Continuous monitoring system for detecting, locating and quantifying dissipative emissions

Abstract

A method includes determining a location at which one or more devices are placed at a field. Each device includes a first sensor configured to measure a concentration of greenhouse gas (GHG). The method further includes measuring a concentration of GHG with a first sensor. The method further includes quantifying a rate of emission of GHG based at least in part on the measured GHG concentration. The method also includes determining a location of a GHG emission source at a site where the GHG measured by the first sensor is being emitted. The location is determined based at least in part on the measured concentration, the quantified rate, or both. The method also includes identifying a GHG emission source at the determined location by comparing the determined location to a list of the plurality of GHG emission sources at the site and its location.

Description

[0001] Related Applications

[0002] This application claims priority to and the benefit of U.S. Provisional Application Serial No. 63 / 367,361, filed on June 30, 2022, the entire contents of which are incorporated herein by reference. Background Art

[0003] Methane is an anthropogenic greenhouse gas (GHG) in the atmosphere. Methane is 80 times more potent than carbon dioxide over a 20-year period and 30 times more potent than carbon dioxide over a century. Fugitive emissions from oil and gas account for approximately 4% of total GHG emissions. Fugitive emissions are unintentional releases (e.g., leaks) that are traditionally detected when maintenance operations are performed on a facility or when regulators require the implementation of a periodic leak detection and repair (LDAR) program. LDAR programs have limited effectiveness in areas where facilities are sparsely populated due to the speed at which operators can survey facilities and the low frequency of inspections, which are typically annual or semi-annual. This means that leaks may go undetected for weeks, months, or longer. Tighter environmental targets imposed by stakeholders and financial institutions, stricter operating permit rules, and evolving regulations are driving oil and gas operators to find effective solutions that can help them detect and reduce fugitive emissions with a quick turnaround. Summary of the invention

[0004] A method is disclosed. The method includes determining a location to place one or more devices at a site. Each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG). The method also includes measuring the concentration of the GHG with the first sensor. The method also includes quantifying a rate of emitting the GHG based at least in part on the measured GHG concentration. The method also includes determining a location of a GHG emission source at the site that is emitting the GHG measured by the first sensor. The location is determined at least in part based on the measured concentration, the quantified rate, or both. The method also includes identifying a GHG emission source at the determined location by comparing the determined location with a list of multiple GHG emission sources at the site and its location. The method also includes displaying the site and the identified GHG emission source at the determined location.

[0005] A computing system is also disclosed. The computing system includes one or more processors and a memory system. The memory system includes one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations. The operations include determining a location to place one or more devices at a site. Each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG). The operations also include measuring the concentration of the GHG with the first sensor. The operations also include quantifying a rate of emitting GHG based at least in part on the measured GHG concentration. The operations also include determining a location of a GHG emission source at the site that is emitting the GHG measured by the first sensor. The location is determined at least in part based on the measured concentration, the quantified rate, or both. The operations also include identifying a GHG emission source at the determined location by comparing the determined location with a list of multiple GHG emission sources at the site and its location. The operations also include displaying the site and the identified GHG emission source at the determined location.

[0006] A non-transitory computer-readable medium is also disclosed. The medium stores instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations. The operations include determining a location to place one or more devices at a site. Each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG). The operations also include measuring the concentration of the GHG with the first sensor. The operations also include quantifying a rate of emitting the GHG based at least in part on the measured GHG concentration. The operations also include determining a location of a GHG emission source at the site that is emitting the GHG measured by the first sensor. The location is determined at least in part based on the measured concentration, the quantified rate, or both. The operations also include identifying a GHG emission source at the determined location by comparing the determined location with a list of multiple GHG emission sources at the site and its location. The operations also include displaying the site and the identified GHG emission source at the determined location.

[0007] This Summary is provided to introduce a selection of concepts that are further described below in the Detailed Description. This Summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used to help limit the scope of the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teaching and, together with the description, are used to explain the principles of the present teaching. In the drawings:

[0009] Figure 1A , Figure 1B , Figure 1C , Figure 1D , Figure 2 , Figure 3A and Figure 3B A simplified schematic diagram of an oil field and its operations is shown according to one embodiment.

[0010] Figure 4 A schematic plan view of a site having one or more GHG emission sources is shown according to an embodiment.

[0011] Figure 5 A flow chart of a method for monitoring GHG emissions at a site according to an embodiment is shown.

[0012] Figure 6 A computing system for performing at least a portion of the methods disclosed herein is shown according to an embodiment. DETAILED DESCRIPTION

[0013] Reference will now be made in detail to embodiments, examples of which are shown in the accompanying drawings and figures. In the following detailed description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, it is apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other cases, well-known methods, processes, components, circuits and networks are not described in detail to avoid unnecessarily obscuring aspects of the embodiments.

[0014] It will also be understood that although the terms first, second, etc. can be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, without departing from the scope of the present invention, a first object can be referred to as a second object, and similarly, a second object can be referred to as a first object. The first object and the second object are both objects, respectively, but they are not considered to be the same object.

[0015] The terms used in the description of the present invention herein are only used for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the description of the present invention and the appended claims, the singular forms "one", "an" and "the" are intended to also include plural forms, unless the context clearly indicates otherwise. It will also be understood that the term "and / or" as used herein refers to and encompasses any possible combination of one or more of the associated listed items. It will be further understood that when used in this specification, the terms "includes", "including", "comprises" and / or "comprising" specify the existence of stated features, integers, steps, operations, elements and / or components, but do not exclude the existence or addition of one or more other features, integers, steps, operations, elements, components and / or their groups. In addition, as used herein, the term "if" can be interpreted as meaning "when..." or "at..." or "in response to determining" or "in response to detecting", depending on the context.

