based on the membership corresponding to the data sample.

[0161] In specific implementation, the wellbore complexity index prediction model can be used to process the membership of the wellbore complexity data corresponding to different completion methods, and obtain the wellbore complexity index corresponding to different completion methods. Then, the tubing running friction resistance, tubing buckling index, and triaxial safety factor corresponding to different completion methods are obtained. Then, a tubing running risk evaluation index system based on the wellbore complexity index, tubing running friction resistance, tubing buckling index, and triaxial safety factor is established. Based on the tubing running risk evaluation index system, the tubing running risks of different completion methods can be quantitatively evaluated, and the completion method with the lowest risk can be selected as the optimal completion method.

[0162] By comprehensively considering the complexity of the wellbore itself and the key engineering data of the string running risk of the oil and gas well, a risk assessment system is established to quantitatively analyze the string running risk of different completion methods and evaluate the adaptability of different completion methods, so as to effectively guide the selection of completion methods and improve the accuracy of the selection of completion methods. After determining the string running risk of different completion methods, it can also provide guidance for the formulation of risk control measures during the completion operation to ensure the safety of the completion operation.

[0163] In a specific scenario example, a horizontal well can be taken as an example to comprehensively evaluate the string running risks in different completion methods and select the optimal completion method. The specific implementation can include the following steps:

[0164] Step 1: Collect basic parameters such as well depth, well inclination, azimuth, leakage, well diameter expansion rate, and gap between the tubing string / downhole tool and the casing / open hole section (or gap expansion rate) during the actual drilling process of the oil and gas well;

[0165] Step 2: Pre-establish a wellbore trajectory torsional index prediction model (or wellbore trajectory torsional index calculation model), and obtain the wellbore trajectory torsional index at different well depths in the entire wellbore based on the established wellbore trajectory torsional index prediction model;

[0166] Step 3: Based on the existing mature theoretical model, obtain the wellbore temperature and pressure data;

[0167] Step 4: Pre-establish a wellbore complexity index prediction model (or wellbore complexity index calculation model), wherein the weights of various influencing factors in the wellbore complexity index prediction model can be determined by statistically analyzing the complex conditions of the wellbore on site and combining them with expert system scoring. The wellbore complexity index can be obtained by first establishing the wellbore complexity index prediction model;

[0168] Step 5: Obtain engineering data, such as string running friction, string buckling index, and triaxial safety factor, and then establish a string running risk evaluation index system for different completion methods based on wellbore complexity index, string running friction, string buckling index, and triaxial safety factor (that is, a risk scoring combination chart (or table), risk level classification chart (or table) can be established) to quantitatively evaluate the string running risks of different completion methods and determine the optimal completion method.

[0169] Among them, see Figure 4 As shown, Figure 4 The curves showing the variation of well inclination and azimuth with well depth are shown. Figure 4 The left side is the curve of the change of well inclination (or horizontal section extension distance) with well depth. Figure 4 The right side shows the curve of the change of azimuth with well depth. Figure 4 As can be seen on the left: as the well depth increases, the horizontal section extension distance also increases. Figure 4 It can be seen on the right that as the horizontal segment extends, the azimuth gradually changes from north to south.

[0170] See also Figure 5 As shown, Figure 5 The curve of wellbore size (i.e. well diameter) changing with well depth is shown. Figure 5 It can be seen that with the increase of well depth, the wellbore size fluctuates. When the well depth increases to 7500m, 7650m, and 7700m, the increase in well diameter is large. Among them, when the well depth reaches 7700m, the increase in well diameter is the largest.

[0171] See also Figure 6 As shown, Figure 6 The curve of the wellbore trajectory tortuosity index changing with well depth is shown. Figure 6It can be seen that when the well depth is 0m-5000m, the corresponding wellbore trajectory torsion index does not change; when the well depth is 5000m-8000m, the corresponding wellbore trajectory torsion index does not change; when the well depth increases to 5000m, the wellbore trajectory torsion index begins to decrease.

[0172] See also Figure 7 , Figure 8 As shown, Figure 7 The pressure curve is shown as the depth of the well changes. Figure 8 The temperature curve is shown as the temperature changes with the depth of the well. Figure 7 , 8 It can be seen that as the well depth increases, the pressure and temperature increase linearly.

