Method for predicting maximum load of drilling machine

Abstract

The invention relates to the field of oil and gas drilling engineering, in particular to a method for predicting the maximum load of a drilling machine, which comprises the following steps of: acquiring basic data of a historical completed drilling well; calculating the maximum tubular column weight in the well drilling and completion operation of each drilled well based on the basic data; calculating the difference value between the maximum tubular column weight in the well drilling and completion operation of each drilled well and the maximum load data in the actual drilling process to obtain a difference value sample; determining difference value sample probability distribution; calculating an overload margin based on the difference sample probability; and calculating the maximum load of the drilling machine in the drilling and completion process of the to-be-drilled well at least based on the overload allowance. The method can be widely applied to prediction and calculation of the maximum load of the drilling machine in the well drilling and completion process, and has very important significance on drilling machine model selection, equipment matching and drilling construction safety evaluation. According to the method, the reliability of the calculation result is ensured by utilizing the condition data such as the well track or trajectory, the friction resistance, the drilling fluid density and the tubular column material density parameter.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas drilling engineering, and in particular to a method for predicting the maximum load of a drilling rig, and in particular to a method for predicting the maximum load of an oil and gas well drilling rig. Background Art

[0002] The hook load refers to the axial force borne by the hook. It is one of the important basic data for drilling rig selection and equipment matching, and is also one of the important bases for drilling construction safety assessment. In the process of drilling, completion and handling of complex accidents, the load borne by the hook includes the deadweight of the drilling rig lifting system and the pipe string, the buoyancy of the drilling fluid, the bending force of the curved well section, the frictional resistance of the well wall, and the impact force when encountering resistance and jamming. Among them, the calculation of bending force, frictional resistance and impact force is relatively complicated. Therefore, in the design of drilling engineering, it is very important to accurately predict the hook load for drilling rig selection and equipment matching, and to avoid the waste of drilling costs caused by the large selection of drilling rig level.

[0003] At present, the existing oil industry recommended standard SY / T 5724-2008 "Casing String Structure and Strength Design" and the public monograph "Oil and Gas Well Pipe String Mechanics and Engineering" (China University of Petroleum Press, published in October 2006) disclose the axial force calculation model of vertical wells, two-dimensional wellbores and three-dimensional wellbores, dividing the wellbore trajectory or trajectory into N micro-element segments, and recursively calculating the axial force of different pipe strings under different working conditions based on the balance principle of static load and different mathematical models. This calculation method performs micro-unit calculations and superimposed solutions based on different wellbore trajectories and pipe string combinations, which can predict the maximum load of the drilling rig and calculate the large hook load during drilling construction. It has high reliability and is recognized by drilling industry technicians. The disadvantage is that the calculation model is complex, the calculation process is cumbersome, and professional software is required to obtain the results, which is not conducive to use on-site drilling operations.

[0004] Based on this, there is still room for improvement in the existing technology. Summary of the invention

[0005] This application summarizes various aspects of the embodiments and should not be used to limit the claims. Other embodiments are conceivable based on the technology described herein, which will be apparent to those skilled in the art after studying the following drawings and detailed descriptions, and these embodiments are intended to be included within the scope of this application.

[0006] The purpose of the present invention is to provide a method for predicting the maximum load of an oil drilling rig, so as to solve the problems of the currently used complex calculation model and cumbersome calculation process, and to predict the maximum load of the drilling rig during operation, and to reasonably select the drilling rig and related equipment according to the predicted maximum load. The present invention collects conditional data such as the borehole track or trajectory of the completed well, friction, drilling fluid density, pipe string material density, and maximum hook load data monitored by the on-site weight indicator of the completed well, calculates the maximum pipe string weight in the drilling and completion operation of the completed well, and determines the overload margin by probabilistic analysis of the difference between the maximum pipe string weight in the drilling and completion operation of the completed well and the maximum load data in the actual drilling process, thereby predicting the maximum load of the drilling rig in the drilling and completion process of the well to be drilled, and comparing it with 80% of the rated load of the drilling rig to determine the drilling rig level. The present invention ensures the scientificity and economy of the drilling rig selection, and avoids the waste of drilling costs caused by the large selection of drilling rig levels.