[0016] Attention is now directed to processes, methods, techniques, and workflows according to some embodiments.Some operations in the processes, methods, techniques, and workflows disclosed herein may be combined and / or the order of some operations may be changed.

[0017] Figures 1A-1D A simplified schematic diagram of an oil field 100 is shown having an underground formation 102 containing a reservoir 104 therein in accordance with implementations of the various processes and techniques described herein. Although embodiments of the present method are described at least in part herein with reference to an oil field, it should be understood that this is merely an illustrative example. Embodiments of the present method may be used in any application where detection of fugitive emissions may be useful.

[0018] Figure 1A A survey operation performed by a survey tool, such as a seismic truck 106a, to measure properties of underground formations is shown. The survey operation is a seismic survey operation for generating acoustic vibrations. Figure 1A In the embodiment of the present invention, one such acoustic vibration, such as acoustic vibration 112 generated by source 110, reflects off a horizon 114 in a formation 116. A set of acoustic vibrations is received by a sensor located on the surface of the earth, such as a seismic receiver 118. The received data 120 is provided as input data to a computer 122.1 of the seismic truck 106a, and in response to the input data, the computer 122.1 generates a seismic data output 124. The seismic data output can be stored, transmitted, or further processed, such as by data reduction, as desired.

[0019] Figure 1BA drilling operation is shown performed by a drilling tool 106b suspended by a drilling rig 128 and advanced into a subterranean formation 102 to form a wellbore 136. A mud pit 130 is used to draw drilling mud into the drilling tool via a flow line 132 for circulating the drilling mud downward through the drilling tool and then upward to the wellbore 136 and back to the surface. The drilling mud is typically filtered and returned to the mud pit. A circulation system may be used to store, control or filter the flowing drilling mud. The drilling tool is advanced into the subterranean formation 102 to reach a reservoir 104. Each well may target one or more reservoirs. The drilling tool is adapted to measure downhole properties using a logging while drilling tool. The logging while drilling tool may also be adapted to collect a core sample 133, as shown.

[0020] The computer facility may be located at various locations around the oilfield 100 (e.g., a surface unit 134) and / or a remote location. The surface unit 134 may be used to communicate with the drilling tool and / or off-site operations, as well as to communicate with other surface or downhole sensors. The surface unit 134 is capable of communicating with the drilling tool to send commands to the drilling tool and receive data from the drilling tool. The surface unit 134 may also collect data generated during the drilling operation and generate data output 135, which may then be stored or transmitted.

[0021] Sensors (S) (such as meters) may be positioned around the oilfield 100 to collect data related to various oilfield operations as previously described. For example, the sensor (S) may include one or more sensors to measure: concentrations of greenhouse gases, solar radiation, humidity, GPS coordinates, and / or temperature. As shown, the sensor (S) is positioned in one or more locations in the drilling tool and / or at the drilling rig 128 to measure drilling parameters such as drilling pressure, drill bit torque, pressure, temperature, flow, composition, rotation speed, and / or other parameters of field operations. The sensor (S) may also be positioned at one or more locations in the circulation system.

[0022] The drilling tool 106b may include a bottom hole assembly (BHA) (not shown) (referenced generally) near the drill bit (e.g., within a few drill collar lengths from the drill bit). The bottom hole assembly includes capabilities for measuring, processing, and storing information, as well as communicating with the surface unit 134. The bottom hole assembly also includes drill collars for performing various other measurement functions.

[0023] The bottom hole assembly may include a communication subassembly that communicates with the surface unit 134. The communication subassembly is adapted to send and receive signals to and from the surface using a communication channel such as mud pulse telemetry, electromagnetic telemetry, or wired drill pipe communication. The communication subassembly may include, for example, a transmitter that generates a signal, such as an acoustic or electromagnetic signal, representing the measured drilling parameter. Those skilled in the art will appreciate that various telemetry systems may be employed, such as wired drill pipe, electromagnetic, or other known telemetry systems.

[0024] Typically, a wellbore is drilled according to a drilling plan established prior to drilling. The drilling plan typically sets forth the equipment, pressures, trajectories, and / or other parameters that define the drilling process for the well site. Drilling operations may then be performed according to the drilling plan. However, as information is collected, drilling operations may need to deviate from the drilling plan. Additionally, subsurface conditions may change while drilling or other operations are being performed. Earth models may also need to be adjusted as new information is collected.

[0025] The data collected by the sensor(s) may be collected by the ground unit 134 and / or other data collection sources for analysis or other processing. The data collected by the sensor(s) may be used alone or in combination with other data. The data may be collected in one or more databases and / or transmitted on-site or off-site. The data may be historical data, real-time data, or a combination thereof. Real-time data may be used in real time or stored for later use. The data may also be combined with historical data or other inputs for further analysis. The data may be stored in separate databases or combined into a single database.