[0173] See also Fig. 9 , Fig.10 , Fig.11 As shown, Fig. 9 The comprehensive evaluation results of string running risk during open hole completion are shown. Fig.10 The comprehensive evaluation results of the risk of string running during liner completion are shown. Fig.11 The comprehensive evaluation results of the risk of string running during perforation completion are shown. Fig. 9 , Fig.10 , Fig.11 It can be seen that the risk score or risk value of openhole completion is 8, the risk score or risk value of liner completion is 6, and the risk score or risk value of perforation completion is 6; the complexity index or wellbore complexity index of openhole completion, liner completion, and perforation completion is 141.9; the maximum friction resistance of openhole completion, liner completion, and perforation completion is 157.9kN, 113.2kN, and 93.4kN, respectively; the minimum triaxial safety factors of openhole completion, liner completion, and perforation completion are 2.24, 2.14, and 2.12, respectively (where the minimum safety factor is calculated on the basis of axial force, friction resistance, and Mises stress calculations with the help of existing mechanical analysis software); the buckling sections where tubing buckling occurs in openhole completion, liner completion, and perforation completion are 6394-6710m, none, and none, respectively. The above data and the pre-established risk level classification diagram (or table) and risk level classification diagram (or table) can be combined to establish a comparison diagram (or table) of the comprehensive evaluation results of string running risks for open hole completion, liner completion, and perforation completion. Fig.12 It can be seen that the risk level of open hole completion is critical risk, which is higher than liner completion and perforation completion. Therefore, liner completion or perforation completion is recommended for this well, that is, liner completion or perforation completion can be used as the optimal completion method.

[0174] See also Fig.13 As shown, Fig.13The figure shows the prediction result of the tonnage of the open hole completion string (wherein the prediction result of the tonnage of the resistance can be calculated based on the weight of the string in the mud minus the friction resistance, and the existing tonnage calculation algorithm of the resistance can be referred to, which will not be repeated in this specification). Fig.13 It can be seen that when the well depth increases by 7000m, the obstruction tonnage of open hole completion begins to change. When the well depth is 7000m-9000m, the obstruction tonnage of open hole completion shows a trend of first increasing, then decreasing, and then increasing again. By predicting the obstruction tonnage of the string running into the open hole completion, targeted risk prevention and control measures can be specified to ensure the safety of the open hole completion operation.

[0175] Although this specification provides examples such as the following embodiments or the attached Fig.14 The method operation steps or device structure shown in the figure, but based on routine or without creative labor, the method or device may include more or fewer operation steps or module units after partial merger. In the steps or structures where there is no necessary causal relationship logically, the execution order of these steps or the module structure of the device is not limited to the execution order or module structure shown in the embodiments or drawings of this specification. When the method or module structure described is applied in an actual device, server or terminal product, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiment or drawings (for example, a parallel processor or multi-threaded processing environment, or even a distributed processing, server cluster implementation environment).

[0176] Based on the above-mentioned method for selecting a completion method, this specification also proposes an embodiment of a device for selecting a completion method. Fig.14 As shown, the device may specifically include the following modules:

[0177] The acquisition module 1401 can be used to obtain the membership of wellbore complexity data corresponding to different completion methods;

[0178] The prediction module 1402 can be used to process the membership of the wellbore complexity data corresponding to different completion methods using the wellbore complexity index prediction model to obtain the wellbore complexity index corresponding to the different completion methods, wherein the wellbore complexity index prediction model is pre-established using the membership corresponding to the wellbore complexity data sample;

[0179] The determination module 1403 may be used to obtain engineering data corresponding to different completion methods, and determine the risk levels corresponding to the different completion methods according to the wellbore complexity index and the engineering data;

[0180] The selection module 1404 may be used to select a target completion method from different completion methods by comparing the risk levels corresponding to the different completion methods.

[0181] In some embodiments, the wellbore complexity data in the above-mentioned acquisition module 1401 may include: wellbore trajectory tortuosity index, wellbore temperature, wellbore pressure, leakage volume, wellbore diameter expansion rate, and gap expansion rate; the above-mentioned acquisition module 1401 can be specifically used to obtain the wellbore trajectory tortuosity index membership, wellbore temperature membership, wellbore pressure membership, leakage volume membership, wellbore diameter expansion rate membership, and gap expansion rate membership corresponding to different completion methods.

[0182] In some embodiments, the wellbore complexity data in the above-mentioned acquisition module 1401 may also include: well inclination and azimuth, the well inclination can be used to determine the well inclination arc length, and the azimuth can be used to determine the azimuth arc length; the wellbore trajectory torsion index is determined based on the well inclination arc length and the azimuth arc length.

