Authors
Thomas E. BarchynChris H. HugenholtzTyler R. GoughColeman VollrathMozhou Gao
Topics
Reservoir Engineering and Simulation MethodsWater Systems and OptimizationOil Spill Detection and Mitigation1 Low-cost fixed sensor deployments for leak detection in upstream oil and gas: 2 operational analysis and discussion of a prototypical program 3 Thomas E. Barchyn *,1, Chris H. Hugenholtz 1, Tyler Gough 1, Coleman Vollrath 1, Mozhou Gao 1 4 5 6 *Corresponding author: tbarchyn@ucalgary.ca 7 1 8 Centre for Smart Emissions Sensing Technologies, Department of Geography, University of Calgary, 2500 9 University Drive NW, Calgary, AB, T2N 1N4, Canada 10 11 Note: this is a non-peer reviewed preprint. Subsequent versions of this paper may have different content. 12 Please contact tbarchyn@ucalgary.ca with any questions or comments. 13 14 Abstract 15 Low-cost fixed sensors are an emerging option to aid in the management and reduction of methane 16 emissions at upstream oil and gas sites. They have been touted as a cost-effective continuous monitoring 17 technology to detect, localize, and quantify leaks. However, to support emissions management, the efficacy 18 of low-cost fixed sensors must be assessed in the context of the sites, technologies, methods, work practices, 19 action thresholds, and outcomes that constitute a broader program to manage and reduce emissions. Here, 20 we build on technology-focused research and testing by defining a prototypical low-cost fixed sensor 21 program framework as considered from an operational perspective. We outline potentially large operational 22 cost penalties and risks to industry relative to incumbent programs. Most costs are caused by: (i) follow-up 23 callouts, (ii) non-target emissions, and (iii) maintenance requirements. These represent core areas for 24 improvement. Together the framework and discussion point to significant economic and operational 25 challenges with low-cost fixed sensor leak detection programs and highlight the need for careful 26 consideration in regulations and emissions management program design. 27 28 Introduction 29 Reducing methane emissions from the upstream oil and gas industry is one of the easiest and most effective 30 actions that can be taken to mitigate near-term global temperature rise (Nature Editors, 2021). First, because 31 methane is the principal component of natural gas, a significant portion of emissions from the oil and gas 32 supply chain can be addressed with little cost or paid for through increased production. Second, proven 33 solutions exist for most common issues. Third, while methane is a highly potent greenhouse gas, its short 34 atmospheric lifetime relative to carbon dioxide means that immediate emissions reductions have near-term 35 sub-decadal effects. These facts have led regulators globally to accelerate efforts to reduce emissions 36 (ECCC, 2018; CDPHE, 2019; PDEP, 2019; AER, 2020; EU, 2020; NMED, 2020; US EPA, 2021) and 37 spurred the formation of international climate agreements and commitments targeting methane from the oil 38 and gas sector. 39 40 The problem of reducing methane emissions from the upstream oil and gas industry is multi-faceted due to 41 the complexity of infrastructure. There are hundreds of thousands of upstream sites that have very little 42 equipment but carry significant potential to emit. These sites are geographically dispersed across vast 43 production basins. Generally, the problem can be split into issues that have known locations and known 44 abatement options (e.g., pneumatics, intentional vents), and issues that have unknown locations and 45 unknown magnitude (e.g., leaks, abnormal or unexpected vents). Finding and fixing these unknown sources46 fast has been a major focus of scientific interest and technology development and is part of a process known 47 as Leak Detection and Repair (LDAR). 48 49 Efforts to find these unknown sources are often met with industry cost concerns (Patel, 2017). These 50 concerns, coupled with the need to better understand emissions (UNEP, 2020; Wang et al., 2022), have led 51 to rapid development of new technology to detect, measure, and locate unknown and anomalous emissions 52 (Fox et al., 2019a). This technology is nascent and, in many cases, unproven at scale for reducing emissions, 53 yet shows some promise (Ravikumar et al., 2019; Schwietzke et al., 2019; Sherwin et al., 2021, 2022; Bell 54 et al., 2022; Erland et al., 2022). This paper concerns a specific class of emissions detection and abatement 55 program. 56 57 In many jurisdictions, emissions reductions are prescribed by the regulator. Emissions reductions are 58 normally achieved through prescribed actions (e.g., periodic Optical Gas Imaging, OGI surveys). However, 59 regulators are becoming increasingly flexible, trending towards allowing customized programs involving a 60 range of technologies and actions (US EPA, 2022). In Alberta, Canada, the provincial regulator has allowed 61 customized pilot programs since 2021 (AER, 2020). These customized programs are approved on the basis 62 that they will reduce a certain volume of methane equivalent to standard periodic OGI surveys (AER, 63 2020). As emissions reductions are pre-specified, operators are motivated to design an LDAR program that 64 achieves the prescribed emissions reductions, at the lowest cost possible. 