[0026] The surface unit 134 may include a transceiver 137 to allow communication between the surface unit 134 and various parts or other locations of the oil field 100. The surface unit 134 may also be provided with or functionally connected to one or more controllers (not shown) for actuating mechanisms at the oil field 100. The surface unit 134 may then send a command signal to the oil field 100 in response to the received and / or analyzed data. The surface unit 134 may receive the command via the transceiver 137, or may itself execute the command to the controller. A processor may be provided to analyze the data (locally or remotely), make decisions, and / or actuate the controller. In one embodiment, the action performed by the controller may include generating and / or transmitting a signal to a fugitive emission source, an authorized user, or a combination thereof. In another embodiment, the action performed by the controller may include reducing the speed of one or more sources that are generating fugitive emissions, shutting down one or more sources that are generating fugitive emissions, repairing one or more sources that are generating fugitive emissions to reduce emissions, replacing one or more sources that are generating fugitive emissions, or a combination thereof. In this way, the oil field 100 may be selectively adjusted based on the collected data. The technology can be used to optimize (or improve) parts of field operations, such as controlling drilling, drilling pressure, pumping rate, fugitive emissions, or other parameters. These adjustments can be made automatically based on computer protocols, and / or manually by operators. In some cases, well plans can be adjusted to select optimal (or improved) operating conditions, or to avoid problems.

[0027] Figure 1C Shown is the drilling rig 128 hanging and entering Figure 1B The logging cable tool 106c is adapted to be deployed into the wellbore 136 for generating well logging curves, performing downhole tests and / or collecting samples. The cable tool 106c can be used to provide another method and apparatus for performing seismic survey operations. The logging cable tool 106c can, for example, have an explosive, radioactive, electrical or acoustic energy source 144 that sends and / or receives electrical signals to the surrounding underground formation 102 and the fluid therein.

[0028] The cable tool 106c may be operably connected to, for example, Figure 1A The wireline tool 106c may be positioned at various depths in the wellbore 136 to provide survey or other information related to the subsurface formation 102.

[0029] Sensors (S) for measuring concentrations of greenhouse gases, solar radiation, humidity, GPS coordinates, and / or temperature (such as meters, and / or one or more sensors) may be positioned around the oilfield 100 to collect data related to various oilfield operations as previously described. As shown, the sensor S is positioned in the wireline tool 106.b to measure downhole parameters related to, for example, porosity, permeability, fluid composition, and / or other parameters of field operations.

[0030] Figure 1D Production operations are shown being performed by a production tool 106d deployed from a production unit or Christmas tree 129 and into a completed wellbore 136 for extracting fluid from a downhole reservoir to a surface facility 142. Fluid flows from the reservoir 104 through perforations (not shown) in the casing and into the production tool 106d in the wellbore 136 and to the surface facility 142 via a collection network 146.

[0031] Sensors (S) for measuring concentrations of greenhouse gases, solar radiation, humidity, GPS coordinates, and / or temperature (such as meters, and / or one or more sensors) may be positioned around the oilfield 100 to collect data related to various oilfield operations as previously described. As shown, the sensor (S) may be positioned in the production tool 106d or associated equipment (such as the Christmas tree 129, the gathering network 146, the surface facilities 142, and / or the production facilities) to measure fluid parameters, such as fluid composition, flow, pressure, temperature, and / or other parameters of the production operation.

[0032] Production may also include injection wells for enhanced recovery.One or more gathering facilities may be operably connected to one or more of the well sites for selectively collecting downhole fluids from the well sites.

[0033] Although Figure 1B-1D Tools for measuring properties of an oil field are shown, but it should be understood that the tools may be used in conjunction with non-oil field operations, such as gas fields, mines, aquifers, storage formations, or other underground facilities. In addition, although certain data acquisition tools are depicted, it should be understood that various measurement tools capable of sensing parameters of underground formations and / or their geological formations (such as seismic two-way travel time, density, resistivity, production rate, etc.) may be used. Various sensors (S) may be located at various locations in the oil field along the wellbore and / or monitoring tools to collect and / or monitor the desired data. Other data sources may also be provided from off-site locations.

[0034] Figures 1A-1DThe oilfield configuration is intended to provide a brief description of an example of an oilfield that can be used with the oilfield application framework. A portion or all of the oilfield 100 can be on land, on water, and / or offshore. In addition, although a single oilfield measured at a single location is depicted, the oilfield application can be used with any combination of one or more oilfields, one or more processing facilities, and one or more well sites.

[0035] Figure 2 A schematic diagram showing a partial cross-section of an oil field 200 having data collection tools 202a, 202b, 202c, and 202d located at various locations along the oil field 200 for collecting concentrations of greenhouse gases, solar radiation, humidity, GPS coordinates, and / or temperature, and / or other data of a subsurface formation 204 in accordance with implementations of various techniques and technologies described herein. The data collection tools 202a, 202b, 202c, and 202d may be respectively connected to Figures 1A-1D The data acquisition tools 202a, 202b, 202c, 202d may be the same as the data acquisition tools 106a, 106b, 106c, 106d or other data acquisition tools not depicted. As shown, the data acquisition tools 202a, 202b, 202c, 202d generate data plots or measurements 208a, 208b, 208c, 208d, respectively. These data plots are depicted along the oil field 200 to show the data generated by various operations.

[0036] The data plots 208a, 208b, 208c, 208d are examples of static data plots that can be generated by the data acquisition tools 202a, 202b, 202c, 202d, respectively; however, it should be understood that the data plots 208a, 208b, 208c, 208d can also be real-time updated data plots. These measurements can be analyzed to better define the properties of the formation and / or determine the accuracy of the measurements and / or check for errors. The plots of each of the corresponding measurements can be aligned and scaled for comparison and verification of attributes.