[0183] In some embodiments, the above-mentioned acquisition module 1401 can also be specifically used to obtain the eye trajectory tortuosity, the first target eye trajectory tortuosity and the second target eye trajectory tortuosity, the first target eye trajectory tortuosity is greater than the preset eye trajectory tortuosity threshold, and the second target eye trajectory tortuosity is less than the preset eye trajectory tortuosity threshold; according to the eye trajectory tortuosity, the first target eye trajectory tortuosity and the second target eye trajectory tortuosity, the membership of the wellbore trajectory distortion index is determined.

[0184] In some embodiments, the acquisition module 1401 may be specifically used to establish a membership function corresponding to the wellbore temperature; and determine the wellbore temperature membership corresponding to different completion methods according to the membership function corresponding to the wellbore temperature.

[0185] In some embodiments, the prediction module 1402 may be used to establish a wellbore complexity index prediction model according to the following formula:

[0186] D co =w TI3D *TI 3D +w T *T+w P *P+w η *η+w K *K+w DS *K DS

[0187] Among them, D co is the wellbore complexity index; w TI3D is the weight corresponding to the well trajectory tortuosity index sample; TI 3D is the membership degree corresponding to the wellbore trajectory tortuosity index sample; w T is the weight corresponding to the wellbore temperature sample; T is the membership degree corresponding to the wellbore temperature sample; w P is the weight corresponding to the wellbore pressure sample; P is the membership degree corresponding to the wellbore pressure sample; wη is the weight corresponding to the missing sample; η is the membership degree corresponding to the missing sample; w K is the weight corresponding to the well diameter expansion rate sample; K is the membership degree corresponding to the well diameter expansion rate sample; w DS is the weight corresponding to the gap expansion rate sample; K DS is the membership degree corresponding to the gap expansion rate sample.

[0188] In some embodiments, the engineering data in the above-mentioned determination module 1403 may include: tubing entry friction resistance, tubing string buckling index and triaxial safety factor; the above-mentioned determination module 1403 can be specifically used to sequentially determine the target tubing entry friction resistance corresponding to different completion methods from the tubing entry friction resistance corresponding to different completion methods, and sequentially determine the target triaxial safety factors corresponding to different completion methods from the triaxial safety factors corresponding to different completion methods, the target tubing entry friction group is greater than a preset tubing entry friction group threshold, and the target triaxial safety factor is less than a preset triaxial safety factor. Full coefficient threshold; call the risk scoring rules corresponding to the wellbore complexity index, tubing friction resistance, tubing buckling index and triaxial safety factor in turn, and determine the risk values ​​corresponding to the wellbore complexity index, target tubing friction resistance, tubing buckling index and target triaxial safety factor in turn; sum the risk values ​​corresponding to the wellbore complexity index, target tubing friction resistance, tubing buckling index and target triaxial safety factor to obtain the comprehensive risk values ​​corresponding to different completion methods; determine the risk levels corresponding to different completion methods according to the comprehensive risk values ​​corresponding to different completion methods.

[0189] In some embodiments, the selection module 1404 can be specifically used to compare the risk levels corresponding to different completion methods, determine the target risk level in the risk level and the target completion method corresponding to the target risk level, wherein the target risk level includes an acceptable risk.

[0190] It should be noted that the units, devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described separately by functions divided into various modules. Of course, when implementing this specification, the functions of each module can be implemented in the same or more software and / or hardware, or the modules that implement the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] It can be seen from the above that a completion method selection device provided in the embodiments of this specification can not only quantify the string running risks of different completion methods, but also accurately select the completion method with the lowest risk level.

[0192] The embodiments of the present specification also provide an electronic device based on the above-mentioned completion method selection method, including a processor and a memory for storing instructions executable by the processor, wherein the processor can perform the following steps according to the instructions when implemented: obtaining the membership of wellbore complexity data corresponding to different completion methods; using a wellbore complexity index prediction model to process the membership of wellbore complexity data corresponding to different completion methods to obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is pre-established using the membership corresponding to wellbore complexity data samples; obtaining engineering data corresponding to different completion methods, and determining the risk levels corresponding to different completion methods according to the wellbore complexity index and the engineering data; and selecting a target completion method from different completion methods according to the risk levels corresponding to different completion methods.

