PDC (Polycrystalline Diamond Compact) drill bit damage assessment method based on logging-while-drilling data and fuzzy mathematics

Abstract

The invention relates to the technical field of PDC drill bit damage assessment, and particularly discloses a PDC drill bit damage assessment method based on measurement while drilling logging data and fuzzy mathematics, which comprises the following steps: cleaning the measurement while drilling logging data, and removing data which does not conform to a predetermined standard or is identified as an abnormal value; selecting variables with significant volatility as characteristic variables for drill bit damage prediction; establishing a damage calculation model of the PDC drill bit according to a fuzzy pattern recognition method; and evaluating the total damage of the PDC drill bit. The damage assessment method for the PDC drill bit under the influence of the stratum rock property is established by using statistics to select parameters based on a large amount of data acquired by field logging and element analysis, and theoretical guidance is provided for predicting the damage degree of the PDC drill bit in real time in the drilling process and adjusting the time for changing the drill bit according to actual conditions.

Description

Technical Field

[0001] The invention relates to the technical field of PDC drill bit damage assessment, and in particular to a PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics. Background Art

[0002] As oil and gas exploration deepens, PDC (polycrystalline diamond composite) drill bits are increasingly used in oil and gas well drilling. However, damage assessment of PDC drill bits has always been a difficult problem in oil and gas well engineering, directly affecting drilling efficiency and cost. There is no doubt that the formation conditions are the first key factor in drill bit damage. The harder the formation is, the poorer the drillability is. The stronger the damage to the drill teeth during drilling, the shorter the drill bit life will be. The second is the influence of drilling parameters. Under high drilling pressure and high speed, the drill bit is subjected to great energy, which intensifies the damage.

[0003] In well logging, the radioactivity decreases from igneous rock, metamorphic rock to sedimentary rock, that is, the larger the gamma value, the stronger the radioactivity, the higher the hardness of the rock, and the worse the drillability; from the element logging data, it can be found that the higher the silicon and calcium content of the rock, the more minerals such as quartz, feldspar and mica it contains, the harder the rock is, and the greater the damage to the drill bit.

[0004] The hardness of a rock has a great influence on the drill bit, and the reason for this is mainly due to its mineral composition. Generally speaking, rocks containing the following elements usually have higher hardness: (1) Silicon (Si): Silicon is the main component of many minerals, such as quartz. Quartz is a very hard mineral, so rocks containing silicon may have higher hardness. (2) Aluminum (Al): Aluminum is also the main component of some hard minerals, such as sapphire and garnet. (3) Iron (Fe): Iron is present in many minerals, including magnetite. Some rocks containing iron may have higher hardness. (4) Calcium (Ca): Calcium is the main component of some minerals and rocks, such as marble. Marble is generally relatively hard. The presence and combination of these elements will affect the hardness of the rock, and different types of rocks have different hardnesses.

[0005] Therefore, it is of great significance to use the logging data while drilling combined with fuzzy mathematics theory to analyze the damage and service life of the drill bit. The accuracy and authenticity of the data used are very high, which plays a key role in the damage assessment of the drill bit. Summary of the invention

[0006] In order to solve the problems existing in the prior art, the present invention provides a PDC drill bit damage assessment method based on while drilling logging data and fuzzy mathematics. By real-time monitoring of while drilling logging data, including drilling parameters and element logging data in logging data, and using fuzzy mathematics theory to analyze and process the data, a basis is provided for the assessment and judgment of drill bit damage, thereby solving the problems mentioned in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solution: a PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics, comprising the following steps:

[0008] S1. Clean up the logging while drilling data and remove the data that does not meet the predetermined standards or is identified as an outlier;

[0009] S2. Select variables with significant volatility as characteristic variables for drill bit damage prediction;

[0010] S3, establishing a damage calculation model of the PDC drill bit according to the fuzzy pattern recognition method;

[0011] S4. Overall damage assessment of PDC drill bits.

[0012] Preferably, in step S1, the logging data while drilling includes gamma spectrum, drilling pressure, rotation speed, drilling time and the content of main element components in the cuttings; the data that does not meet the predetermined standard or is identified as an outlier refers to: data obtained by logging under the working conditions of tripping, circulation, reaming and electrical logging.

[0013] Preferably, the main element components include Mg, Al, Si, P, S, Cl, K and Ca.

[0014] Preferably, in step S2, specifically including: firstly, obtaining the average value of the gamma spectrum, drilling pressure, rotation speed, drilling time and the content of the main elements in the cuttings, the average value formula is expressed as:

[0015] in, represents the average value of each variable in the logging data while drilling, n represents the total number of data points of each variable, j represents the jth data point in the data of each variable, x ij Indicates the value of the jth data point in the i-th variable data;

[0016] Then, the data of the variable fluctuates within 20% of the mean value. The variable is considered to have no damage effect on the drill bit, and its damage effect on the drill bit is ignored. The variables in the interval are used as characteristic variables for predicting drill bit damage. The more characteristic variables there are, the more accurate the description of drill bit damage is.

