System and method for gas chromatography and contamination detection

Abstract

Systems and methods for automated gas chromatography and contamination detection. The method includes receiving a chromatogram of a gas sample released from a subterranean formation during a drilling process; identifying candidate peaks in the chromatogram within a specified range of a calibrated elution time of a target gas; determining a respective candidate elution error for each candidate peak; generating a respective array of expected elution times of additional gases in the gas sample based on each candidate elution error; determining a respective average elution error for each candidate peak based on the corresponding array of expected elution times and additional peaks in the chromatogram; and determining that a candidate peak with a smallest average elution error corresponds to the target gas.

Description

Technical Field

[0001] This disclosure relates to mud logging, and more specifically, to systems and methods for automated gas chromatography and contamination detection. Background Technology

[0002] In oil and gas exploration, mud logging refers to the process of generating data associated with the wellbore drilled into the subsurface formation. Mud logging may include, for example, analyzing and / or characterizing drill bit cuttings (e.g., rock fragments) and gases released from the subsurface formation during the drilling process. Regarding operator safety at the drilling site, it is important to understand the amount and / or type of gases released during drilling, as specific concentrations of these gases may be toxic to respiration and / or may cause blowouts. Furthermore, understanding the type and / or amount of gases released during drilling provides insight into the production potential of the subsurface formation beneath the drilling site. In this regard, accuracy in identifying and quantifying gases released during drilling is invaluable.

[0003] Tools such as gas chromatographs and / or mass spectrometers are typically used to identify and / or quantify different types of gases released from underground formations during drilling. In gas chromatography, during operation, a sample of the gases released during drilling is injected into the inlet of the gas chromatograph. The sample is then heated, causing different compounds (e.g., gas types) within the gas sample to elute at different times. The corresponding elution times of the different compounds in the gas sample are then detected by a detector, which generates a signal used to generate and output a chromatogram.

[0004] A chromatogram is a visual representation of different compounds in a gas sample as a series of peaks on a two-dimensional graph, where each peak in the chromatogram corresponds to a different compound present in the gas sample. The height of the peak (e.g., amplitude) indicates the relative abundance of a particular compound in the gas sample, and the position of the peak on the x-axis (e.g., elution time) indicates the time it takes for a particular compound in the gas sample to travel through the chromatographic column and reach the detector.

[0005] In a conventional method of labeling peaks in a chromatogram using corresponding gases, the highest peak in the chromatogram is labeled as C1 gas (e.g., methane) by default. However, when used to analyze chromatograms of gas samples released from underground formations during drilling, several factors adversely affect the ability of this conventional method to accurately detect and label peaks in the chromatogram. For example, peaks in the chromatogram may shift laterally along the x-axis due to one or more of the following: changes in temperature and / or pressure of the gas sample during drilling; the absence of the gas of interest in the gas sample at the time of chromatogram generation (e.g., due to degassing processes prior to injection into the gas chromatograph); and / or contamination present in the gas sample. In this respect, by using the conventional method of labeling the highest peak in the chromatogram as C1 gas by default, C1 gas and other gases in the gas sample (e.g., C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, nC7, etc.) are often incorrectly labeled in the chromatogram. It is worth noting that incorrect labeling of peaks in chromatograms with incorrect gases leads to inaccuracies in the identification and / or quantification of gases released from underground formations during drilling.

[0006] As illustrated above, there is a need in the art for more effective techniques for gas chromatography and contamination detection. Summary of the Invention

[0007] In one aspect, a method for automated gas chromatography is provided. The method includes: receiving a chromatogram of a gas sample released from an underground formation during a drilling process; identifying a first candidate peak and a second candidate peak in the chromatogram within a specified range of calibrated elution times for a target gas; determining a first candidate elution error based on a first elution time of the first candidate peak in the chromatogram and the calibrated elution time of the target gas; generating a first array including multiple expected elution times of additional gases in the gas sample based on the first candidate elution error and a first plurality of calibrated elution times; and determining, based on the first array and one or more additional peaks detected in the chromatogram, a... The first average elution error of the first candidate peak; the second candidate elution error determined based on the second elution time of the second candidate peak in the chromatogram and the calibrated elution time of the target gas; the second array of multiple expected elution times including additional gases in the gas sample generated based on the second candidate elution error and a second plurality of calibrated elution times; the second average elution error of the second candidate peak determined based on the second array and one or more additional peaks detected in the chromatogram; and the first candidate peak corresponding to the target gas determined in response to determining that the first average elution error is less than the second average elution error.

[0008] In another independent aspect, a system for drilling in subsurface formations is provided. The system includes: a drill string suspended at its upper end by a kelly and a traveling block; a drill bit attached to the lower end of the drill string and adapted to rotate during drilling; a pump adapted to pump drilling fluid through the drill string; a gas trap adapted to extract a gas sample from drilling fluid returned to the surface above the subsurface formation, the gas sample being released from the subsurface formation during drilling; a gas chromatograph adapted to generate a chromatogram of the gas sample; and a computing device including one or more processors. The computing device is adapted to: receive the chromatogram of the gas sample; identify a first candidate peak and a second candidate peak in the chromatogram of the gas sample within a specified range of a calibration elution time for a target gas; determine a first candidate elution error based on a first elution time of the first candidate peak in the chromatogram and the calibration elution time of the target gas; generate a first array including multiple expected elution times of additional gases in the gas sample based on the first candidate elution error and a first plurality of calibration elution times; and, based on the first array and one or more additional peaks detected in the chromatogram, [further details needed]. The process involves: determining a first average elution error for the first candidate peak; determining a second candidate elution error based on a second elution time of the second candidate peak in the chromatogram and a calibrated elution time of the target gas; generating a second array of multiple expected elution times for additional gases in the gas sample based on the second candidate elution error and a plurality of calibrated elution times; determining a second average elution error for the second candidate peak based on the second array and one or more additional peaks detected in the chromatogram; and determining that the first candidate peak corresponds to the target gas when the first average elution error is less than the second average elution error.

[0009] In another independent aspect, a mud logging unit includes a display device and a processor coupled to the display device. The processor is adapted to: receive a chromatogram of a gas sample released from a subsurface formation during drilling; identify a first candidate peak and a second candidate peak in the chromatogram within a specified range of a calibrated elution time for a target gas; determine a first candidate elution error based on a first elution time of the first candidate peak in the chromatogram and the calibrated elution time of the target gas; generate a first array including multiple expected elution times of additional gases in the gas sample based on the first candidate elution error and a first plurality of calibrated elution times; and determine the first candidate elution error based on the first array and one or more additional peaks detected in the chromatogram. The first average elution error of the peak; determining a second candidate elution error based on a second elution time of the second candidate peak in the chromatogram and a calibrated elution time of the target gas; generating a second array of multiple expected elution times including additional gases in the gas sample based on the second candidate elution error and a second plurality of calibrated elution times; determining a second average elution error of the second candidate peak based on the second array and one or more additional peaks detected in the chromatogram; determining that the first candidate peak corresponds to the target gas when the first average elution error is less than the second average elution error; and displaying the chromatogram on the display device.

[0010] Other aspects will become apparent by considering the detailed description and accompanying figures.

[0011] The disclosed technique has at least one technical advantage over conventional methods in that it can accurately detect the peak of a target gas (e.g., C1 gas) within a chromatogram, regardless of the presence or absence of noise affecting the clarity of the chromatogram. At least another technical advantage of the disclosed technique over conventional methods is that it allows for the detection of contaminants in gas samples released during drilling based on the chromatogram of the gas sample. Attached Figure Description

[0012] Figure 1 Example drilling systems are illustrated according to various implementation schemes.