[0007] Specifically, the present invention provides a method for predicting the maximum load of a drilling rig, which includes the following steps: a. acquiring basic data of historical completed drilling; b. calculating the maximum tubular weight in the drilling and completion operations of each completed well based on the basic data; c. calculating the difference between the maximum tubular weight in the drilling and completion operations of each completed well and the maximum load data during the actual drilling process to obtain a difference sample; d. determining the probability distribution of the difference sample; e. calculating the overload margin based on the probability of the difference sample; f. calculating the maximum load of the drilling rig during the drilling and completion process of the well to be drilled at least based on the overload margin.

[0008] In an embodiment of the present invention, step a includes: obtaining basic data of historical completed wells within a predetermined time, and the basic data includes at least one of the designed well depth of each completed well, the vertical projection length of the tubing, the horizontal projection length of the tubing, the drilling fluid density, the tubing material density, the weight per unit length of the tubing in the air, the friction coefficient, the weight of the swimming system and the maximum hook load data monitored by the weight indicator at the completion site.

[0009] In an embodiment of the present invention, in step b, the maximum string weight in the drilling and completion operation of each completed well is calculated based on the following formula (1):

[0010] F1=(L1·G+F·L2·G)·[1-(2·ρ1) / (3·ρ2)] Formula (1)

[0011] Among them, F1 is the maximum tubing weight in the drilling and completion operation; L1 is the vertical projection length of the tubing for the completed well; L2 is the horizontal projection length of the tubing; ρ1 is the drilling fluid density; ρ2 is the tubing material density; G is the weight per unit length of the tubing in the air; and F is the friction coefficient.

[0012] In an embodiment of the present invention, in step c, the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process is calculated based on the following formula (2):

[0013] f2=(1.2·F1+Q1)-b Formula (2)

[0014] Among them, Q1 is the weight of the traveling system; f2 is the difference between the maximum tubing weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process; b is the maximum hook load data monitored by the on-site weight indicator of the completed well, and the difference sample includes a set of differences in the number of completed wells.

[0015] In an embodiment of the present invention, in step d, the probability distribution of the difference sample is determined based on the probability distribution function, wherein the probability distribution function includes at least one of contrast normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution.

[0016] In the embodiment of the present invention, the contrast normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution are respectively expressed as the following formulas (3) to (7):

[0017] normal distribution:

[0018] In formula (3), μ is the mathematical expectation of the random variable, and σ is the standard deviation of the random variable;

[0019] Lognormal distribution:

[0020] In formula (4), μ and σ are the logarithmic mean and logarithmic standard deviation of the random variable x, respectively;

[0021] Weibull Distribution:

[0022] In formula (5), η and β are the scale parameter and shape parameter respectively;

[0023] Gamma distribution:

[0024] In formula (6), α and β represent the shape and scale of the distribution, respectively, where a, β ≥ 0; Γ(α) is the gamma function;

[0025] Logistic distribution:

[0026] In formula (7), α is the location parameter and β>0 is the shape parameter, which is a constant.

[0027] In an embodiment of the present invention, step e includes: calculating different probabilities based on different probability functions, and calculating the difference between the maximum string weight in the drilling and completion operation of each completed well corresponding to the different probabilities and the maximum load data in the actual drilling process, and calculating the overload margin based on the following formula (8):

[0028] F2=|f2| Formula (8)

[0029] Among them, F2 is the overload margin.

[0030] In an embodiment of the present invention, in step f, the maximum load of the drilling rig during the drilling and completion process of the well to be drilled is calculated based on the following formula (9):

[0031] Q2=1.2·F1+Q1+F2 Formula (9)

[0032] Among them, Q2 is the maximum load of the drilling rig during the drilling and completion process.

[0033] In an embodiment of the present invention, the method for predicting the maximum load of a drilling rig further comprises: g. determining the drilling rig level based on the maximum load of the drilling rig during the drilling and completion process.

[0034] In an embodiment of the present invention, step g comprises: comparing the maximum load of the drilling rig during the drilling and completion process with a predetermined percentage of the rated load of the drilling rig, and selecting the drilling rig grade based on the comparison result.