[0037] Static data plot 208a is the seismic bi-directional response over a period of time. Static plot 208b is core sample data measured from a core sample of formation 204. The core sample can be used to provide data such as a plot of density, porosity, permeability, or some other physical property of the core sample versus the length of the core. The fluid in the core can be tested for density and viscosity at varying pressures and temperatures. Static data plot 208c is a well log trace, which typically provides resistivity or other measurements of the formation at various depths.

[0038] The production decline curve or graph 208d is a dynamic data plot of fluid flow rate over time. The production decline curve generally provides the production rate as a function of time. As the fluid flows through the wellbore, the fluid properties are measured, such as flow rate, pressure, composition, etc.

[0039] Other data may also be collected, such as concentrations of greenhouse gas data, solar radiation data, humidity data, GPS coordinates, temperature data, historical data, user input, economic information, and / or other measurements and other parameters of interest. As described below, static and dynamic measurements may be analyzed and used to generate a model of the subsurface formation to determine its properties. Similar measurements may also be used to measure changes in aspects of the formation over time.

[0040] The underground structure 204 has a plurality of geological formations 206a, 206b, 206c, 206d. As shown, the structure has several formations or layers, including a shale layer 206a, a carbonate layer 206b, a shale layer 206c, and a sand layer 206d. A fault 207 extends through the shale layer 206a and the carbonate layer 206b. The static data acquisition tool is suitable for taking measurements and detecting characteristics of the formations.

[0041] Although a specific underground formation with a specific geological structure is depicted, it should be understood that oil field 200 can contain a variety of geological structures and / or formations, sometimes with extreme complexity. In some locations, typically below the waterline, fluids may occupy the pore space of the formation. Each of the measurement devices can be used to measure the properties of the formation and / or its geological characteristics. Although each acquisition tool is shown as a specific location in oil field 200, it should be understood that one or more types of measurements can be made at one or more locations or other locations in one or more oil fields for comparison and / or analysis.

[0042] Then, data from various sources (such as Figure 2 Typically, geophysicists use seismic data displayed in static data plot 208a from data acquisition tool 202a to determine the properties of subsurface formations and features. Geologists typically use core data shown in static plot 208b and / or well log data from well log curve 208c to determine various properties of subsurface formations. Production data from curve plot 208d is typically used by reservoir engineers to determine fluid flow reservoir properties. The data analyzed by geologists, geophysicists, and reservoir engineers can be analyzed using modeling techniques.

[0043] Figure 3A An oil field 300 is shown for performing production operations in accordance with implementations of the various techniques and technologies described herein. As shown, the oil field has a plurality of well sites 302 operatively connected to a central processing facility 354. Figure 3AThe oilfield configuration is not intended to limit the scope of the oilfield application system. Part or all of the oilfield may be on land and / or offshore. In addition, although a single oilfield with a single processing facility and multiple well pads is depicted, any combination of one or more oilfields, one or more processing facilities, and one or more well pads may exist.

[0044] Each well site 302 has equipment for forming a wellbore 336 underground. The wellbore extends through an underground formation 306 including a reservoir 304. These reservoirs 304 contain fluids, such as hydrocarbons. The well site extracts fluids from the reservoir and delivers them to a processing facility via a surface network 344. The surface network 344 has pipelines and control mechanisms for controlling the flow of fluids from the well site to the processing facility 354.

[0045] Now turn your attention to Figure 3B , which shows a side view of a marine-based survey 360 of a lower level 362 of the subsurface according to one or more implementations of various techniques described herein. The lower level 362 includes a seafloor surface 364. A seismic source 366 may include a marine source such as a vibrator or an air gun, which may propagate seismic waves 368 (e.g., energy signals) into the earth over an extended period of time or with nearly instantaneous energy provided by a pulsed source. The seismic waves may be propagated by the marine source as a frequency swept signal. For example, a vibrator-type marine source may initially emit seismic waves at a low frequency (e.g., 5 Hz) and increase the seismic waves to a high frequency (e.g., 80-90 Hz) over time.

[0046] Components of seismic waves 368 may be reflected and converted by seafloor surface 364 (i.e., reflectors), and seismic wave reflections 370 may be received by a plurality of seismic receivers 372. Seismic receivers 372 may be disposed on a plurality of streamers (i.e., streamer array 374). Seismic receivers 372 may generate electrical signals representative of received seismic wave reflections 370. The electrical signals may be embedded with information about underlying surface 362 and captured as a record of seismic data.

[0047] In one embodiment, each streamer may include a streamer steering device, such as a pod, deflector, tail buoy, etc., which is not shown in this application. The streamer steering device can be used to control the position of the streamers according to the techniques described herein.

[0048] In one embodiment, seismic wave reflections 370 may travel upward and reach the water / air interface at the water surface 376, and a portion of the reflections 370 may then be reflected downward again (i.e., surface ghost waves 378) and received by a plurality of seismic receivers 372. Surface ghost waves 378 may be referred to as surface multiples. The point at which the wave on the water surface 376 is reflected downward is often referred to as a downward reflection point.