[0013] Figure 2 Examples are given based on various implementation schemes. Figure 1 A close-up view of the lower end of the drill bit and drill string included in the drilling system.

[0014] Figure 3 Examples are given based on the combination of various implementation schemes. Figure 1 A block diagram of the mud logging unit implemented by the drilling system.

[0015] Figure 4 It is based on a combination of various implementation plans. Figure 3A block diagram of the computing device implemented by the mud logging unit.

[0016] Figure 5A and Figure 5B Example chromatographic calibration data are shown according to various implementation schemes.

[0017] Figure 6 It is a flowchart of the method steps for automated gas chromatography according to various implementation schemes.

[0018] Figure 7 Example chromatograms of gas samples released from underground formations during the drilling process are shown according to various implementation schemes.

[0019] Figure 8 Examples are given based on various implementation schemes. Figure 7 The example window in the chromatogram is within the range of the calibrated elution time for C1 gas.

[0020] Figure 9A and Figure 9B Examples are provided for listing various implementation schemes. Figure 7 Example table of expected logging elution times for each additional gas in the chromatogram.

[0021] Figure 10A and Figure 10B Example tables are provided showing the differences between the expected logging elution time and the elution time of the matching peak, based on various implementation schemes.

[0022] Figure 11 Example parameter functions for peaks fitted to chromatograms according to various implementation schemes are shown.

[0023] Figure 12 Examples are given based on various implementation schemes. Figure 11 The parameter function and Figure 11 A comparison between the sums of peaks included in the chromatogram. Detailed Implementation

[0024] Before explaining any implementation scheme in detail, it should be understood that the application of the implementation scheme is not limited to the details of the configuration and arrangement of the components set forth in the following description or illustrated in the accompanying drawings. The implementation scheme can be practiced or performed in various ways. Furthermore, it should be understood that the wording and terminology used herein are for descriptive purposes and should not be considered restrictive. The use of “comprising,” “including,” or “having,” and variations thereof is intended to cover the items subsequently listed and their equivalents, as well as any additional items. Unless otherwise specified or limited, the terms “installation,” “connection,” “support,” and “linkage,” and variations thereof, are used extensively and cover both direct and indirect installation, connection, support, and linking.

[0025] Furthermore, it should be understood that implementations may include hardware, software, and electronic components or modules, which, for the sake of discussion, may be illustrated and described as if most components were implemented solely in hardware. However, those skilled in the art, based on reading this detailed description, will recognize that in at least one implementation, the electronic aspects may be implemented in software (e.g., stored on a non-transitory computer-readable medium) executable by one or more electronic processors (such as microprocessors and / or application-specific integrated circuits (“ASICs”)). Therefore, it should be noted that implementations may be implemented using multiple hardware and software-based devices and multiple different structural components. For example, “server,” “computing device,” “controller,” “processor,” etc., described in the specification may include one or more electronic processors, one or more computer-readable medium modules, one or more input / output interfaces, and various connections of connecting components (e.g., system buses).

[0026] Relative terms used in conjunction with quantities or conditions (such as, for example, "about," "approximately," "substantially," etc.) will be understood by a person skilled in the art to include the stated value and have a meaning indicated by the context (e.g., the term includes at least the degree of error associated with measurement accuracy, the tolerance associated with a particular value [e.g., manufacturing, assembly, use, etc.]). Such terms should also be considered to disclose a range defined by the absolute values ​​of the two endpoints. For example, expressing "about 2 to about 4" also discloses the range "2 to 4." Relative terms may refer to a positive or negative percentage of the indicated value (e.g., 1%, 5%, 10% or more).

[0027] This document describes how functionality performed by one component can be performed by multiple components in a distributed manner. Similarly, functionality performed by multiple components can be combined and performed by a single component. Likewise, a component described as performing a particular function can also perform additional functions not described herein. For example, an apparatus or structure "configured" in a particular way is configured at least in that way, but may also be configured in ways not explicitly listed.

[0028] Figure 1 An example drilling system 100 according to various embodiments is illustrated. The drilling system 100 (which may be referred to below as a "drilling rig") is used for, for example, drilling. As shown, the drilling rig 100 includes a drill string 102 suspended at its upper end by a crisscross drill pipe and a traveling block 104, and terminated at its lower end by a drill bit 106. A rotary table 108 supported on a drill press base plate 110 is adapted to rotate the drill string 102 and the drill bit 106, thereby drilling a wellbore 112 into a subsurface formation 114. In some examples, a portion of the wellbore 112 is covered by a casing 116.

[0029] The drilling rig 100 also includes a mud pump 118 adapted to pump drilling fluid, or "mud," 120 to the upper end of the drill string 102 via a mud line 122. From there, the mud 120 is pumped downwards through the drill string 102 and exits through an opening in the drill bit 106. The mud 120 exiting the drill string 102 through the opening in the drill bit 106 is forced back to the surface via an annulus formed between the wellbore 112 and the outer diameter of the drill string 102. Figure 1 In the illustrative examples, the mud 120 returned to the surface is indicated by an upward-facing arrow. Once on the surface, the mud 120 flows through the bell-shaped section 126 into the return line 124. In some examples, the drilling rig 100 includes a blowout preventer 128 positioned near the bell-shaped section 126. The blowout preventer 128 is adapted to prevent blowouts during drilling operations.

[0030] During drilling operations, drill cuttings are formed as the drill bit 106 rotates and crushes the rock within the underground formation 114. These drill cuttings are returned to the surface along with mud 120, which flows upward through the annulus formed between the wellbore 112 and the outer diameter of the drill string 102. To remove drill cuttings from the mud 120 so that it can be reused for injection during drilling operations, a shale vibrating screen 130 is provided along the return line 124. For example, the shale vibrating screen 130 includes a vibrating screen pool 132 adapted to remove drill cuttings from the mud 120. The mud 120 then flows from the vibrating screen pool 132 into a mud pool 134, from which a mud pump 118 can draw mud 120 to pump it to the upper end of the drill string 102 via the mud line 122.

[0031] like Figure 1 As further shown, the shale vibrating screen 130 includes and / or is coupled to a gas trap 136. During drilling operations, gas is released from the subsurface formation 114 and returned to the surface in the mud 120. For example, similar to drill cuttings formed during drilling, the gas released during drilling flows upward through the annulus formed between the wellbore 112 and the outer diameter of the drill string 102. As will be described in more detail herein, the gas trap 136 is adapted to extract these gases from the mud 120. The extracted gas is then delivered via a gas line 138 to a mud logging unit 140 for analysis.

[0032] Figure 2 A close-up view of the lower end of the drill bit 106 and drill string 102 included in a drilling rig 100, according to various embodiments, is shown. Figure 2 As shown, during drilling operations, drill bit cuttings 200 generated by drill bit 106 flow upward toward the surface within mud 120. For example, mud 120 and the drill bit cuttings 200 contained therein flow upward through the annulus formed between the wall of wellbore 112 and the outer diameter of drill string 102.