[0035] The technical effects of the present invention are at least:

[0036] (1) Importance. In drilling engineering, the present invention can be widely used in the prediction and calculation of the maximum load of the drilling rig during the drilling and completion process, which is of great significance for the selection of drilling rigs, equipment matching and safety assessment of drilling construction.

[0037] (2) Reliability. The method of the present invention ensures the reliability of the calculation results by using conditional data such as wellbore trajectory or track, friction, drilling fluid density, and string material density parameters.

[0038] (3) Scientificity. The method of the present invention determines the overload margin by probabilistically analyzing the difference between the maximum string weight in the drilling and completion operation and the maximum load data in the actual drilling process, thereby ensuring the scientificity of the calculation result.

[0039] (4) Economical. The method described in the present invention standardizes the overload margin value, expands the applicable well depth of the drilling rig, and avoids the waste of drilling costs caused by selecting a large drilling rig level.

[0040] Those skilled in the art will understand and appreciate these and other aspects, objects and features of the present disclosure after studying the following specification, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] For a more complete understanding of the embodiments of the present application, reference should be made to the embodiments illustrated in more detail in the accompanying drawings and described by way of example below, in which:

[0042] Figure 1 It is a schematic diagram of several common trajectories, where L1 is the vertical projection length of the completed wellbore string, and L2 is the horizontal projection length of the string;

[0043] Figure 2 is a flow chart of a method for predicting maximum load of a drilling rig provided by an embodiment of the present invention;

[0044] Figure 3 It is the normal distribution and logistic distribution probability diagram of the difference sample f2 (well depth MD<3000m);

[0045] Figure 4 It is the normal distribution and logistic distribution histogram of the difference sample f2 (well depth MD<3000m);

[0046] Figure 5 It is the normal distribution and logistic distribution probability diagram of the difference sample f2 (3000<well depth MD<4000m);

[0047] Figure 6 It is the normal distribution and logistic distribution histogram of the difference sample f2 (3000<well depth MD<4000m);

[0048] Figure 7 It is the normal distribution and logistic distribution probability diagram of the difference sample f2 (4000<well depth MD<5000m);

[0049] Figure 8 is the normal distribution and logistic distribution histogram of the difference sample f2 (4000<well depth MD<5000m); and

[0050] Fig. 9 is a flow chart of a method for predicting maximum load of a drilling rig according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] Embodiments of the present disclosure are described below. However, it should be understood that the disclosed embodiments are merely examples, and other embodiments may take various alternative forms. The drawings are not necessarily drawn to scale; certain features may be exaggerated or minimized to show the details of a particular component. Therefore, the specific structural and functional details disclosed herein should not be interpreted as limiting, but merely as a representative basis for teaching those skilled in the art to use the present application in various ways. As will be understood by those skilled in the art, the various features shown and described with reference to any one of the figures may be combined with the features shown in one or more other figures to produce embodiments that are not explicitly shown or described. The combination of features shown provides representative embodiments for typical applications. However, various combinations and modifications of features consistent with the teachings of the present disclosure may be desirable for certain specific applications or embodiments.

[0052] Furthermore, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or action from another entity or action, and do not necessarily require or imply any actual such relationship or order between such entities or actions. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but may also include elements not expressly listed or inherent to such process, method, article, or apparatus.

[0053] One or more embodiments of the present application will be described below in conjunction with the accompanying drawings. The flowchart illustrates the process performed by the system according to the present application. It can be understood that the execution of the flowchart does not need to be performed in sequence, one or more steps can be omitted, one or more execution steps can be added, and one or more steps can be performed in sequence or in reverse order, and even in some embodiments, one or more steps can be performed simultaneously.

[0054] According to the present invention, a method for predicting the maximum load of a drilling rig is provided. Figure 2 As shown, it includes the following steps:

[0055] a. Obtain basic data of historically completed drilling;

[0056] b. Calculate the maximum string weight in the drilling and completion operation of each completed well based on the basic data;

[0057] c. Calculate the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data during the actual drilling process to obtain a difference sample;

[0058] d. Determine the probability distribution of the difference sample;

[0059] e. Calculate the overload margin based on the difference sample probability;

[0060] f. Calculate the maximum load of the drilling rig during the drilling and completion of the well to be drilled based at least on the overload margin.