[0193] In order to complete the above instructions more accurately, refer to Fig.15 As shown, the embodiment of this specification also provides another specific electronic device, wherein the electronic device includes a network communication port 1501, a processor 1502 and a memory 1503, and the above structures are connected through internal cables so that each structure can perform specific data interaction.

[0194] The network communication port 1501 can be used to obtain the degree of membership of wellbore complexity data corresponding to different completion methods.

[0195] The processor 1502 can be specifically used to use the wellbore complexity index prediction model to process the membership of the wellbore complexity data corresponding to different completion methods, and obtain the wellbore complexity index corresponding to the different completion methods, wherein the wellbore complexity index prediction model is pre-established using the membership corresponding to the wellbore complexity data samples; obtain the engineering data corresponding to the different completion methods, and determine the risk levels corresponding to the different completion methods according to the wellbore complexity index and the engineering data; and select the target completion method from the different completion methods according to the risk levels corresponding to the different completion methods.

[0196] The memory 1503 may be specifically used to store corresponding instruction programs.

[0197] In this embodiment, the network communication port 1501 can be a virtual port that is bound to different communication protocols so that different data can be sent or received. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. In addition, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it can also be a Bluetooth chip.

[0198] In this embodiment, the processor 1502 may be implemented in any appropriate manner. For example, the processor may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, etc. This specification does not limit this.

[0199] In this embodiment, the memory 1503 may include multiple levels. In a digital system, anything that can store binary data can be a memory; in an integrated circuit, a circuit with a storage function that has no physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0200] The embodiments of the present specification also provide a computer storage medium based on the above-mentioned completion method selection method, wherein the computer storage medium stores computer program instructions, and when the computer program instructions are executed, the following are achieved: obtaining the membership of wellbore complexity data corresponding to different completion methods; using a wellbore complexity index prediction model to process the membership of wellbore complexity data corresponding to different completion methods to obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is pre-established using the membership corresponding to wellbore complexity data samples; obtaining engineering data corresponding to different completion methods, and determining the risk levels corresponding to different completion methods based on the wellbore complexity index and the engineering data; and selecting a target completion method from different completion methods based on the risk levels corresponding to different completion methods.

[0201] In this embodiment, the storage medium includes, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a cache, a hard disk (HDD), or a memory card. The memory may be used to store computer program instructions. The network communication unit may be an interface for network connection communication set in accordance with the standard specified by the communication protocol.

[0202] Although the present specification provides method operation steps as described in the embodiments or flow charts, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way of executing the order of many steps, and does not represent a unique execution order. When the device or client product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such a process, method, product or device. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. The first, second, etc. words are used to represent the name, and do not represent any particular order.

[0203] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules for implementing the method and structures within the hardware component.

[0204] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media including storage devices.

[0205] Through the description of the above embodiments, it can be known that those skilled in the art can clearly understand that the present specification can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present specification can essentially be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in each embodiment of the present specification or some parts of the embodiments.

[0206] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. This specification can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0207] Although the present specification is described through embodiments, persons skilled in the art will appreciate that there are many variations of the present specification without departing from the spirit of the present specification, and it is intended that the appended claims include these variations without departing from the spirit of the present specification.

Claims

1. A method for selecting a completion method, characterized in that: The method comprises: Obtain the membership of wellbore complexity data corresponding to different completion methods; Using a wellbore complexity index prediction model to process the membership of wellbore complexity data corresponding to different completion methods, and obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples; Acquire engineering data corresponding to different completion methods, and determine risk levels corresponding to different completion methods according to the wellbore complexity index and the engineering data; According to the risk levels corresponding to different completion methods, a target completion method is selected from different completion methods.

2. The method according to claim 1, characterized in that The wellbore complexity data includes: wellbore trajectory tortuosity index, wellbore temperature, wellbore pressure, leakage, wellbore diameter expansion rate, and gap expansion rate; accordingly, the degree of membership of the wellbore complexity data corresponding to different completion methods includes: Obtain the wellbore trajectory tortuosity index membership, wellbore temperature membership, wellbore pressure membership, leakage volume membership, wellbore diameter expansion rate membership, and gap expansion rate membership corresponding to different completion methods.

3. The method according to claim 2, characterized in that The wellbore complexity data also includes: well inclination and azimuth, the well inclination is used to determine the well inclination arc length, and the azimuth is used to determine the azimuth arc length; the wellbore trajectory torsionalness index is determined based on the well inclination arc length and the azimuth arc length.