[0033] like Figure 2 As further shown, the lower end of drill string 102 includes drill string assembly 202. Drill string assembly 202 may be, for example, a bottom hole assembly (BHA). In some examples, drill string assembly 202 is equipped with telemetry device 204. Telemetry device 204 may include, for example, one or more of the following: a rotatable drive shaft; a turbine impeller mechanically coupled to the drive shaft such that mud 120 can rotate the turbine impeller; a modulator rotor mechanically coupled to the drive shaft such that rotation of the turbine impeller causes rotation of the modulator rotor; a modulator stator mounted adjacent to or near the modulator rotor such that rotation of the modulator rotor relative to the modulator stator forms pressure pulses in mud 120; and a controllable brake for selectively braking the rotation of the modulator rotor to modulate the pressure pulses. In some examples, an alternator may be coupled to the aforementioned drive shaft. This alternator includes at least one stator winding electrically coupled to control circuitry to selectively short-circuit the at least one stator winding, thereby electromagnetically braking the alternator and thus selectively braking the rotation of the modulator rotor to modulate pressure pulses in the mud 120. In some examples, the surface equipment 142, included in and / or coupled to the mud logging unit 140, includes circuitry adapted to sense pressure pulses generated by the telemetry device 204 and transmit the sensed pressure pulses to the mud logging unit 140.

[0034] like Figure 2 As further illustrated in the example, drill string assembly 202 may include a logging-while-drilling (LWD) module 206, a measurement-while-drilling (MWD) module 208, and a rotary steered drilling system (RSS) and / or a motor 210. The drill bit 106, LWD module 206, MWD module 208, and / or RSS 210 may be referred to as downhole tools of drill string 102.

[0035] In some examples, the LWD module 206 is housed in a suitable type of drill collar and may contain one or more logging tools. In some examples, the drill string assembly 202 may include more than one LWD 206. In some examples, the LWD module 254 includes a seismic measuring device. The LWD module 206 may be adapted to measure or record one or more properties of a well drilled in the subsurface formation 114. For example, the LWD module 206 generates logging data and / or logging profiles during drilling operations. The logging data generated by the LWD module 206 may include, for example, geological data such as gamma-ray logging data, resistivity logging data, density logging data, sonic logging data, and / or other types of logging data. The LWD module 206 may then transmit the generated logging data and / or other information associated with the subsurface formation 114 to the surface equipment 142 and / or the mud logging unit 140.

[0036] In some examples, the MWD module 208 is housed in a suitable type of drill collar and may include one or more means for measuring the characteristics of the drill string 102 and / or the drill bit 106. In some examples, the MWD module 208 includes means for generating power to supply power to various components of the drill string 102. In some examples, the MWD module 208 includes one or more measuring means adapted to generate logging data associated with the drill string 102 and / or the drill bit 106. For example, the MWD module 208 includes one or more of the following: a pressure on drill bit (PBD) measuring means, a rotation measuring means, a torque measuring means, a vibration measuring means, an impact measuring means, a stick-slip measuring means, a direction measuring means, and an inclination measuring means. The logging data generated by one or more measuring means included in the MWD module 208 may be transmitted by the MWD module 208 and / or the LWD module 206 to the surface equipment 142 and / or the mud logging unit 140.

[0037] RSS 210 includes equipment for directional drilling. Directional drilling involves drilling into the subsurface formation 114 to form an skewed borehole, such that the borehole trajectory is not vertical. Instead, the trajectory deviates from vertical along one or more sections of the borehole. For example, consider a target located at a certain lateral distance from a surface position 100 at the drilling site. In this example, the drilling could begin with a vertical section and then deviate from vertical, such that the borehole is aimed at the target and eventually reaches it. In this respect, directional drilling can be achieved when the target is inaccessible from a vertical position on the surface above the subsurface formation 114, when there is material in the subsurface formation 114 that may hinder drilling or otherwise harm it (e.g., consider salt domes), when the formation extends laterally (e.g., consider a relatively thin but laterally extending reservoir), when multiple boreholes are to be drilled from a single surface borehole, when a decompression well is required, and / or for some other reason.

[0038] Figure 3Examples are given based on the combination of various implementation schemes. Figure 1 A block diagram of the mud logging unit 140 implemented by the drilling rig 100. Figure 3 In one of the exemplary examples, the mud logging unit 140 includes a computing device 300 coupled to a mass spectrometer 302 and a gas chromatograph 304. In some examples, the computing device 300 is connected to the mass spectrometer 302 and / or the gas chromatograph 304 via one or more wired connections. In other examples, the computing device 300 is connected to the mass spectrometer 302 and / or the gas chromatograph 304 via one or more wireless (e.g., wireless network) connections.

[0039] During operation, gas particles or gas samples 306, released from the underground formation 114 during drilling and extracted from the mud 120 by the gas trap 136, are transported to the mud logging unit 140 via the gas line 138. For example... Figure 3 As illustrated in the example, gas sample 306 flows through gas line 138 to mass spectrometer 302. In some examples, mass spectrometer 302 is adapted to measure the mass of molecules included in gas sample 306. In some examples, mass spectrometer 302 is adapted to identify and / or quantify chemicals and / or compounds included in gas sample 306. In some examples, mass spectrometer 302 outputs or transmits one or more measurements associated with gas sample 306 to computing device 300. In some examples, mud logging unit 140 does not include mass spectrometer 302.

[0040] like Figure 3 As further illustrated in the example, gas sample 306 flows through gas line 138 to gas chromatograph 304. For example, gas sample 306 may be injected into the inlet of gas chromatograph 304, which is adapted to heat gas sample 306 such that the different gases and / or compounds contained in gas sample 306 (e.g., C1, C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, nC7, etc.) are eluted at different times. Gas chromatograph 304 then detects (e.g., via a detector) and generates chromatograms indicating the corresponding abundance and elution time of the different gases and / or compounds in the sample. As will be described in more detail herein, in some examples, gas chromatograph 304 transmits the generated chromatograms to computing device 300 for further analysis. In other examples, gas chromatograph 304 is adapted to perform the chromatographic analysis described herein with respect to computing device 300.

[0041] Figure 4 It is based on a combination of various implementation plans. Figure 3A block diagram of a computing device 300 implemented in the mud logging unit 140. The computing device 300 can be implemented as, for example, a smartphone, tablet, laptop, desktop computer, server, and / or any other suitable computing device. Those skilled in the art will understand that... Figure 4 The computing device 300 shown is only a non-limiting example architecture that can be used to implement the computing device 300 included in the mud logging unit 140. Furthermore, other suitable computing devices not described herein can be used to implement the computing device 300. In some examples, the computing device 300 is located in the field at the drilling rig 100. In other examples, the computing device 300 is located off-site at a remote location.

[0042] like Figure 4 As shown, computing device 300 may include, but is not limited to, processor 402, graphics subsystem 404, I / O device interface 406, network interface 408, interconnect 410, memory subsystem 412, and system disk 414. The interconnect or bus 410 may include one or more wires, cables, traces, contacts, analog components, digital components, wireless connectivity components, and / or other suitable means for interconnecting the hardware components of computing device 300.

[0043] In some implementations, processor 402 (e.g., CPU or similar processor) is adapted to retrieve and execute programming instructions stored in memory subsystem 412. Similarly, processor 402 is adapted to store and retrieve application data (e.g., software libraries) residing in memory subsystem 412 and / or system disk 414. Interconnect 410 is adapted to facilitate the transfer of data (such as programming instructions and application data) between processor 402, graphics subsystem 404, I / O device interface 406, network interface 408, memory subsystem 412, and system disk 414.

[0044] In some embodiments, the graphics subsystem 404 is adapted to generate frames of image and / or video data and transmit these frames to the display device 416. In some embodiments, the graphics subsystem 404 may be integrated with the processor 402 into an integrated circuit. The display device 416 may include any technically feasible means for generating images for display. For example, the display device 416 may be manufactured using liquid crystal display (LCD) technology, cathode ray technology, and light-emitting diode (LED) display technology. The display device 416 may include, for example, one or more monitors.