[0017] Preferably, in step S3, it specifically includes:

[0018] S31, fuzzy variable matrix construction: according to the characteristic variables (x1 x2 ... x i ... x m ) T Combine feature variable data rows into a fuzzy variable matrix

[0019] S32. Use matrix standardization method to establish samples: Perform maximum value standardization on each element in the fuzzy variable matrix to establish samples, that is,

[0020] Among them, M j Indicates the maximum value of the j-th column data, M j =max(x 1j ,x 2j ,…,x mj ); x′ ij represents the data in row i and column j after standardization, x mn Represents the nth data of the mth variable;

[0021] S33. Establish a fuzzy set of drill bit damage degree: Assume the damage matrix Each set of characteristic variables constitutes a set y j is the domain of the problem, is a fuzzy set on the domain, is the degree to which the jth group of data belongs to damage. Considering that the selected characteristic variables have different influences on the damage of PDC drill bits, a parameter α is set. i The weight coefficient representing the influence of different parameters on the degree of drill bit damage;

[0022] S34. Using the pattern recognition method, the samples are classified into the fuzzy set of drill bit damage degree calculation, and the damage calculation model of the PDC drill bit is obtained. The formula is expressed as follows:

[0023] Preferably, in step S32, the weight coefficient α i The value of depends on the degree of fluctuation of the variable data with the depth of the well. The greater the fluctuation, the greater the weight coefficient.

[0024] Preferably, in step S4, damage results of drill bits at different well depths are calculated according to the damage calculation model of the PDC drill bit in step S34, and the total damage of the PDC drill bit is accumulated by combining the damage results of drill bits at different well depths.

[0025] The beneficial effects of the present invention are as follows: the present invention combines logging data while drilling and fuzzy mathematics, and can more accurately evaluate the damage of PDC drill bits, reducing the errors caused by traditional empirical evaluation methods or subjective judgments. By using logging data while drilling, the model can realize real-time monitoring, so that drill bit damage can be discovered in time during the drilling process and corresponding measures can be taken, thereby improving drilling efficiency. At the same time, it can be promoted and applied in multiple drilling projects and under different geological conditions, and has wide applicability and market potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics in an embodiment of the present invention;

[0027] Figure 2 Schematic diagram of characteristic variables in an embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of the result of characteristic variable standardization in an embodiment of the present invention;

[0029] Figure 4 This is a diagram showing the damage changes of a PDC drill bit in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1-Figure 4 The present invention provides a technical solution: a PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics, such as Figure 1 As shown, the following steps are included:

[0032] S1. Clean up the logging while drilling data and remove the data that does not meet the predetermined standards or is identified as an outlier.

[0033] The logging data while drilling include gamma spectrum, drilling pressure, rotation speed, drilling time and the content of main elements in the cuttings; the data that do not meet the predetermined standards or are identified as abnormal values ​​refer to the data obtained by logging under the conditions of tripping, circulation, reaming and electrical logging. The main elements include Mg, Al, Si, P, S, Cl, K and Ca.

[0034] In this embodiment, the logging data: γ spectrum, drilling parameters: drilling pressure, rotation speed, element logging data: Mg, Al, Si, P, S, Cl, K and Ca content are screened. The screening process is as follows: Figure 2 As shown; after screening, the characteristic variables are determined to be: γ energy spectrum, drilling pressure, rotation speed, Ca, Al, and Si.

[0035] S2. Use statistical analysis to select data rows with fluctuations exceeding 20% ​​of the average value, and select variables with significant volatility as characteristic variables for drill bit damage prediction.

[0036] Further, the specific method includes: firstly, obtaining the average value of the gamma spectrum, drilling pressure, rotation speed, drilling time and the content of the main elements in the cuttings, and the average value formula is expressed as:

[0037] in, represents the average value of each variable in the logging data while drilling, n represents the total number of data points of each variable, j represents the jth data point in the data of each variable, x ij Indicates the value of the jth data point in the i-th variable data;

[0038] Then, the data of the variable fluctuates within 20% of the mean value. The variable is considered to have no damage effect on the drill bit, and its damage effect on the drill bit is ignored. The variables in the interval are used as characteristic variables for predicting drill bit damage. The more characteristic variables there are, the more accurate the description of drill bit damage is.

[0039] S3. A damage calculation model of PDC drill bit is established based on fuzzy pattern recognition method.

[0040] Further, it specifically includes:

[0041] S31, fuzzy variable matrix construction: The variables with fluctuation range greater than 20% selected in step S2 are used as characteristic variables, and according to the characteristic variables (x1 x2...x i ...x m ) T Combine feature variable data rows into a fuzzy variable matrix

[0042] S32. Use matrix standardization method to establish samples: Due to different dimensions, it is necessary to perform maximum standardization on each element in the fuzzy variable matrix to establish samples, that is,

[0043] Among them, M j Indicates the maximum value of the j-th column data, M j =max(x 1j ,x 2j ,…,x mj ); x′ ij represents the data in row i and column j after standardization, x mn represents the nth data of the mth variable; the standardized result is as follows Figure 3 shown.