4. The method according to claim 2, characterized in that: The obtaining of the wellbore trajectory tortuosity index membership corresponding to different completion methods includes: Acquire an eye trajectory tortuosity, a first target eye trajectory tortuosity, and a second target eye trajectory tortuosity, wherein the first target eye trajectory tortuosity is greater than a preset eye trajectory tortuosity threshold, and the second target eye trajectory tortuosity is less than the preset eye trajectory tortuosity threshold; Determine the wellbore trajectory twisting index membership according to the wellbore trajectory tortuosity, the first target wellbore trajectory tortuosity, and the second target wellbore trajectory tortuosity; The obtaining of the wellbore temperature membership corresponding to different completion methods includes: Establish the membership function corresponding to the wellbore temperature; According to the membership function corresponding to the wellbore temperature, the wellbore temperature membership corresponding to different completion methods is determined.

5. The method according to claim 1, characterized in that The wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples, and includes: According to the following formula, the wellbore complexity index prediction model is established: D co =w TI3D *TI 3D +w T *T+w P *P+w η *η+w K *K+w DS *K DS Among them, D co is the wellbore complexity index; w TI3D is the weight corresponding to the well trajectory tortuosity index sample; TI 3D is the membership degree corresponding to the wellbore trajectory tortuosity index sample; w T is the weight corresponding to the wellbore temperature sample; T is the membership degree corresponding to the wellbore temperature sample; w P is the weight corresponding to the wellbore pressure sample; P is the membership degree corresponding to the wellbore pressure sample; w η is the weight corresponding to the missing sample; η is the membership degree corresponding to the missing sample; w K is the weight corresponding to the well diameter expansion rate sample; K is the membership degree corresponding to the well diameter expansion rate sample; w DS is the weight corresponding to the gap expansion rate sample; K DS is the membership degree corresponding to the gap expansion rate sample.

6. The method according to claim 1, characterized in that The engineering data includes: pipe string running friction, pipe string buckling index and triaxial safety factor. Accordingly, the risk level corresponding to different completion methods is determined according to the wellbore complexity index and the engineering data, including: Determine the target string entry friction resistance corresponding to different completion methods from the string entry friction resistance corresponding to different completion methods in turn, and determine the target triaxial safety factor corresponding to different completion methods in turn from the triaxial safety factors corresponding to different completion methods, wherein the target string entry friction group is greater than a preset string entry friction group threshold, and the target triaxial safety factor is less than a preset triaxial safety factor threshold; The risk scoring rules corresponding to the wellbore complexity index, the tubing running friction resistance, the tubing buckling index and the triaxial safety factor are retrieved in sequence, and the risk values ​​corresponding to the wellbore complexity index, the target tubing running friction resistance, the tubing buckling index and the target triaxial safety factor are determined in sequence; The risk values ​​corresponding to the wellbore complexity index, target string running friction, string buckling index and target triaxial safety factor are summed to obtain the comprehensive risk values ​​corresponding to different completion methods. According to the comprehensive risk values ​​corresponding to different completion methods, the risk levels corresponding to different completion methods are determined.

7. The method according to claim 1, characterized in that The selecting of a target completion method from different completion methods according to the risk levels corresponding to different completion methods includes: The risk levels corresponding to different completion methods are compared to determine a target risk level in the risk level and a target completion method corresponding to the target risk level, wherein the target risk level includes an acceptable risk.

8. A device for selecting a completion method, characterized in that: The device comprises: An acquisition module, used to obtain the membership of wellbore complexity data corresponding to different completion methods; A prediction module, used to process the membership of wellbore complexity data corresponding to different completion methods using a wellbore complexity index prediction model to obtain wellbore complexity indexes corresponding to different completion methods, wherein the wellbore complexity index prediction model is established in advance using the membership corresponding to the wellbore complexity data samples; A determination module, used to obtain engineering data corresponding to different completion methods, and determine the risk levels corresponding to the different completion methods according to the wellbore complexity index and the engineering data; The selection module is used to select a target completion method from different completion methods according to the risk levels corresponding to the different completion methods.

9. A device for selecting a completion method, characterized in that: The method comprises a processor and a memory for storing processor-executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the instructions.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the instructions are executed, the steps of the method according to any one of claims 1 to 7 are implemented.

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