[0045] Input / output (I / O) device interface 406 is adapted to receive input data from user I / O device 418 and transmit the input data to processor 402 via interconnect 410. For example, user I / O device 418 may include one or more buttons, a touchscreen, a keyboard, a mouse, or other pointing devices. I / O device interface 406 also includes an audio output unit adapted to generate an electrical audio output signal. User I / O device 418 may include one or more speakers adapted to generate an acoustic output in response to the electrical audio output signal. In an alternative embodiment, display device 416 may include speakers.

[0046] In some examples, the I / O device interface 406 may connect to one or more modules of the surface equipment 142, one or more modules of the drill string assembly 202 (e.g., telemetry device 204, LWD module 206, MWD module 208, and / or RSS 210), mass spectrometer 302, and / or gas chromatograph 304. In some examples, the computing device 300 may receive logging data and / or other measurement results generated by the LWD module 206 and / or MWD module 208 via the I / O device interface 406. In some examples, the computing device 300 may transmit commands for controlling drilling to the telemetry device 204 and / or RSS 210 via the I / O device interface 406. In some examples, the computing device 300 may receive one or more measurement results from the mass spectrometer 302 via the I / O device interface 406. In some examples, the computing device 300 may receive one or more measurement results and / or chromatograms from the gas chromatograph 304 via the I / O device interface 406.

[0047] Network interface 408 is adapted to transmit and receive data packets via one or more network connections 420. In some examples, network interface 408 is adapted to receive logging data and / or other measurement data from one or more of LWD module 206, MWD module 208, and / or surface equipment 142 via one or more network connections 420. In some examples, network interface 408 is adapted to transmit one or more signals for controlling drilling to telemetry device 204 and / or RSS 210 via one or more network connections 420. In some examples, network interface 408 is adapted to receive one or more measurement results from mass spectrometer 302 via one or more network connections 406. In some examples, network interface 408 is adapted to receive one or more measurement results and / or chromatograms from gas chromatograph 304 via one or more network connections 406. In some examples, network interface 408 is adapted to communicate with one or more external computing devices via one or more network connections 420.

[0048] One or more network connections 420 may be established, for example, via one or more of a wide area network (WAN) (e.g., the Internet, TCP / IP-based networks, cellular networks, such as Global System for Mobile Communications [GSM] networks, General Packet Radio Service [GPRS] networks, Code Division Multiple Access [CDMA] networks, Evolved Data Optimized [EV-DO] networks, Enhanced Data Rate for GSM Evolution [EDGE] networks, 3GSM networks, 4GSM networks, Digital Enhanced Cordless Telecommunications [DECT] networks, Digital AMPS [IS-136 / TDMA] networks, or Integrated Digital Enhanced Network [iDEN] networks, etc.). In other examples, one or more network connections 420 may be established using a local area network (LAN), neighborhood area network (NAN), home area network (HAN), and / or personal area network (PAN) employing any of a variety of communication protocols, such as Wi-Fi, Bluetooth, ZigBee, etc. In some examples, a wide area network (WAN), local area network (LAN), neighborhood area network (NAN), home area network (HAN), or personal area network (PAN) is used to establish one or more network connections 420. In some examples, a wired connection is used to establish one or more network connections 420.

[0049] System disk 414 (such as a hard disk drive or flash memory storage drive) is adapted to store non-volatile data. For example, system disk 414 stores one or more files, applications, and / or programs to be implemented by processor 402. In some examples, system disk 414 stores logging data and / or other measurement data 422. For example, system disk 414 stores one or more gamma-ray depth logging curves, one or more formation strength depth logging curves, and / or other types of logging curves, including logging data and / or other measurement data generated by LWD module 206, MWD module 208, and / or one or more other sensors. In some examples, system disk 414 may also store one or more chromatograms 424 and / or chromatographic calibration data 426 generated by gas chromatograph 304.

[0050] As will be described in more detail herein, chromatographic calibration data 426 may include chromatograms and associated data of gas samples extracted from mud 120 by gas trap 136 during the calibration phase. During the calibration phase, the temperature and / or pressure conditions associated with the gas samples released from subsurface formation 114 during drilling are stable. Furthermore, during the calibration phase, the gas samples released from subsurface formation 114 during drilling are virtually free of contaminants. In this respect, peaks are readily detectable in the chromatograms generated from the gas samples collected during the calibration phase. In some examples, chromatographic calibration data 426 is provided by a third-party contractor. In other examples, the operator of drilling rig 100 uses mud logging unit 140 to generate chromatographic calibration data 426.

[0051] Figure 5A and Figure 5B Example chromatographic calibration data according to various implementation schemes are illustrated. For example, Figure 5A Example calibration chromatogram 500 is shown and Figure 5B A calibration data table 502 corresponding to calibration chromatogram 500 is illustrated. Chromatogram 500 is generated, for example, by gas chromatograph 304 during a calibration phase, during which the temperature and / or pressure conditions associated with the gas sample released from the underground formation 114 during drilling are stable and there is no contamination in the gas sample.

[0052] like Figure 5A As shown, the calibration chromatogram 500 has the highest amplitude (e.g., 2.45e). -07 Peaks corresponding to the shortest elution time (e.g., 21.150 seconds) are labeled as C1 gas (e.g., methane). The remaining peaks detected in calibration chromatogram 500 are labeled sequentially according to their elution time. For example, the peak corresponding to the second shortest elution time (e.g., 21.610 seconds) is labeled as C2 gas (e.g., ethane), the peak corresponding to the third shortest elution time (e.g., 22.450 seconds) is labeled as C3 gas (e.g., propane), the peak corresponding to the fourth shortest elution time (e.g., 23.560 seconds) is labeled as iC4 gas (e.g., isobutane), the peak corresponding to the fifth shortest elution time (e.g., 24.410 seconds) is labeled as nC4 gas (e.g., n-butane), the peak corresponding to the sixth shortest elution time (e.g., 27.230 seconds) is labeled as iC5 gas (e.g., isopentane), and the peak corresponding to the seventh shortest elution time (e.g., 28.510 seconds) is labeled as nC5 gas (e.g., n-pentane).

[0053] like Figure 5B As shown, calibration data table 502 includes additional data associated with each peak detected in calibration chromatogram 500. For example, calibration data table 502 includes the corresponding amplitude, elution time, cross-union ratio (iOu) value, injection rate, elution time difference, and peak area for each peak in calibration chromatogram 500. It is noteworthy that in calibration data table 502, the elution time difference is always zero. However, as will be described in more detail herein, the elution time difference is a metric that can be used to compare the peaks in chromatogram 424 generated by gas chromatograph 304 with chromatographic calibration data 426.

[0054] In some examples, the memory subsystem 412 includes programming instructions and application data, which includes an operating system 428, a user interface 430, a drilling control application 432, and a gas chromatography and contamination detection (GCCD) application 434. The operating system 428 performs system management functions, such as managing hardware devices including a graphics subsystem 404, an I / O device interface 406, a network interface 408, and a system disk 414. The operating system 428 also provides process and memory management models for the user interface 430, the drilling control application 432, and / or the GCCD application 434. The user interface 430 provides mechanisms (such as windows and object metaphors) for user interaction with the computing device 300. Those skilled in the art will recognize various operating systems and user interfaces well-known in the art and suitable for incorporation into the computing device 300.