[0049] The electrical signal may be transmitted to the vessel 380 via a transmission cable, wireless communication, or the like. The vessel 380 may then transmit the electrical signal to a data processing center. Alternatively, the vessel 380 may include an onboard computer capable of processing the electrical signal (i.e., seismic data). Those skilled in the art who have benefited from this disclosure will appreciate that this illustration is highly idealized. For example, the survey may be of a stratum deep underground. The stratum may typically include a plurality of reflectors, some of which may include tilt events, and may generate a plurality of reflections (including wave conversions) for reception by the seismic receiver 372. In one embodiment, the seismic data may be processed to generate a seismic image of the lower layer 362.

[0050] The marine seismic acquisition system tows each streamer in the streamer array 374 at the same depth (e.g., 5-10 m). However, the ocean-based survey 360 may tow each streamer in the streamer array 374 at a different depth so that seismic data can be acquired and processed in a manner that avoids the effects of destructive interference caused by sea surface ghost waves. For example, Figure 3B The marine survey 360 shows eight streamers towed at eight different depths by a vessel 380. The depth of each streamer may be controlled and maintained using a pod disposed on each streamer.

[0051] Continuous monitoring system and method for detecting, locating and quantifying fugitive emissions

[0052] A system including one or more sensors may be configured to continuously monitor a remote site (e.g., a well site) or group of sites with the ability to send measurements to a solution hosted in a public or private cloud. Thus, the present disclosure may include cloud-based systems and methods that can continuously monitor a remote facility by: (1) detecting excess atmospheric GHG concentrations from fugitive GHG emissions, (2) quantifying the amount and / or rate of GHG emissions, (3) locating point sources of GHG emissions, (4) identifying possible (e.g., most likely) sources from an inventory list, and / or (5) triggering an alarm when a problem is detected (e.g., GHG concentrations and / or GHG rates exceed a predetermined threshold) so that corrective action can be initiated in a timely manner. As used herein, "excess" refers to a level of a predetermined (e.g., background) concentration that is above a given detection threshold. As used herein, a "possible source object" refers to a possible source of methane emissions (e.g., a generator).

[0053] Figure 4A schematic plan view of a site 400 having one or more GHG emission sources 420A, 420B according to an embodiment is shown. The site 400 may include a perimeter 410. The GHG emission sources 420A, 420B may be located within the perimeter 410. The GHG emission sources 420A, 420B may be or include equipment such as one or more generators, one or more compressors, one or more valves, one or more tanks, one or more pipelines or conduits, one or more wells, one or more vehicles, or a combination thereof.

[0054] One or more devices (four are shown: 430A-430D) may be positioned in and / or around site 400. Devices 430A-430D may each include one or more sensors: 431A-436A, 431B-436B, 431C-436C, 431D-436D. For example, devices 430A-430D may each include a first sensor 431A-431D configured to measure GHG concentration, a second sensor 432A-432D configured to measure wind speed and / or wind direction, a third sensor 433A-433D configured to measure solar radiation, a fourth sensor 434A-434D configured to measure humidity, a fifth sensor 435A-435D configured to measure GPS coordinates, a sixth sensor 436A-436D configured to measure temperature, or a combination thereof.

[0055] GHG Sensor

[0056] The first (e.g., GHG) sensors 431A-431D may be or include ground permanent sensors that are part of an autonomous sensor grid positioned at least partially around the site 400. The GHG sensors 431A-431D may be configured to detect and / or measure fugitive GHG emissions better than conventional discrete measurement methods. The GHG sensors 431A-431D may be placed in and / or around the site 400 based at least in part on the latitude, longitude, and altitude of the site 400, the region of the site 400, the terrain in and around the site 400 (e.g., mountains, rivers, lakes, trees, deserts, etc.), the structures in and around the site 400 (e.g., buildings), the type of GHG emission sources 420A, 420B at the site 400, the location of the GHG emission sources 420A, 420B at the site 400, the current and / or historical meteorological conditions at the site 400, or a combination thereof. A user may provide details of the site 400 or group of sites to be monitored. A placement algorithm may be used to determine the number of GHG sensors 431A-431D to use and where to place them.

[0057] Device Configuration

[0058] To monitor a facility or group, a user with access rights can enter information to connect to the sensor's data stream. The user can provide a list of locations to be monitored, including details such as facility type, equipment, component list, fluid type, managed fluid and / or volume, boundaries, location of equipment, or a combination thereof. The user can also or alternatively provide the location of the field-installed equipment, the type of sensor, and / or a unique identifier. The user can also or alternatively provide an identifier for any routing equipment used to stream information from the field device. The user can associate one or more devices to one or more specific sites.

[0059] Notification Configuration

[0060] In order to notify the user of an event, a list of users responsible for a site or site group may be provided. More specifically, the user may select a site or site group. The user may also add the usernames of persons to be notified when an event has been detected on a site. When fugitive emissions have been detected, localized and / or quantified, the person responsible for the site may be notified.

[0061] Continuous Monitoring

[0062] As described above, field devices 430A-430D can detect and / or measure methane concentration and local meteorological conditions. The collected data can be preprocessed on the edge. The data can also be compressed and streamed to a cloud ingestion endpoint via radio frequency, data network, satellite, etc. Then, a cloud-based system that can be hosted in a private cloud or a public cloud can ingest the data streamed from each sensor. The system can also verify the quality of the received data and route it to the algorithm responsible for the field or region. The algorithm can analyze the data streams from each sensor and search for anomalies in the methane concentration measurements. As used herein, "abnormal" refers to methane concentrations above a predetermined threshold. When excessive methane concentrations are detected, additional sensors that can help identify the source of fugitive emissions can be selected. The data from the selected sensor can be fed into an algorithm responsible for locating and quantifying fugitive emissions. This can be the same algorithm or a different algorithm that searches for anomalies.