[0061] In an embodiment of the present invention, step a includes: obtaining basic data of historical well completions within a predetermined time, and the basic data includes at least one of the designed well depth MD of each completed well, the vertical projection length L1 of the tubular column, the horizontal projection length L2 of the tubular column, the drilling fluid density ρ1, the tubular column material density ρ2, the weight G of the tubular column per unit length in the air, the friction coefficient F, the weight Q1 of the traveling system, and the maximum hook load data b monitored by the weight indicator at the completion site. The vertical projection length L1 of the tubular column and the horizontal projection length L2 of the tubular column can be based on Figure 1 The three-segment trajectory, double-increasing trajectory, and five-segment trajectory shown in are obtained.

[0062] In an embodiment of the present invention, in step b, the maximum string weight in the drilling and completion operation of each completed well is calculated based on the following formula (1):

[0063] F1=(L1·G+F·L2·G)·[1-(2·ρ1) / (3·ρ2)] Formula (1)

[0064] Among them, F1 is the maximum tubing weight in the drilling and completion operation; L1 is the vertical projection length of the tubing for the completed well; L2 is the horizontal projection length of the tubing; ρ1 is the drilling fluid density; ρ2 is the tubing material density; G is the weight per unit length of the tubing in the air; and F is the friction coefficient.

[0065] In an embodiment of the present invention, in step c, the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process is calculated based on the following formula (2):

[0066] f2=(1.2·F1+Q1)-b Formula (2)

[0067] Among them, Q1 is the weight of the traveling system; f2 is the difference between the maximum tubing weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process; b is the maximum hook load data monitored by the on-site weight indicator of the completed well, and the difference sample includes a set of differences in the number of completed wells.

[0068] In an embodiment of the present invention, in step d, the probability distribution of the difference sample is determined based on the probability distribution function, wherein the probability distribution function includes at least one of contrast normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution.

[0069] In the embodiment of the present invention, the contrast normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution are respectively expressed as the following formulas (3) to (7):

[0070] normal distribution:

[0071] In formula (3), μ is the mathematical expectation of the random variable, and σ is the standard deviation of the random variable;

[0072] Lognormal distribution:

[0073] In formula (4), μ and σ are the logarithmic mean and logarithmic standard deviation of the random variable x, respectively;

[0074] Weibull Distribution:

[0075] In formula (5), η and β are the scale parameter and shape parameter respectively;

[0076] Gamma distribution:

[0077] In formula (6), α and β represent the shape and scale of the distribution, respectively, where a, β ≥ 0; Γ(α) is the gamma function;

[0078] Logistic distribution:

[0079] In formula (7), α is the location parameter and β>0 is the shape parameter, which is a constant.

[0080] In an embodiment of the present invention, step e includes: calculating different probabilities based on different probability functions, and calculating the difference between the maximum string weight in the drilling and completion operation of each completed well corresponding to the different probabilities and the maximum load data in the actual drilling process, and calculating the overload margin based on the following formula (8):

[0081] F2=|f2| Formula (8)

[0082] Among them, F2 is the overload margin.

[0083] In an embodiment of the present invention, in step f, the maximum load of the drilling rig during the drilling and completion process of the well to be drilled is calculated based on the following formula (9):

[0084] Q2=1.2·F1+Q1+F2 Formula (9)

[0085] Among them, Q2 is the maximum load of the drilling rig during the drilling and completion process.

[0086] In an embodiment of the present invention, Figure 2 As shown, the method for predicting the maximum load of the drilling rig further includes: g. determining the drilling rig level based on the maximum load of the drilling rig during the drilling and completion process.

[0087] In an embodiment of the present invention, step g comprises: comparing the maximum load of the drilling rig during the drilling and completion process with a predetermined percentage of the rated load of the drilling rig, and selecting the drilling rig grade based on the comparison result.

[0088] In the embodiment of the present invention, the predetermined percentage is 80%.