[0055] When executed by processor 402, drilling control application 432 can be used to control one or more parameters of drilling operations. For example, drilling control application 432 can be used to control telemetry device 204 and / or RSS 210 to perform drilling operations as described herein. In some examples, drilling control application 432 uses logging data and / or other measurement data generated by LWD module 206 and / or MWD module 208 to control drilling operations. In some examples, drilling control application 432 uses chromatograms and / or chromatographic data generated by gas chromatograph 304 and / or GCCD application 434 to control drilling operations. In some examples, drilling control application 432 provides an interface through which an operator at drilling rig 100 can interact with drilling control application 432 to control drilling operations. For example, drilling control application 432 enables an operator at drilling rig 100 to input one or more commands for controlling drilling operations via I / O device 418.

[0056] As described herein, gas chromatograph 304 is adapted to generate chromatograms of gas samples released from subsurface formation 114 during drilling. When executed by processor 402, GCCD application 434 uses one or more techniques to analyze chromatogram 424 generated by gas chromatograph 304. In some examples, analyzing chromatogram 424 includes identifying and / or quantifying the gases released during drilling based on peaks included in chromatogram 424. For example, GCCD application 434 may detect peaks in the chromatogram and correlate them with corresponding gas types (e.g., C1, C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, nC7, etc.). In some examples, analyzing chromatograms includes detecting contamination in gas samples released from subsurface formation 114, partially based on peaks in chromatogram 424. For example, when peaks in chromatogram 424 deviate from chromatographic calibration data 426 by an amount exceeding a threshold, GCCD application 434 may determine the presence of contamination in the gas sample.

[0057] As described herein, using conventional methods for analyzing chromatograms, the first peak in a chromatogram is typically labeled as gas C1 by default. However, the first peak appearing in a chromatogram often does not correspond to gas C1, and therefore, using conventional methods, peaks in a chromatogram are frequently incorrectly labeled as the wrong gas type. For example, the first peak in a chromatogram might correspond to noise attributable to contamination in a gas sample released during drilling, varying pressure conditions, and / or varying pressure and temperature conditions. In such an example, using conventional methods, the peak corresponding to the noise is labeled as C1, and subsequent peaks may also be incorrectly labeled as the wrong gas (e.g., C2, C3, C4, etc.).

[0058] In this regard, when analyzing peaks in chromatogram 424, the GCCD application 434 does not by default label the first peak in chromatogram 424 as C1. Instead, as will be described in more detail herein, the GCCD application 434 identifies C1 in chromatogram 424 by detecting one or more candidate peaks within a range r of elution times corresponding to the calibrated elution time of C1. For each candidate peak identified within the range r of the calibrated elution time of C1, the GCCD application 434 determines a candidate elution error for calculating the corresponding expected elution time for each of the other gases expected in the chromatogram. The GCCD application 434 then associates C1 with a candidate peak that produces the minimum combined error between the expected elution time and the calibrated elution time described in the chromatographic calibration data 426.

[0059] Figure 6 This is a flowchart of method steps for automated gas chromatography according to various implementation schemes. Although these method steps are combined... Figure 1 To Figure 5 and Figures 7 to 12 The system described herein is for informational purposes only; however, those skilled in the art will understand that any system configured to perform these method steps in any order is within the scope of this disclosure.

[0060] As shown in the figure, method 600 begins at step 602, where a chromatogram of a gas sample released during drilling is received. For example, GCCD application 434 receives a chromatogram of a gas sample released from subsurface formation 114 during drilling.

[0061] In some examples, the chromatogram received at step 602 is generated by a gas chromatograph 304. In this example, a gas trap 136 extracts a gas sample from mud 120 and delivers the extracted gas sample to a mud logging unit 140 via a gas line 138. The gas sample is then injected into the inlet of a gas chromatograph 304, which is adapted to heat the gas sample such that different gases and / or compounds contained in the gas sample (e.g., C1, C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, nC7, etc.) are eluted at different times. The gas chromatograph 304 detects (e.g., via a detector) and generates a chromatogram indicating the corresponding abundance and elution time of the different gases and / or compounds in the sample. A GCCD application 434 then receives the chromatogram from the gas chromatograph 304.

[0062] Figure 7 Example chromatograms 700 of gas samples released from the subsurface formation during the drilling process are illustrated according to various embodiments. Chromatogram 700 is generated, for example, by a gas chromatograph 304 based on the gas sample released from the subsurface formation 114 during the drilling process. In some examples, chromatogram 700 is received by a GCCD application 434 at step 602 of method 600.

[0063] At step 604, one or more candidate peaks for the target gas are identified in the chromatogram received at step 602. For example, GCCD application 434 identifies one or more peaks in chromatogram 700 as candidates for C1 gas.

[0064] In some examples, identifying one or more candidate peaks for C1 gas involves analyzing the chromatogram within a window *r* of the calibration elution time *t* associated with C1 gas. The calibration elution time associated with C1 gas (which may be denoted as "t" below) C1 "" refers to the elution time of C1 determined and stored as chromatographic calibration data 426 during the calibration phase. In such examples, the elution time at t is detected by the GCCD application 434. C1 Any peak within the range r can be considered a candidate peak for C1 gas. In some examples, the value of r is a predetermined value. In some examples, the value of r is a configurable value that can be adjusted by the operator of the mud logging unit 140. In some examples, the value of r is determined in part based on the number of peaks detected in the chromatogram received at step 602 and / or the chromatogram 426.

[0065] about Figure 7 Example of GCCD application 434 analysis of chromatogram 700 in t C1 A window 702 within the range r is used to identify one or more candidate peaks for C1 gas. Figure 7 In the example of the instantiation, tC1 It has a value of 21.15 seconds. However, in other examples, t C1 They have different values. Furthermore, in Figure 1 In the example provided, the value of r is one second. Therefore, in Figure 7 In the example shown, window 702 is centered at 21.15 seconds and spans from 20.15 seconds to 22.15 seconds.

[0066] Figure 8 Examples are given based on various implementation schemes. Figure 7 An example window in the chromatogram, within the range of calibrated elution times for C1 gas. For example, Figure 8 An example is shown for chromatogram 700 at t C1 A window 702 is defined within a range r (e.g., 1 second) of 21.15 seconds. GCCD application 434 analyzes window 702 to identify one or more candidate peaks of C1 within window 702. Figure 8 In the illustrative example, the GCCD application 434 detects a first candidate peak 802 and a second candidate peak 804 within window 702. In this respect, the GCCD application 434 identifies the first candidate peak 802 and the second candidate peak 804 as candidate peaks of the Cl gas at step 604 of method 600.

[0067] exist Figure 8 In the illustrative example, the elution time for the first candidate peak 802 is 21.09 seconds, and the elution time for the second candidate peak 804 is 21.53 seconds. The elution times for the first candidate peak 802 and the second candidate peak 804 may be referred to hereinafter as the expected logging elution times because chromatogram 700 was generated during the logging (e.g., mud logging) phase, not the calibration phase. Although in Figure 8 The example provided identifies only two candidate peaks, but those skilled in the art will understand that in other examples, fewer or more candidate peaks may be identified.

[0068] In some examples, at step 604, GCCD is applied 434 in t C1 No candidate peaks for C1 gas were detected within the range r. In such examples, GCCD application 434 can detect peaks within t. C1 Artificial candidate peaks for C1 gas are created within the range r. Creating artificial candidate peaks for C1 gas includes selecting the artificial candidate peak within t. C1 The expected logging washout time within the range r. In some examples, GCCD is applied randomly at t 434. C1 One or more time points within the range r are selected to create artificial candidate peaks for C1 gas. In some examples, GCCD applies 434 selection. One or more of these can be used as the expected logging elution time for one or more artificial candidate peaks of C1 gas. In some examples, even if the GCCD application 434 identifies one or more candidate peaks of C1 gas at step 604, the GCCD application 434 also creates one or more artificial candidate peaks of C1 gas. For example, if candidate peaks of C1 gas smaller than a threshold amount (e.g., 2, 3, 4, etc.) are identified at step 602, the GCCD application 434 may generate one or more artificial candidate peaks of C1 gas.