[0063] The solutions (e.g., algorithms) provided by the system can be horizontally scaled on cloud infrastructure to handle parallel processing of many sites. Devices can be mapped to different tenants so that data is isolated into separate storage devices, and partitioning of computations can provide secure multi-tenancy.

[0064] The integrity of the measurement data may be checked using checksums and / or data quality checks to determine that the data has not been corrupted during transmission and that the algorithm has not processed corrupted data. The data may be encrypted during transmission and storage to prevent tampering.

[0065] Artificial intelligence techniques may be used to remove data that includes false positives. False positive removal may include using data science methods that combine multimodal data (e.g., sensor, meteorological, and operational data) to classify fugitive and exhaust events. Users may provide feedback based on the outcome of an alert or the lack of an alert, which may or may not be used to improve the accuracy of the data science methods in classifying detected anomalies (e.g., exhaust versus fugitive or false positive).

[0066] Therefore, the systems and methods described herein can use a physics-based model, a data-driven model, or both, which can be fed with historical meteorological data, field attributes, and geographic attributes to determine where to place sensors. A physics-based model, a data-driven model, or both can also be used to detect, quantify, locate, and / or identify emission sources in a stream processing pipeline. The use of data science methods can improve the quality and reliability of detection (e.g., reducing false positives). This integrated workflow for detecting fugitive emissions can improve turnaround time. The model can also improve the accuracy of locating and quantifying fugitive emission sources. Integration with other measurements can provide an overall methane mitigation solution. The improved accuracy and reliability of source identification can reduce field visits and improve elimination plans (e.g., repair / maintenance).

[0067] Figure 5 A flow chart of a method 500 for monitoring emissions at a site 400 is shown according to an embodiment. More specifically, the method 500 can detect, measure, quantify, and / or locate fugitive gas (e.g., GHG) emissions at a wellsite 400. The GHGs can be or include methane, carbon monoxide, carbon dioxide, or a combination thereof. An illustrative sequence of the method 500 is provided below; however, one or more portions of the method 500 can be performed in a different order, combined, split, repeated, or omitted. One or more portions of the method 500 can be performed by a computing system 600 (described below).

[0068] The method 500 may include determining a location to place one or more devices 430A-430D at a site (e.g., a well site) 400, as at 502. As described above, the devices 430A-430D may include GHG sensors 431A-431D configured to detect and / or measure GHG emissions. More specifically, the GHG sensors 431A-431D may be configured to measure atmospheric GHG concentrations. The determination may be based at least in part on the location of the site 400, the terrain in and / or around the site 400, the size of the site 400, the devices at the site 400 (e.g., the number, type, and / or location of GHG emission sources 420A, 420B), current and / or historical meteorological conditions at the site 400, or a combination thereof. The devices 430A-430D may be placed at the determined locations.

[0069] The method 500 may also include detecting and / or measuring GHG concentration at the site 400 using the GHG sensors 431A-431D, as shown at 504. This may include detecting and / or measuring when the atmospheric GHG concentration is greater than or equal to a predetermined threshold. More specifically, this may include detecting and / or measuring when the atmospheric GHG concentration is greater than or equal to the predetermined threshold for greater than or equal to a predetermined amount of time.

[0070] The method 500 may also include quantifying the rate at which GHGs are emitted, as shown at 506. This may include quantifying the GHG emission rate based on measurements from each GHG sensor 431A-431D individually (e.g., four rates may be calculated). In another embodiment, this may include quantifying the GHG emission rate based on combined measurements from the GHG sensors 431A-431D (e.g., one rate may be calculated).

[0071] The method 500 may also include determining the location of the sources 420A, 420B of the GHG emissions, as at 508. This may also include determining the location of two or more sources 420A, 420B. The location may be determined based at least in part on measured GHG concentrations, quantified GHG rates, or both. For example, when the quantified GHG rate at one GHG sensor 431A exceeds a predetermined threshold, the quantified GHG rates from one or more other sensors 431B-431D may be used to determine the location of the sources 420A, 420B (e.g., by triangulating the sources). The location may also or alternatively be determined by an algorithm based at least in part on the known locations of the GHG emission sources 420A, 420B at the site 400, the types of GHG emission sources 420A, 420B at the site 400, the types and / or amounts of fluids pumped, produced, or otherwise transported, the boundaries 410 of the site 400, or a combination thereof.

[0072] The method 500 may also include determining or identifying a source 420A, 420B of the GHG emissions, as shown at 510. The source 420A, 420B may be determined or identified based at least in part on the determined location (from 508) and / or an inventory list of the site. For example, the source 420A, 420B may be determined or identified by comparing the determined location (from 508) to an inventory list including known locations of GHG emission sources 420A, 420B at the site 400, types of GHG emission sources 420A, 420B at the site 400, types and / or amounts of fluids pumped, produced, or otherwise transported, boundaries 410 of the site 420A, 420B, or a combination thereof. A particular source 420A, 420B may be identified from the list based at least in part on the comparison.

[0073] The method 500 may also include displaying the site 400, as at 512. More specifically, this may include generating and displaying an image of the site 400 including the perimeter 410, measured concentrations at each GHG sensor 431A-431D, quantified rates (e.g., at each GHG sensor 431A-431D), determined locations of the sources 420A, 420B, identification of the sources 420A, 420B, or a combination thereof.