[0089] Further references Fig. 9 , which shows a flow chart of a method for predicting the maximum load of a drilling rig provided by an embodiment of the present invention. The method may specifically include the following steps:

[0090] Step 1: Obtain the basic data of completed wells for one year, including the designed well depth MD of each completed well, the vertical projection length L1 of the tubing, the horizontal projection length L2 of the tubing, the density of the drilling fluid ρ1, the density of the tubing material ρ2, the weight G per unit length of the tubing in the air, the friction coefficient F, the weight of the swimming system Q1, and the maximum hook load data b monitored by the weight indicator at the completion well site.

[0091] Step 2: Calculate the maximum string weight F1 of each completed well using formula (1):

[0092] F1=(L1·G+F·L2·G)·[1-(2·ρ1) / (3·ρ2)] (1)

[0093] Where: F1 is the maximum string weight in the drilling and completion operation, in kN; L1 is the vertical projection length of the completed string, in m; L2 is the horizontal projection length of the string, in m; ρ1 is the drilling fluid density, in g / cm 3 ; ρ2 is the density of the column material, in g / cm 3 ; G is the weight per unit length of the pipe in the air, in kN / m; F is the friction coefficient, dimensionless.

[0094] Step 3: Calculate the difference f2 between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data during the actual drilling process, and obtain the difference sample f 2i , where i = 1,…,N max , N max The number of wells drilled.

[0095] According to formula (2), the difference f2 between the maximum string weight in the completed drilling and completion operation and the maximum load data in the actual drilling process is calculated to obtain the difference sample f 2i , where i = 1,…,N max , N max The number of wells drilled.

[0096] f2=(1.2·F1+Q1)-b (2)

[0097] Where, F1 is the maximum string weight during drilling and completion operations, in kN; Q1 is the weight of the traveling system, in kN; f2 is the difference, in kN; and b is the maximum hook load data monitored by the weight indicator at the completion site, in kN.

[0098] Step 4: Difference sample f 2i Determination of probability distribution. The choice of probability distribution is to compare and analyze the five distribution types of normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution, and to evaluate the goodness of fit, and finally select the probability distribution type suitable for the difference between the maximum string weight in the drilling and completion operation and the maximum hook load data monitored by the weight indicator on the completion site. The five probability distribution functions are as follows:

[0099] normal distribution:

[0100] Where μ is the mathematical expectation of the random variable and σ is the standard deviation of the random variable.

[0101] Lognormal distribution:

[0102] Where μ and σ are the logarithmic mean and logarithmic standard deviation of the random variable x, respectively.

[0103] Weibull Distribution:

[0104] Where η and β are the scale parameter and shape parameter respectively.

[0105] Gamma distribution:

[0106] Where α and β represent the shape and scale of the distribution, respectively, where a, β ≥ 0; Γ(α) is the gamma function.

[0107] Logistic distribution:

[0108] Where α is the location parameter, β>0 is the shape parameter, and is a constant.

[0109] Step 5: Determination of overload margin F2. Use probability function to calculate different probabilities, and calculate the corresponding difference f2 under different probabilities, and take the absolute value. The obtained value is the overload margin F2.

[0110] F2=|f2| (8)

[0111] Step 6: Predict the maximum load Q2 of the drilling rig during the drilling and completion process of the well to be drilled.

[0112] According to the overload margin F2 obtained in step 5 and formula (8), the maximum load Q2 of the drilling rig during the drilling and completion process of the well to be drilled is predicted.

[0113] Q2=1.2·F1+Q1+F2 (9)

[0114] Where Q2 is the maximum load of the drilling rig during drilling and completion, in kN; F1 is the maximum string weight during drilling and completion operations, in kN; Q1 is the weight of the swimming system, in kN; F2 is the overload margin, in kN.

[0115] Step 7: Determine the drilling rig level.

[0116] According to the requirements of the drilling rig rated load, the following formula is used:

[0117] Q×80%≥Q2 (10)

[0118] Where, Q is the rated load of the drilling rig, in kN; Q2 is the maximum load of the drilling rig during drilling and completion, in kN.