65 66 The cost of equipment for emissions detection, measurement, and localization is not the only cost that 67 matters – costs borne by industry have a much broader scope. Emissions measurement equipment can 68 provide (i) incorrect information (e.g., biased emissions quantifications or false positive detections), or (ii) 69 imprecise information (e.g., detect emissions at a site, but not locate it accurately, necessitating a time 70 consuming search). And once an emissions source has been identified, there are costs associated with the 71 repair. Additionally, there are a wide range of business-related costs associated with the risks of emissions 72 reduction underperformance (e.g., regulatory or public relations risks). 73 74 First, costs are borne at the program level – the cost of the emissions measurement equipment is often only 75 a small part of total costs. Second, emissions reductions occur at the program level from the full suite of 76 activities within the program. Third, the quality of information provided by emissions measurement 77 technology affects program cost; there is a clear market for accuracy and precision to guide targeted repairs 78 and investigation. And fourth, the more data and information industry has on the sources, rates, and root 79 causes of its emissions, the more optimized and tailored a program can be, saving costs. There is strategic 80 value in synoptic emissions information. 81 82 Cost pressure has led to considerable discussion of a particular class of emissions measurement technology 83 known as ‘low-cost fixed sensors’ (Siebenaler et al., 2016; Patel, 2017; Riddick et al., 2020, 2022). These 84 are small, tripod- or pole-mounted emissions measurement systems similar to weather stations that are 85 typically mounted around sites at the fence-line (Figure 1). Because these systems are relatively 86 inexpensive and developed using mass-produced, consumer-grade commodity components, they have 87 potential to enable cost-effective continuous monitoring at scale (e.g., hundreds to thousands of oil and gas 88 sites). However, they also typically lack the quality and accuracy of scientific-grade sensors (Peltier et al., 89 2021). Interest in low-cost fixed sensors has been spurred by the Methane Detectors Challenge (Siebenaler 90 et al., 2016) and regulatory signals in proposed methane rules (US EPA, 2022; Government of Canada, 91 2022). This interest is warranted, but a deep study of the merits of programs built upon the technology is 92 lacking.93 94 95 96 Figure 1. Example of low-cost fix sensors (a, b). 97 The anemometer provides wind speed and direction, most systems use either a sonic anemometer (a), or 98 inexpensive cup / vane (b). The methane sensor, modem, and computer infrastructure are inside a 99 weatherproof box that is open on the bottom to allow flush of air. In almost all cases, low-cost fixed sensors 100 are powered by a small solar panel and battery. 101 102 103 Here, we expand the scope of previous research from evaluations of low-cost sensors in isolation to 104 evaluations of these sensors within the broader operational context of a prototypical methane emissions 105 management program. . This work adds to existing research and testing that has considered field 106 performance of low-cost fixed sensors (e.g., Siebenaler et al., 2016; Riddick et al., 2022; Bell et al., 2022). 107 Our goal is to develop a more complete understanding of the programs built around this type of emissions 108 measurement technology by identifying areas for advancing these technologies and their implementation. 109 110 We base our discussion on a prototypical low-cost fixed sensor program framework that describes the sites 111 and emissions sources, primary and secondary methods, and abatement efforts. We discuss important 112 regulatory considerations, cost levers, and areas and feasibilities of technical advances required to improve 113 performance. Our comparison benchmark throughout is the common regulatory standard: periodic (e.g., 114 quarterly) OGI surveys. 115 116 In this discussion we do not consider emissions reductions explicitly for three reasons: (i) most emissions 117 reduction programs are mandatory, where the regulator prescribes the required emissions reductions, (ii) 118 there is often little incentive for operators to reduce emissions beyond regulatory compliance, and (iii) 119 emissions reductions are rarely empirically measured – demonstrating emissions performance is elusive 120 whereas costs are carefully tracked. While there are emerging methods to monetize emissions reductions 121 beyond regulatory compliance, we leave these out of scope to simplify our discussion. 122 123 Prototypical low-cost fixed sensor program description 124 We begin by defining a precise prototypical emissions management program. For clarity, an emissions 125 management program defines the sites, methods, work practices, action thresholds, and outcomes thereof 126 to reduce emissions (Fox et al., 2019b). Ultimately, it is the program that results in emissions reductions, 127 not any given technology or method. Discussing operational aspects of emissions management at the128 program scale is more faithful to the true costs borne by industry as the interrelations between different 129 aspects of the program can be considered. 130 131 Our program has two emissions measurement methods and work practices. First is our prototypical low 132 cost fixed sensor, which provides emissions event detections, localizations, and quantifications at the 133 equipment group scale in the form of alerts. These alerts trigger follow-up with OGI to identify the exact 134 component that is emitting. Finally, images and data from the OGI follow-up can trigger abatement (Figure 135 2). We do not explicitly consider the emissions reductions of the program. We assume that it is designed 136 and implemented to achieve regulatory compliance (Fox et al., 2019b; 2021a; 2021b). 