[0074] The method 500 may also include generating and / or sending a notification (e.g., an alarm), as at 514. The notification may be sent to an authorized user. The notification may include the measured concentration, the quantified rate, the location of the source 420A, 420B, the specific source determined (e.g., source 420A but not source 420B), or a combination thereof. In one embodiment, when the measured concentration and / or the quantified rate indicates a false positive (e.g., which may occur during a known exhaust event), the notification may not be generated or transmitted.

[0075] The method 500 may also include performing a wellsite action, such as at 516. The wellsite action may be performed based at least in part on and / or at least in part in response to the measured concentration, the quantified rate, the location of the source 420A, 420B, the determined source 420A, 420B, the display, the notification, or a combination thereof. In one embodiment, the wellsite action may be or include generating and / or transmitting a signal to the source 420A, 420B, the device 430A-430D, the authorized user, or a combination thereof. In another embodiment, the wellsite action may be or include reducing the speed of the source 420A, 420B that is generating fugitive emissions, shutting down the source 420A, 420B that is generating fugitive emissions, repairing the source 420A, 420B that is generating fugitive emissions to reduce emissions, replacing the source 420A, 420B that is generating fugitive emissions, or a combination thereof.

[0076] In some embodiments, any of the methods of the present disclosure may be performed by a computing system. Figure 6An example of such a computing system 600 is shown in accordance with some embodiments. The computing system 600 may include a computer or computer system 601A, which may be a separate computer system 601A or an arrangement of distributed computer systems. The computer system 601A includes one or more analysis modules 602, which are configured to perform various tasks in accordance with some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the analysis modules 602 execute independently or in coordination with one or more processors 604, which are connected to one or more storage media 606. Processor 604 (or multiple processors) is also connected to a network interface 607 to allow computer system 601A to communicate with one or more additional computer systems and / or computing systems (such as 601B, 601C, and / or 601D) via a data network 609 (note that computer systems 601B, 601C, and / or 601D may or may not share the same architecture as computer system 601A and may be located in different physical locations, for example, computer systems 601A and 601B may be located in a processing facility while communicating with one or more computer systems (such as 601C and / or 601D) located in one or more data centers and / or in different countries on different continents).

[0077] A processor may include a microprocessor, a microcontroller, a processor module or subsystem, a programmable integrated circuit, a programmable gate array, or another control or computing device.

[0078] Storage medium 606 may be implemented as one or more computer-readable or machine-readable storage media. Figure 6 In the example embodiment of , storage medium 606 is depicted as being within computer system 601A, but in some embodiments, storage medium 606 may be distributed within and / or across multiple internal and / or external chassis of computing system 601A and / or additional computing systems. Storage medium 606 may include one or more different forms of memory, including semiconductor memory devices such as dynamic or static random access memory (DRAM or SRAM), erasable and programmable read-only memory (EPROM), electrically erasable and programmable read-only memory (EEPROM) and flash memory, magnetic disks such as fixed disks, floppy disks and removable disks, other magnetic media including magnetic tape, optical media such as compact disks (CDs) or digital video disks (DVDs), Blu-ray disks, and other optical media. ®disk or other type of optical storage or other type of storage device. Note that the instructions discussed above may be provided on one computer-readable or machine-readable storage medium, or alternatively, may be provided on multiple computer-readable or machine-readable storage media distributed in a large system that may have multiple nodes. Such one or more computer-readable or machine-readable storage media are considered to be part of an article (or product). An article or product may refer to any manufactured single component or multiple components. The one or more storage media may be located in the machine that runs the machine-readable instructions, or at a remote site from which the machine-readable instructions may be downloaded over a network for execution.

[0079] In some embodiments, the computing system 600 includes one or more GHG monitoring modules 608, which can perform at least a portion of one or more of the above methods. It should be understood that the computing system 600 is only one example of a computing system, and the computing system 600 may have more or fewer components than shown, and may be combined. Figure 6 Additional components not depicted in the example embodiment of FIG. 6A and / or computing system 600 may have Figure 6 Different configurations or arrangements of the components depicted in . Figure 6 The various components shown in the drawings may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and / or application specific integrated circuits.

[0080] In addition, the steps in the processing method described herein can be implemented by running one or more functional modules in an information processing device, such as a general-purpose processor or a dedicated chip, such as an ASIC, FPGA, PLD or other appropriate device. These modules, combinations of these modules and / or their combination with general hardware are all included in the protection scope of the present invention.

[0081] The geological interpretation, model, and / or other interpretation aids may be improved in an iterative manner; this concept applies to the embodiments of the present method discussed herein. This may include the use of a feedback loop executed on an algorithmic basis, such as on a computing device (e.g., computing system 600, Figure 6 ) and / or through manual control by a user, a user can determine whether a given step, action, template, model, or set of curves has become sufficiently accurate for evaluating the subsurface three-dimensional geological formation under consideration.

[0082] For the purpose of explanation, the foregoing description has been described with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive or limit the invention to the disclosed precise form. In view of the above teachings, many modifications and variations are possible. In addition, the order of the elements of the method shown and described can be rearranged, and / or two or more elements can occur simultaneously. The embodiments are selected and described in order to best explain the principles of the invention and its practical application, so that other technical personnel in the art can best utilize the present invention and various embodiments with various modifications suitable for the specific purpose expected.