[0119] According to the maximum load Q2 of the drilling rig during drilling and completion calculated in step 6, compared with 80% of the rated load Q of the drilling rig, as shown in Table 1, the appropriate drilling rig level is selected.

[0120] Table 1 Drilling rig selection parameters

[0121]

[0122]

[0123] The present invention is further described below by a specific embodiment:

[0124] 171 wells are known to be completed. The maximum load of the drilling rig during the drilling and completion of the wells to be drilled will be calculated by the method of the present invention.

[0125] (1) Input data

[0126] Enter the basic data of each completed well and number the wells, see Table 2 for details.

[0127] Table 2 Basic data table

[0128]

[0129]

[0130]

[0131]

[0132] (2) Calculate the maximum string weight F1 in the drilling and completion operations of a well in one year

[0133] Calculate according to formula (1), and the results are shown in Table 3.

[0134] Table 3 Maximum pipe string weight in drilling and completion operations

[0135]

[0136]

[0137] (3) Calculate the difference f2 between the maximum string weight in the completed drilling and completion operation and the maximum load data in the actual drilling process. The calculation results are shown in Table 4. The difference sample f 2i , where i=1,…,171.

[0138] The difference f2 is calculated according to formula (2).

[0139] Table 4 Difference f2

[0140]

[0141]

[0142]

[0143] (4) Difference sample f 2i Determination of probability distribution.

[0144] Perform probability distribution analysis based on samples.

[0145] According to the well depth MD, the samples are divided into three samples: difference sample f2 (well depth MD < 3000m), f2 (3000 < well depth MD < 4000m), and f2 (4000 < well depth MD < 5000m), as shown in Tables 5, 6, and 7.

[0146] Table 5 Difference f2 (well depth MD < 3000m)

[0147]

[0148]

[0149] Probabilistic analysis is performed on the difference sample f2 (well depth MD<3000m).

[0150] like Figure 3 , 4 As shown, the analysis results: the difference sample f2 (well depth MD<3000m) conforms to the logistic distribution.

[0151] Table 6 Difference f2 (3000 < Well Depth MD < 4000m)

[0152] Serial number MD <![CDATA[f2]]> Serial number MD <![CDATA[f2]]> Serial number MD <![CDATA[f2]]> 118 3030 185.09 129 3241 706.37 140 3600 -466.87 119 3035 -693.90 130 3285 -350.33 141 3620 -127.30 120 3100 193.82 131 3312 -207.17 142 3621 -346.72 121 3135 289.06 132 3331 116.65 143 3633 -261.20 122 3136 363.15 133 3350 4.27 144 3756 228.61 123 3150 -307.44 134 3374 224.45 145 3778 120.37 124 3159 101.21 135 3389 295.74 146 3813 -41.66 125 3185 224.74 136 3405 -993.52 147 3835 822.99 126 3234 -468.73 137 3511 -252.31 148 3845 27.90 127 3235 16.22 138 3533 -17.13 149 3883 -370.75 128 3239 -289.97 139 3545 -632.42 150 3898 585.50

[0153] A probability analysis is performed on the difference sample f2 (3000<well depth MD<4000m).

[0154] like Figure 5 , 6 As shown, the analysis results: the difference sample f2 (3000<well depth MD<4000m) is more consistent with the logistic distribution.

[0155] Table 7 Difference f2 (4000 < Well Depth MD < 5000m)

[0156]

[0157] A probability analysis is performed on the difference sample f2 (4000<well depth MD<5000m).

[0158] like Figure 7 , 8 As shown, the analysis results: the difference sample f2 (4000<well depth MD<5000m) is more consistent with the logistic distribution.

[0159] (5) Determination of overload margin prediction value F2

[0160] The overload margin prediction value F2 is calculated according to formula (7). The calculation results are shown in Tables 8, 9 and 10.