137 138 139 140 Figure 2. Flow chart of prototypical low-cost fixed sensor program. 141 The low-cost fixed sensor program uses a multi-step pathway to abatement. First, an emissions source 142 occurs, which is subsequently detected by the fixed sensor. If the detection or quantification exceeds pre 143 defined thresholds, an alert is issued. Then the operator interprets the data from the low-cost fixed sensor 144 and requests a follow-up OGI survey. In our program, all alerts proceed to OGI survey, but this 145 interpretation step is an important modulator of program cost. If the source is identified as a target for the 146 program, a leak tag can be issued, and abatement performed. 147 148 149 Sites 150 We model our prototype sites after upstream oil and gas sites that are common across North America. These 151 sites typically contain one or several wells that flow into simple separators. In the case of gas production, 152 the separators split up liquid phase hydrocarbons or water, which are stored in an onsite tank and 153 periodically trucked out. In the case of oil production, the separators split up the gas phase hydrocarbons, 154 which are often vented or flared (combusted) on site. The oil is collected in a large onsite tank and is also 155 periodically trucked out. Our prototypical sites do not have mains electricity – onsite produced gas is used 156 to control the processes. These sites are very common across North America and present a good case study 157 for emissions management. 158 159 Upstream sites have several known classes of emissions:160 161 • Leaks: unintended emissions that occur in locations that are not designed to emit. These occur due 162 to inevitable degradation of production equipment over time and unintended repair or assembly 163 mistakes. 164 • Vents: intended emissions that exist by design on the site and are therefore, in most cases, 165 understood. For example, it is normal to use gas-driven pneumatic controllers on upstream sites as 166 the gas pressure provides an easy power source to actuate valves. Often, casing vents on a wellhead 167 are vented to release pressure associated with gas build-up in the well casing. In cases where liquids 168 production is the target, gas is often considered waste and is vented if it cannot be combusted or 169 tied into a pipeline. 170 • Non-routine venting: emissions where a known vent emits more or less than the engineered rate. 171 We treat this as a separate class of emissions event as it has a known source location, but a rate that 172 is different than the known rate. 173 • Combustion process emissions: emissions associated with incomplete combustion of gas on 174 upstream sites. Gas is often combusted to (i) dispose of the gas while lowering the climate impact 175 by converting methane to carbon dioxide (e.g., flaring or incineration), or (ii) provide power or heat 176 for some part of production such as compression, pumping, or another use. 177 • Maintenance emissions: short-lived emissions events related to regular processes (e.g., liquid 178 transfers) or maintenance activities. Emissions often occur when any equipment is being 179 depressurized, or when any managed changes in process conditions occur. 180 181 Low-cost fixed sensors and work practice 182 The prototypical low-cost fixed sensor used here mirrors commercially available options (Bell et al., 2022) 183 (Figure 1). Emissions sources emit methane that is advected by the wind to the sensor, which measures the 184 methane concentration anomaly and coeval wind speed and direction. The raw data are periodically 185 processed to map the location of emissions sources, quantify emissions rates, and eventually trigger alerts 186 for follow-up. The sensor unit consists of five basic hardware components: 187 188 • Methane concentration: a low-cost metal oxide total hydrocarbon sensor is used to measure the 189 methane concentration. This sensor may be coupled with a small fan to improve temporal response. 190 These sensors have several well-understood issues and require careful data conditioning and regular 191 maintenance to be useful (Peltier et al., 2021; Furuta et al., 2022). 192 • Wind: a wind speed and direction sensor, which is used to locate the emissions source and provide 193 quantification algorithms with wind data. 194 • Onsite compute infrastructure: a small, single-board IoT-enabled computer system with 195 supporting sensors and modules to record measurement data and communicate with offsite 196 computer infrastructure. 197 • Power: a power source and mounting hardware. 198 • Offsite computer infrastructure: an offsite computer infrastructure to process raw measurements, 199 converting them to emissions detections, localizations, and quantifications. Comparing these 200 processed data against pre-defined thresholds produces alerts. 201 202 In our prototypical program the deployment is designed by the low-cost fixed sensor vendor such that they 203 specify the number of fixed sensors required to meet a certain performance specification (similar to Bell et 204 al., 2022). As the fixed sensor only provides emissions data when downwind of equipment, it is usually 205 necessary to deploy at least four systems per site.206 207 Our prototypical low-cost sensors do not function without field support from a local technician. First, during 208 install and in any changes to the equipment on site, the locations of all possible emissions sources 209 (equipment) are surveyed and uploaded to the offsite computer infrastructure. This is necessary because 210 fixed sensors themselves do not know where equipment are located. Including the locations where there is 211 a potential to emit significantly improves algorithm performance. Second, downtime associated with broken 212 sensors must be resolved reasonably quickly to maintain compliance – local technicians are required to 213 repair or replace sensors. Third, all sensors across the fleet require periodic maintenance and calibration. 