Claims

1. A method comprising: determining locations to place one or more devices at a site, wherein each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG); measuring the concentration of GHG with a first sensor; quantifying a rate at which GHGs are emitted based at least in part on the measured GHG concentrations; determining a location of a GHG emission source at the site that is emitting GHGs as measured by a first sensor, wherein the location is determined based at least in part on the measured concentration, the quantified rate, or both; identifying a GHG emission source at the determined location by comparing the determined location to a list of a plurality of GHG emission sources at the site and its location; and The site and the identified GHG emission sources are displayed at the determined locations.

2. The method of claim 1 , wherein determining a location to place one or more devices is based at least in part on the latitude, longitude, and altitude of the site, the area of ​​the site, the terrain within and around the site, the structures within and around the site, the type of GHG emission sources at the site, the location of the GHG emission sources at the site, current and historical meteorological conditions at the site, or a combination thereof.

3. The method of claim 1, wherein the GHG emission source comprises a generator, a compressor, a valve, a tank, a pipeline or conduit, a well, a vehicle, or a combination thereof.

4. The method of claim 1, wherein each device further comprises a second sensor configured to measure wind speed and wind direction, wherein the location of the GHG emission source is also determined based at least in part on the measured wind speed and wind direction.

5. The method of claim 1, wherein each device further comprises: a third sensor configured to measure solar radiation; a fourth sensor configured to measure humidity; a fifth sensor configured to measure GPS coordinates; and a sixth sensor configured to measure temperature, Wherein the location of the GHG emission source is also determined based at least in part on solar radiation, humidity, GPS coordinates, and temperature. The method of claim 1 , further comprising determining that the measured concentration of GHG is not part of a scheduled exhaust event.

7. The method of claim 1, further comprising sending a notification in response to determining a location of a GHG emission source, identifying a GHG emission source, or both.

8. The method of claim 1, further comprising performing a wellsite action in response to determining a location of a GHG emission source, identifying a GHG emission source, or both.

9. A computing system comprising: one or more processors; and A memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations comprising: determining locations to place one or more devices at a site, wherein each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG); measuring the concentration of GHG with a first sensor; quantifying a rate at which GHGs are emitted based at least in part on the measured GHG concentrations; determining a location of a GHG emission source at the site that is emitting GHGs as measured by a first sensor, wherein the location is determined based at least in part on the measured concentration, the quantified rate, or both; identifying a GHG emission source at the determined location by comparing the determined location to a list of a plurality of GHG emission sources at the site and its location; and The site and the identified GHG emission sources are displayed at the determined locations.

10. The computing system of claim 9, wherein determining a location to place one or more devices is based at least in part on the latitude, longitude, and altitude of the site, the area of ​​the site, the terrain within and around the site, structures within and around the site, the type of GHG emission sources at the site, the location of the GHG emission sources at the site, current and historical meteorological conditions at the site, or a combination thereof.

11. The computing system of claim 9, wherein the GHG emission source comprises a generator, a compressor, a valve, a tank, a pipeline or conduit, a well, a vehicle, or a combination thereof.

12. The computing system of claim 9, wherein each device further comprises a second sensor configured to measure wind speed and wind direction, wherein the location of the GHG emission source is further determined based at least in part on the measured wind speed and wind direction.

13. The computing system of claim 9, wherein each device further comprises: a third sensor configured to measure solar radiation; a fourth sensor configured to measure humidity; a fifth sensor configured to measure GPS coordinates; and a sixth sensor configured to measure temperature, Wherein the location of the GHG emission source is also determined based at least in part on solar radiation, humidity, GPS coordinates, and temperature.

14. The computing system of claim 9, wherein the operations further comprise determining that the measured concentration of GHG is not part of a predetermined exhaust event.

15. The computing system of claim 9, wherein the operations further comprise sending a notification in response to determining a location of a GHG emission source, identifying a GHG emission source, or both.

16. The computing system of claim 9, wherein the operations further comprise performing a wellsite action in response to determining a location of a GHG emission source, identifying a GHG emission source, or both.

17. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations comprising: determining locations to place one or more devices at a site, wherein each device includes a first sensor configured to measure a concentration of a greenhouse gas (GHG); measuring the concentration of GHG with a first sensor; quantifying a rate at which GHGs are emitted based at least in part on the measured GHG concentrations; determining a location of a GHG emission source at the site that is emitting GHGs as measured by a first sensor, wherein the location is determined based at least in part on the measured concentration, the quantified rate, or both; identifying a GHG emission source at the determined location by comparing the determined location to a list of a plurality of GHG emission sources at the site and its location; and The site and the identified GHG emission sources are displayed at the determined locations.

18. The non-transitory computer-readable medium of claim 17, wherein each device further comprises a second sensor configured to measure wind speed and wind direction, wherein the location of the GHG emission source is further determined based at least in part on the measured wind speed and wind direction.

19. The non-transitory computer readable medium of claim 17, wherein each device further comprises: a third sensor configured to measure solar radiation; a fourth sensor configured to measure humidity; a fifth sensor configured to measure GPS coordinates; and a sixth sensor configured to measure temperature, Wherein the location of the GHG emission source is also determined based at least in part on solar radiation, humidity, GPS coordinates, and temperature.

20. The non-transitory computer-readable medium of claim 17, wherein the operations further comprise performing a wellsite action in response to determining a location of a GHG emission source, identifying a GHG emission source, or both.

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