[0161] Table 8 Calculation results of overload margin prediction value F2 (well depth MD<3000m)

[0162] Cumulative probability <![CDATA[f2]]> <![CDATA[F2]]> 0.01 -658.045 658.045 0.02 -556.623 556.623 0.03 -496.672 496.672 0.04 -453.692 453.692 0.05 -420.003 420.003 0.06 -392.184 392.184 0.07 -368.412 368.412 0.08 -347.597 347.597 0.09 -329.035 329.035 0.1 -312.248 312.248

[0163] Table 9 Calculation results of overload margin prediction value F2 (3000<well depth MD<4000m)

[0164] Cumulative probability <![CDATA[f2]]> <![CDATA[F2]]> 0.01 -1064.38 1064.38 0.02 -907.068 907.068 0.03 -814.083 814.083 0.04 -747.419 747.419 0.05 -695.166 695.166 0.06 -652.019 652.019 0.07 -615.148 615.148 0.08 -582.863 582.863 0.09 -554.073 554.073 0.1 -528.036 528.036

[0165] Table 10 Calculation results of overload margin prediction value F2 (4000<well depth MD<5000m)

[0166] Cumulative probability <![CDATA[f2]]> <![CDATA[F2]]> 0.01 -378.365 378.365 0.02 -271.232 271.232 0.03 -207.906 207.906 0.04 -162.505 162.505 0.05 -126.919 126.919 0.06 -97.534 97.534 0.07 -72.423 72.423 0.08 -50.436 50.436 0.09 -30.829 30.829 0.1 -13.097 13.097

[0167] According to the results in Tables 8-10, the value of F2 is selected when the cumulative probability is 0.05, as shown in Table 11:

[0168] Table 11F2 value table

[0169] Well depth MD<3000m 3000<Well depth MD<4000m 4000<Well depth MD<5000m <![CDATA[Value of F2]]> 420 700 130

[0170] (6) Predict the maximum load Q of the drilling rig during the drilling and completion process of the well to be drilled

[0171] The basic parameters of wells N107X1 and B138X1 are shown in Table 12.

[0172] Table 12 Basic parameters of N107X1 and B138X1 wells

[0173]

[0174] According to the well depth MD and the value of F2 in Table 11, the maximum load Q of the drilling rig during drilling and completion is predicted according to formula (8). The results are shown in Table 13.

[0175] Table 13 Prediction results of maximum rig load Q during drilling and completion of wells N107X1 and B138X1

[0176]

[0177] (7) Determination of drilling rig level

[0178] According to the parameters in Table 1 and the prediction results in Table 13, the rig level selection is shown in Table 14.

[0179] Table 14 Results of rig grade selection for N107X1 and B138X1 wells

[0180]

[0181] Error analysis of calculation results:

[0182]

[0183] By applying the method described in the present invention, the maximum load of the drilling rig during operation can be predicted, and the drilling rig and related equipment can be reasonably selected according to the predicted maximum load.

[0184] The method of the present invention collects conditional data such as borehole track or trajectory, friction, drilling fluid density, pipe string material density, and maximum hook load data monitored by the on-site weight indicator of the completed well, calculates the maximum pipe string weight in the drilling and completion operation of the completed well, and determines the overload margin by probabilistic analysis of the difference between the maximum pipe string weight in the drilling and completion operation of the completed well and the maximum load data in the actual drilling process, thereby predicting the maximum load of the drilling rig in the drilling and completion process of the well to be drilled, and comparing it with 80% of the rated load of the drilling rig to determine the drilling rig level. The present invention ensures the scientificity and economy of the drilling rig selection, and avoids the waste of drilling costs caused by the large selection of the drilling rig level.

[0185] This application document is intended to illustrate how to use the disclosed technology and various embodiments, but is not intended to limit the scope and spirit to which it is actually directed and equivalent. In addition, the above description is not intended to be exhaustive of all possibilities or to limit the scope of protection to the precise form disclosed. According to the above teachings, changes and variations are possible. The selected and illustrated embodiments provide the best description of the principles of the technology and its practical application, and enable those skilled in the art to use the disclosed technology for various changes in various conceivable specific applications. Therefore, without substantially departing from the spirit and principles of the technology described herein, the various changes and modifications made to the above embodiments are intended to be included in the scope of this disclosure.