[0069] At step 606 of method 600, a candidate elution error is determined for each identified candidate peak of the target gas. In some examples, GCCD application 434 determines the candidate elution error of the candidate peak of C1 gas as the expected logging elution time of the candidate peak of C1 gas versus t. C1 The ratio between them. For example, Equation 1 below represents the candidate elution error C used to determine the candidate peaks for C1 gas. EE The equation.

[0070] Equation 1:

[0071] exist Figure 7 and Figure 8 In the illustrative example, GCCD application 434 uses Equation 1 to determine that the candidate elution error for the first candidate peak 802 is approximately 0.997. Furthermore, GCCD application 434 uses Equation 1 to determine that the candidate elution error for the second candidate peak 804 is approximately 1.018.

[0072] At step 608 of method 600, for each corresponding candidate peak of the target gas, an array of expected logging elution times for additional gases (e.g., C2, C3, iC4, nC4, etc.) in the chromatogram is generated. That is, a first array of expected logging elution times corresponding to the first candidate peak of C1 gas is generated, a second array of expected logging elution times corresponding to the second candidate peak of C1 gas is generated, and so on. In some examples, the array of expected logging elution times corresponding to the corresponding candidate peak of C1 gas is determined in part based on: (i) the candidate elution error C of the corresponding candidate peak of C1 gas. EE (i) The calibration elution times of the additional gases included in the chromatograph. The calibration times of the additional gases in the chromatogram can be obtained from the chromatographic calibration data 426.

[0073] about Figure 7 and Figure 8 As an example, GCCD application 434 can generate a first array of expected logging elution times corresponding to the first candidate peak 802 based on: (i) the candidate elution error C of the first candidate peak 802. EEand (ii) the calibrated elution time of the additional gas in chromatogram 700. Similarly, GCCD application 434 can generate a second array of expected logging elution times corresponding to the second candidate peak 804 based on: (i) the candidate elution error C of the second candidate peak 804. EE (ii) Calibration elution time of additional gases in chromatogram 700.

[0074] In some examples, GCCD application 434 multiplies the calibration elution time of the corresponding additional gas by the candidate elution error C of the candidate peak of the C1 gas. EE This is used to determine the expected logging elution time for the corresponding additional gases. For example, Equation 2 below represents the method used to determine the expected logging elution time for the additional gases in the chromatogram. The formula, where C EE It is determined using Equation 1 above, and This is the corresponding calibrated elution time for the additional gas. As described in this article, The value can be obtained from chromatographic calibration data 426.

[0075] Equation 2:

[0076] For example, GCCD application 434 can multiply each calibration elution time of the additional gas by the candidate elution error C of the first candidate peak 802. EE (e.g., 0.997) to determine the corresponding value of the expected logging elution time included in the first array corresponding to the first candidate peak 802. Figure 9A Table 900A illustrates the expected logging elution times for each additional gas in chromatogram 700 according to various implementation schemes. For example, the candidate elution error C of the first candidate peak 802 is calculated using Equation 2 by GCCD application 434. EE (e.g., 0.997) and the corresponding calibrated elution time are used to calculate the expected logging elution time for each of the additional gases (e.g., C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, and nC7) listed in Table 900A. For example, using Equation 2, the C... EE The expected logging elution time for C2 gas listed in Table 900A is determined using the value of C2 (e.g., 0.997) and the calibrated elution time for C2 gas (e.g., 21.61 seconds). Similarly, the C2 gas elution time is determined using Equation 2 for the first candidate peak 802. EE The value (e.g., 0.997) and the calibrated elution time of C3 gas (e.g., 22.45 seconds) are used to determine the expected logging elution time (e.g., 22.39 seconds) of C3 gas listed in Table 900A.

[0077] Similarly, GCCD application 434 can multiply each calibration elution time of the additional gas by the candidate elution error C of the second candidate peak 804. EE (e.g., 1.018) to determine the corresponding value of the expected logging elution time included in the second array corresponding to the second candidate peak 804. Figure 9B Table 900B illustrates the expected logging elution times for each additional gas in chromatogram 700 according to various implementation schemes. For example, the candidate elution error C of the second candidate peak 804 is calculated using Equation 2 by GCCD application 434. EE (e.g., 1.018) and the corresponding calibrated elution times are used to calculate the expected logging elution time for each of the additional gases (e.g., C2, C3, iC4, nC4, iC5, nC5, nC6, benzene, and nC7) listed in Table 900B. For example, using Equation 2, the C... EE The expected logging elution time (e.g., 22 seconds) for C2 gas, as listed in Table 900B, is determined using the value of C2 (e.g., 1.018) and the calibrated elution time of C2 gas (e.g., 21.61 seconds). Alternatively, Equation 2 is used to determine the C2 gas value for the second candidate peak 804. EE The value (e.g., 1.018) and the calibrated elution time of C3 gas (e.g., 22.45 seconds) are used to determine the expected logging elution time (e.g., 22.85 seconds) of C3 gas listed in Table 900B.

[0078] At step 610 of method 600, the corresponding average elution error is determined for each candidate peak of the target gas. In some examples, the average elution error of a specific candidate peak of C1 gas can be determined in part based on an array of expected logging elution times corresponding to that peak. In some examples, GCCD application 434 determines the average elution error for each candidate peak of the C1 gas identified at step 604. .

[0079] In some examples, the average elution error in determining candidate peaks for C1 gas is... This includes: (i) matching each expected logging elution time corresponding to a candidate peak in the array with the corresponding peak detected in the chromatogram received at step 602; (ii) determining the difference between each expected logging elution time in the array and the elution time of the corresponding peak that matches the expected logging elution time; and (iii) averaging the determined differences between the expected logging elution times in the array and the corresponding elution times of the matched peaks.

[0080] When the average elution error of the first candidate peak 802 is determined In this case, the GCCD application 434 can match the expected logging elution times included in the first array with the peaks detected in chromatogram 700 in a left-to-right order. For example, when moving from left to right from the first candidate peak 802, the GCCD application 434 can match the expected logging elution time of C2 gas with the next peak detected in chromatogram 700 after the first candidate peak 802. (Reference) Figure 7 Since the first candidate peak 802 was selected as the peak with an elution time of 21.09 seconds in chromatogram 700, GCCD application 434 matched the expected logging elution time of C2 gas with the peak with an elution time of 21.53 seconds detected in chromatogram 700 (e.g., the next peak to the right of the first candidate peak 802).

[0081] Similarly, GCCD application 434 can match the expected logging elution time of C3 gas with the next peak detected in chromatogram 700 after the peak with an elution time of 21.53 seconds. In this respect, GCCD application 434 matches the expected logging elution time of C3 gas with the peak detected in chromatogram 700 with an elution time of 22.34 seconds. GCCD application 434 repeats the matching process from left to right until each expected logging elution time in the first array matches the corresponding peak, or until no more peaks are detected in chromatogram 700.