[0044] S33. Establish a fuzzy set of drill bit damage degree: Assume the damage matrix Each set of characteristic variables constitutes a set y j is the domain of the problem, is a fuzzy set on the domain, is the degree to which the jth group of data belongs to damage. Considering that the selected characteristic variables have different influences on the damage of PDC drill bits, a parameter α is set. i The weight coefficient representing the influence of different parameters on the degree of drill bit damage;

[0045] Weight coefficient α i The value of depends on the degree of fluctuation of the variable data with the depth of the well. The greater the fluctuation, the greater the weight coefficient.

[0046] In this embodiment, α1=α2=α3=α6=1 and α4=α5=0.5 are set.

[0047] S34, using the pattern recognition method to classify the samples into the fuzzy set of drill bit damage degree calculation, according to the parameter settings in S31 and S32, the damage calculation model of the PDC drill bit is obtained, and the formula is expressed as:

[0048] S4. Overall damage assessment of PDC drill bits.

[0049] Further, according to the damage calculation model of the PDC drill bit in step S34, the damage results of the drill bits at different well depths are calculated, and the damage results and damage change diagrams are shown in FIG. Figure 4 The total damage of the PDC drill bit is accumulated by combining the damage results of drill bits at different well depths. A comprehensive analysis of all damages can be performed to obtain a reasonable drill bit working time.

[0050] The present invention provides an advanced PDC drill bit damage assessment method for oil and gas well engineering, which will play an important role in improving drilling efficiency and reducing costs.

[0051] In the embodiment provided by the embodiment of the present invention, it should be understood that each box in the flow chart or block diagram can represent a module, a program segment or a part of code, and the module, a program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0052] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0053] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention is essentially or partly contributed to the prior art or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, an electronic device, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk. It should be noted that, in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements inherent to such a process, method, article or device. Without more constraints, an element defined by the phrase "comprising a..." does not exclude the existence of other identical elements in the process, method, article or apparatus comprising the element.

[0054] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0055] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0056] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0057] The "first\second" mentioned in the embodiments is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0058] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics, characterized in that: The steps include: S1. Clean up the logging while drilling data and remove the data that does not meet the predetermined standards or is identified as an outlier; S2. Select variables with significant volatility as characteristic variables for drill bit damage prediction; S3, establishing a damage calculation model of the PDC drill bit according to the fuzzy pattern recognition method; S4. Overall damage assessment of PDC drill bit.

2. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 1 is characterized in that: In step S1, the logging data while drilling include gamma spectrum, drilling pressure, rotation speed, drilling time and the content of main elements in the cuttings; the data that does not meet the predetermined standard or is identified as an abnormal value refers to: the data obtained by logging under the working conditions of tripping, circulation, reaming and electrical logging.

3. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 2 is characterized in that: The main element components include Mg, Al, Si, P, S, Cl, K and Ca.

4. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 1 is characterized in that: In step S2, the following steps are specifically performed: first, the average values ​​of the gamma spectrum, drilling pressure, rotation speed, drilling time and the content of the main elements in the cuttings are obtained. The average value formula is expressed as: in, represents the average value of each variable in the logging data while drilling, n represents the total number of data points of each variable, j represents the jth data point in the data of each variable, x ij Indicates the value of the jth data point in the i-th variable data; The data of the variable fluctuates within 20% of the mean value. The variables are considered to have no damaging effect on the drill bit and will not be The interval variables are used as characteristic variables for drill bit damage prediction.

5. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 1 is characterized in that: In step S3, it specifically includes: S31, fuzzy variable matrix construction: according to the characteristic variables (x1 x2...x i ...x m ) T Combine feature variable data rows into a fuzzy variable matrix S32. Use matrix standardization method to establish samples: Perform maximum value standardization on each element in the fuzzy variable matrix to establish samples, that is, Among them, M j Indicates the maximum value of the j-th column data, M j =max(x 1j ,x 2j ,…,x mj );x' ij represents the data in row i and column j after standardization, x mn Represents the nth data of the mth variable; S33. Establish a fuzzy set of drill bit damage degree: Assume the damage matrix The set yj formed by each set of characteristic variables is the domain of the problem. is a fuzzy set on the domain, is the degree to which the jth group of data belongs to damage. Considering that the selected characteristic variables have different influences on the damage of PDC drill bits, a parameter α is set. i The weight coefficient representing the influence of different parameters on the degree of drill bit damage; S34. Using the pattern recognition method, the samples are classified into the fuzzy set of drill bit damage degree calculation, and the damage calculation model of the PDC drill bit is obtained. The formula is expressed as follows:

6. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 5 is characterized by: In step S32, the weight coefficient α i The value of depends on the degree of fluctuation of the variable data with the depth of the well. The greater the fluctuation, the greater the weight coefficient.

7. The PDC drill bit damage assessment method based on logging while drilling data and fuzzy mathematics according to claim 1 is characterized in that: In step S4, the damage results of the drill bits at different well depths are calculated according to the damage calculation model of the PDC drill bit in step S34, and the total damage of the PDC drill bit is accumulated by combining the damage results of the drill bits at different well depths.

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