Claims

1. A method for predicting maximum load of a drilling rig, characterized in that: The following steps are involved: a. Obtain basic data of historically completed drilling; b. Calculate the maximum string weight in the drilling and completion operation of each completed well based on the basic data; c. Calculate the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data during the actual drilling process to obtain a difference sample; d. Determine the probability distribution of the difference sample; e. Calculate the overload margin based on the difference sample probability; f. Calculate the maximum load of the drilling rig during the drilling and completion of the well to be drilled based at least on the overload margin.

2. The method for predicting the maximum load of a drilling rig according to claim 1, characterized in that: Step a includes: obtaining basic data of historical completed wells within a predetermined time, and the basic data includes at least one of the designed well depth of each completed well, the vertical projection length of the tubing, the horizontal projection length of the tubing, the density of the drilling fluid, the density of the tubing material, the weight per unit length of the tubing in the air, the friction coefficient, the weight of the swimming system and the maximum hook load data monitored by the weight indicator at the completion site.

3. The method for predicting the maximum load of a drilling rig according to claim 2, characterized in that: In step b, the maximum string weight in the drilling and completion operation of each completed well is calculated based on the following formula (1): F1=(L1·G+F·L2·G)·[1-(2·ρ1) / (3·ρ2)] Formula (1) Among them, F1 is the maximum tubing weight in the drilling and completion operation; L1 is the vertical projection length of the tubing for the completed well; L2 is the horizontal projection length of the tubing; ρ1 is the drilling fluid density; ρ2 is the tubing material density; G is the weight per unit length of the tubing in the air; and F is the friction coefficient.

4. The method for predicting the maximum load of a drilling rig according to claim 3, characterized in that: In step c, the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data during the actual drilling process is calculated based on the following formula (2): f2=(1.2·F1+Q1)-b Formula (2) Among them, Q1 is the weight of the traveling system; f2 is the difference between the maximum tubing weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process; b is the maximum hook load data monitored by the on-site weight indicator of the completed well, and the difference sample includes a set of differences in the number of completed wells.

5. The method for predicting the maximum load of a drilling rig according to claim 4, characterized in that: In step d, the probability distribution of the difference samples is determined based on a probability distribution function, wherein the probability distribution function includes at least one of a contrast normal distribution, a lognormal distribution, a Weibull distribution, a gamma distribution, and a logistic distribution.

6. The method for predicting the maximum load of a drilling rig according to claim 5, characterized in that: The normal distribution, lognormal distribution, Weibull distribution, gamma distribution, and logistic distribution are respectively expressed as the following formulas (3) to (7): normal distribution: In formula (3), μ is the mathematical expectation of the random variable, and σ is the standard deviation of the random variable; Lognormal distribution: In formula (4), μ and σ are the logarithmic mean and logarithmic standard deviation of the random variable x, respectively; Weibull Distribution: In formula (5), η and β are the scale parameter and shape parameter respectively; Gamma distribution: In formula (6), α and β represent the shape and scale of the distribution, respectively, where a, β ≥ 0; Γ(α) is the gamma function; Logistic distribution: In formula (7), α is the location parameter and β>0 is the shape parameter, which is a constant.

7. The method for predicting the maximum load of a drilling rig according to claim 6, characterized in that: Step e includes: calculating different probabilities based on different probability functions, and calculating the difference between the maximum string weight in the drilling and completion operation of each completed well and the maximum load data in the actual drilling process under different probabilities, and calculating the overload margin based on the following formula (8): F2=|f2| Formula (8) Among them, F2 is the overload margin.

8. The method for predicting the maximum load of a drilling rig according to claim 7, characterized in that: In step f, the maximum load of the drilling rig during the drilling and completion process of the well to be drilled is calculated based on the following formula (9): Q2=1.2·F1+Q1+F2 Formula (9) Among them, Q2 is the maximum load of the drilling rig during the drilling and completion process.

9. The method for predicting the maximum load of a drilling rig according to claim 1, characterized in that: Further including: g. Determine the drilling rig level based on the maximum load of the drilling rig during drilling and completion.

10. The method for predicting the maximum load of a drilling rig according to claim 9, characterized in that: Step g comprises: comparing the maximum load of the drilling rig during the drilling and completion process with a predetermined percentage of the rated load of the drilling rig, and selecting the drilling rig grade based on the comparison result.

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