[0082] After matching the expected logging elution times in the first array with the corresponding peaks detected in chromatogram 700, GCCD application 434 determines the absolute difference between each expected logging elution time in the first array and the corresponding elution time of the matching peak. For example, GCCD application 434 determines the absolute difference between the expected logging elution time of C2 gas (e.g., 21.55 seconds) and the elution time of the peak matching the expected logging elution time of C2 gas (e.g., 21.53 seconds). In this example, the absolute difference is 0.02. As another example, GCCD application 434 determines the absolute difference between the expected logging elution time of C3 gas (e.g., 22.39 seconds) and the elution time of the peak matching the expected logging elution time of C3 gas (e.g., 22.34 seconds). In this example, the absolute difference is 0.05. Figure 10A Table 1000A illustrates the difference between the expected logging elution time included in the first array and the elution time of the matching peak.

[0083] After determining the absolute difference between the expected elution time of each expected logging peak included in the first array and the corresponding elution time of the matching peak, GCCD application 434 averages the elution error of the first candidate peak 802. The average of the determined absolute differences is used. For example, GCCD application 434 uses Equation 3 below to determine the average elution error of the first candidate peak 802 based on the absolute differences listed in Table 1000A. In this example, GCCD application 434 determines the average elution error of the first candidate peak 802. It is 0.134.

[0084] Equation 3:

[0085] When the average elution error of the second candidate peak 804 is determined At this time, the GCCD application 434 can match the expected logging elution times included in the second array with the peaks detected in chromatogram 700 in a left-to-right order. For example, when moving from left to right from the second candidate peak 804, the GCCD application 434 can match the expected logging elution time of C2 gas with the next peak detected in chromatogram 700 after the second candidate peak 804. (Reference) Figure 7 Since the second candidate peak 804 was selected as the peak with an elution time of 21.53 seconds in chromatogram 700, GCCD application 434 matched the expected logging elution time of C2 gas with the peak with an elution time of 22.34 seconds detected in chromatogram 700 (e.g., the next peak to the right of the second candidate peak 804).

[0086] Similarly, GCCD application 434 can match the expected logging elution time of C3 gas with the next peak detected in chromatogram 700 after the peak with an elution time of 22.34 seconds. In this respect, GCCD application 434 matches the expected logging elution time of C3 gas with the peak detected in chromatogram 700 with an elution time of 22.85 seconds. GCCD application 434 repeats the matching process from left to right until each expected logging elution time in the first array matches the corresponding peak, or until no more peaks are detected in chromatogram 700.

[0087] After matching the expected logging elution times in the second array with the corresponding peaks detected in chromatogram 700, GCCD application 434 determines the absolute difference between each expected logging elution time in the first array and the corresponding elution time of the peak matching the expected logging elution time. For example, GCCD application 434 determines the absolute difference between the expected logging elution time for C2 gas (e.g., 22.00 seconds) and the elution time of the peak matching the expected logging elution time for C2 gas (e.g., 22.34 seconds). In this example, the absolute difference is 0.34. As another example, GCCD application 434 determines the absolute difference between the expected logging elution time for C3 gas (e.g., 22.85 seconds) and the elution time of the peak matching the expected logging elution time for C3 gas (e.g., 22.85 seconds). In this example, the absolute difference is 0.00. Figure 10B Table 1000B illustrates the difference between the expected logging elution time and the elution time of the matching peak included in the second array.

[0088] After determining the absolute difference between the expected elution time of each expected logging peak included in the second array and the corresponding elution time of the matching peak, GCCD applies 434 to the average elution error of the second candidate peak 804. The average of the determined absolute differences is used. For example, GCCD application 434 uses Equation 3 above to determine the average elution error of the second candidate peak 804 based on the absolute differences listed in Table 1000B. In this example, GCCD application 434 determines the average elution error of the second candidate peak 804. It is 0.503.

[0089] At step 612 of method 600, the target gas is eluted with the minimum average error. The candidate peaks are identified as the actual peaks in the chromatogram corresponding to the target gas. For example, GCCD application 434 determines that the first candidate peak 802 is the peak in chromatogram 700 corresponding to gas C1. In some examples, step 612 includes labeling the selected candidate peak of gas C1 in chromatogram 700 with a C1 label.

[0090] In some examples, method 600 also includes modifying drilling parameters (e.g., rate of penetration, rotational speed, or pressure on the drill bit) during drilling, in part based on the determined actual peak value of the C1 gas. In some examples, method 600 also includes stopping drilling, in part based on the determined actual peak value of the C1 gas. In some examples, method 600 also includes rendering and displaying a chromatogram on display device 416, wherein the peaks detected in the chromatogram are labeled with the corresponding gas names determined by method 600.

[0091] As described herein, in some examples, GCCD application 434 can analyze the shape of peaks in chromatogram 434 to determine whether contamination exists in a gas sample. For example, when a peak in chromatogram 424 deviates from the chromatographic calibration data 426 by more than a threshold amount, GCCD application 434 can determine that contamination exists in the gas sample.

[0092] In one example, assuming the peak shapes of the target gas (e.g., C1, C2, C3, etc.) in chromatogram 434 remain relatively stable during the transition from the calibration phase to the logging phase, GCCD application 434 can use a peak fitting parameter function to reconstruct or model each peak in chromatogram 434. This peak fitting parameter function may include parameters related to peak width, peak height, peak amplitude, peak time shift, and / or other parameters of the peaks in the chromatogram. In some examples, one or more parameters of the peak fitting parameter function (such as amplitude and time shift) are dynamic, while one or more other parameters remain constant.

[0093] Figure 11 Example parameter functions for peaks fitted to chromatograms according to various implementation schemes are illustrated. For example, Figure 11 The example illustrates the parametric function 1100 fitted to the first peak 1102 and the second peak 1104 in chromatogram 1106. In some examples, GCCD application 434 generates the parametric function 1100 and fits it to the first peak 1102 and the second peak 1104. For example... Figure 11 As shown, the parameter function 1100 is not a perfect fit because there is some overlap and / or crossing between the parameter function 1100 and the first peak 1102 and the second peak 1104.

[0094] Figure 12 Examples are given based on various implementation schemes. Figure 11 The parameter function and Figure 11 A comparison between the sums of peaks included in the chromatogram. For example, Figure 12 A graph 1200 is illustrated, showing a comparison between the parametric function 1100 in chromatogram 1106 and the sum 1202 of the first peak 1102 and the second peak 1104. In some examples, GCCD application 434 may generate graph 1200 and display it on display device 416.

[0095] In some examples, the GCCD application 434 can analyze the parametric function 1100 relative to one or more of the first peak 1102 and the second peak 1104 to determine the presence and / or accumulation of contaminants within the gas sample. For example, the GCCD application 434 can perform cross-union ratio (iOu) analysis by comparing the area of ​​intersection between the parametric function 1100 and the sum 1202 of the first peak 1102 and the second peak 1104 with the area of ​​union of the parametric function 1100 and the sum 1202 of the first peak 1102 and the second peak 1104.

[0096] In some examples, GCCD application 434 uses Equation 4 below to determine the area of ​​intersection between the parametric function 1100 and either the first peak 1102 or the second peak 1104.

[0097] Equation 4:

[0098] Furthermore, in some examples, GCCD application 434 uses Equation 5 below to determine the area of ​​the union between the parametric function 1100 and either the first peak 1102 or the second peak 1104.

[0099] Equation 5:

[0100] Using the results of Equations 4 and 5, GCCD application 434 can then use Equation 6 below to determine the iOu of the corresponding peak in the first peak 1102 or the second peak 1104 with respect to the parameter function 1100.

[0101] Equation 6:

[0102] about Figure 11 and Figure 12 Using Equations 4-6, GCCD application 434 determines that the first peak 1102 has an iOu of 0.94 and the second peak 1104 has an iOu of 0.85. Generally, the further the iOu value of a peak is from the value 1.0, the greater the likelihood that the gas corresponding to that peak is contaminated. For example, GCCD application 434 determines that the gas corresponding to the second peak 1104 is likely contaminated because its iOu value differs from 1.0 by 0.15. Similarly, GCCD application 434 determines that the gas corresponding to the first peak 1102 is unlikely to be contaminated because its iOu value differs from 1.0 by only 0.06.

[0103] In some examples, the GCCD application 434 compares the iOu value of a given peak with a threshold to determine whether the gas corresponding to that given peak is contaminated. For example, when the iOu value of the peak corresponding to the gas is less than a threshold (e.g., 0.9, 0.85, 0.8, etc.), the GCCD application 434 determines that the gas is contaminated. In some examples, the GCCD application 434 compares the iOu value of a given peak with multiple thresholds to measure the severity and / or amount of contamination present in the gas corresponding to the given peak. In some examples, in response to determining that the gas is contaminated, the GCCD application 434 generates an alert. Generating an alert may include displaying the alert on a display device 416, transmitting a message containing the alert to one or more external computing devices, issuing an alarm, and / or some other action.

[0104] In some examples, in response to the GCCD application 434 determining that the gas is contaminated, the drilling control application 432 controls one or more components of the drilling rig 100 to stop the drilling process. In some examples, in response to the GCCD application 434 determining that the gas is contaminated, the drilling control application 432 modifies drilling parameters (e.g., mechanical rate of penetration, rotational speed, or pressure on the drill bit) during drilling.

[0105] Any and all combinations of any elements of the claims and / or any elements described in this application fall within the intended scope of this disclosure and protection in any way. Descriptions of various embodiments have been presented for illustrative purposes but are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

[0106] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or apparatuses, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media will include the following: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium can be any tangible medium that may contain or store programs used by or in conjunction with instruction execution systems, devices, or apparatuses.

[0107] The foregoing description, with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure, has described various aspects of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine.

[0108] These instructions, when executed by a processor of a computer or other programmable data processing device, enable the implementation of the functions / actions specified in one or more boxes of the flowchart and / or block diagram. Such processors may be, but are not limited to, general-purpose processors, special-purpose processors, dedicated processors, or field-programmable gate arrays.

[0109] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible specific implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code comprising one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative embodiments, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two blocks shown successively may actually be executed substantially in parallel, or these blocks may sometimes be executed in reverse order, depending on the functionality involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a system based on dedicated hardware or a combination of dedicated hardware and computer instructions that performs the specified function or action.

[0110] While the foregoing describes an embodiment of this disclosure, other and further embodiments of this disclosure may be designed without departing from the basic scope of this disclosure, and the scope of this disclosure is defined by the appended claims.

Claims

1. A method for automated gas chromatography, the method comprising: Chromatogram of the receiving gas sample (306) (424, 700); Within a specified range of calibrated elution times for the target gas, identify the first candidate peak (802) and the second candidate peak (804) in the chromatogram (424, 700). A first average elution error of the first candidate peak (802) is determined in part based on the first elution time of the first candidate peak (802) and the calibrated elution time of the target gas; The second average elution error of the second candidate peak (804) is determined in part based on the second elution time of the second candidate peak (804) and the calibrated elution time of the target gas; as well as In response to determining that the first average elution error is less than the second average elution error, the first candidate peak (802) is determined to correspond to the target gas.

2. The method according to claim 1, further comprising: The gas sample (306) is extracted from the drilling fluid (120) that returns to the underground formation (114) above the ground during the drilling process by the gas trap (136). The gas sample (306) is injected into the inlet of the gas chromatograph (304); and The chromatogram (424, 700) is generated by the gas chromatograph (304).

3. The method according to claim 1 or claim 2, wherein determining the first average elution error comprises: The first candidate elution error is determined in part based on the first elution time and the calibration elution time; Based in part on the first candidate elution error and the first plurality of calibrated elution times, a first array is generated including a first plurality of expected elution times for additional gases in the gas sample (306); as well as The first average elution error is determined in part based on the first array and one or more additional peaks detected in the chromatogram (424, 700).

4. The method of claim 3, wherein generating the first array comprises multiplying each of the first plurality of calibration elution times by the first candidate elution error.

5. The method according to claim 3 or claim 4, wherein determining the first average elution error further comprises: Detect one or more additional peaks in the chromatogram (424, 700); Match each expected elution time included in the first array with a corresponding additional peak included in the one or more additional peaks; Determine the corresponding time difference between each expected elution time included in the first array and the elution time of the corresponding additional peak matching the expected elution time; and Determine the average of the sums of each corresponding time difference.

6. The method according to any one of claims 1 to 5, wherein determining the second average elution error comprises: The second candidate elution error is determined in part based on the second elution time and the calibrated elution time; A second array is generated, comprising a second plurality of expected elution times for additional gases in the gas sample (306), based in part on the second candidate elution error and a second plurality of calibrated elution times; as well as The second average elution error is determined in part based on the second array and one or more additional peaks detected in the chromatogram (424, 700).

7. The method of claim 6, wherein generating the second array comprises multiplying each of the second plurality of calibration elution times by the second candidate elution error.

8. The method of claim 6 or claim 7, wherein determining the second average elution error further comprises: Detect one or more additional peaks in the chromatogram (424, 700); Each expected elution time included in the second array is matched with a corresponding additional peak included in the one or more additional peaks; Determine the corresponding time difference between each expected elution time included in the second array and the elution time of the corresponding additional peak matching the expected elution time; and Determine the average of the sums of each corresponding time difference.

9. The method according to any one of claims 1 to 8, further comprising: Generate a parametric function that fits the first candidate peak (802) in the chromatogram (424, 700); Determine the area of ​​intersection between the parameter function and the first candidate peak (802); Determine the area of ​​the union between the parameter function and the first candidate peak (802); Determine the ratio between the intersection area and the union area; In response to determining that the ratio is less than a threshold, an alert is generated indicating the presence of contamination in the target gas.

10. The method of claim 9, further comprising stopping the drilling process in response to determining that the ratio is less than the threshold.

11. The method according to any one of claims 1 to 10, the method further comprising generating an artificial candidate peak having an artificial elution time within the specified range of the calibrated elution time of the target gas.

12. The method according to claim 11, further comprising: The artificial candidate elution error is determined based on the artificial elution time of the artificial candidate peak and the calibration elution time of the target gas. Based on the artificial candidate elution error and the third plurality of calibrated elution times, an array of multiple expected elution times including additional gases in the gas sample is generated; as well as Based on the array and one or more additional peaks detected in the chromatogram, a third average elution error of the artificial candidate peak is determined.

13. The method according to any one of claims 1 to 12, wherein the target gas is methane.

14. A system (100) for drilling in an underground formation (114), the system comprising: A drill string (102) is suspended at its upper end by a square drill rod and a traveling block (104); A drill bit (106) is attached to the lower end of the drill string (102) and is adapted to rotate during drilling. Pump (118), the pump being adapted to pump drilling fluid (120) through the drill string (102). A gas trap (136) adapted to extract a gas sample (306) from drilling fluid (120) returned to the surface above the subsurface formation (114), the gas sample (306) being released from the subsurface formation (114) during drilling; Gas chromatograph (304), the gas chromatograph is adapted to generate chromatograms (424, 700) of the gas sample (306). and A computing device (300) comprising one or more processors (402), the computing device (300) being adapted to perform the method according to any one of claims 1 to 13.

15. A mud logging unit (140), the mud logging unit comprising: Display device (416); and A processor (402) coupled to the display device (416) is adapted to perform the method according to any one of claims 1 to 13.

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