214 This ranges from evaluating sensor drift on a regular basis by comparing against a reference instrument, to 215 replacing batteries, clearing snow and dust off solar panels, and cleaning the intake filters. Maintenance is 216 critical to maintain system specification. 217 218 Once collected, data are transmitted off-site and run through a suite of algorithms: 219 220 • Quality control and error detection: raw data must be automatically checked for errors that could 221 indicate sensor problems. Any issues flag human inspection and potentially trigger a service callout 222 to field technicians. 223 • Calibration and anomaly detection: once initial quality control is passed, the data are calibrated. 224 It is well known that low-cost metal-oxide sensors require careful and sensor-unique calibration to 225 produce useful data (Peltier et al., 2020; Furuta et al., 2022; Riddick et al., 2022). The raw data 226 timeseries are then analyzed for anomalies, which may represent plumes of methane from 227 equipment. 228 • Source localization and detection: the data are then fed into an updating model of source locations 229 that accumulates information on the probability that any given location on the site is emitting. Areas 230 upwind of detected plumes are nudged upwards in probability of being a source (and vice versa). 231 These localization algorithms have been widely discussed and generally function (e.g., 232 Abdelghaffar et al., 2017). Localization performance is significantly improved when masked with 233 known equipment locations determined at install. 234 • Source quantification: once a potential known source is localized with high probability, emissions 235 quantification can be performed. There is a diverse range of quantification algorithms available, 236 but this prototypical sensor uses a variation of EPA OTM 33A, which is a well understood point 237 source Gaussian model that provides screening grade emissions quantifications (Thoma and Squier, 238 2014; Riddick et al., 2022). 239 • Alerting: source detections, localizations, and quantifications are then considered against the pre 240 defined alert thresholds to issue text message or email alerts to operators. Thresholds are pre 241 defined as part of the program to maintain a desired performance specification. 242 243 Interpretation and OGI follow-up 244 Alerts from the low-cost fixed sensor system are passed over to site operators for follow-up investigation. 245 How the operator deals with these alerts is a major component of fixed-sensor programs that requires 246 considerable discussion and is likely the most difficult component of the entire program to regulate and 247 ensure reliable and knowable performance. 248 249 For our prototypical program, all alerts immediately trigger an OGI inspection to ensure an emissions 250 reduction outcome. However, outside of our program there are several possible scenarios: (i) ignore: the 251 operator could simply ignore the alert, (ii) triage: the operator could issue immediate instructions for follow 252 up only when an alert is significantly out of the ordinary, (iii) investigate: the operator could conduct a253 simple investigation without specialized equipment, or (iv) investigate with OGI: upon failure to identify 254 any emissions through simple investigation, the operator could conduct a more rigorous investigation with 255 an OGI camera, which can isolate the component that is leaking. 256 257 The decision that an operator makes can be both clouded and informed by knowledge of the facility. 258 Operators have deep knowledge of the processes at their facilities and are best positioned to interpret 259 emissions events. For example, vents that have temporal variation in their emissions rate, yet on average 260 are emitting design rates, could be justifiably ignored; however, it takes a human with knowledge of the 261 site and previous emissions to make that interpretation. Localization skill of the alert can meaningfully 262 affect decisions. If the emissions source can be localized to a certain piece of equipment this can assist in 263 two ways: (i) interpretation could be much easier, and (ii) the follow-up could be targeted, reducing survey 264 time and cost (but not mobilization cost). 265 266 OGI surveys are costly – but in our prototypical program there is no path to abatement without component 267 scale identification and confirmation of the exact issue. Abatement requires detailed information and the 268 low-cost fixed sensor alone cannot provide sufficient information. 269 270 Abatement 271 Abatement can be considered from two lenses: (i) required abatement as part of the program, and (ii) non 272 required abatement enabled by program data. In our example, leaks are the required abatement as it is 273 effectively an LDAR program. Other emissions sources could be abated, or the program could contribute 274 information to help with other abatement – but operators would likely have difficulty getting ‘credit’ for 275 these emissions reductions with the regulator or public. 276 277 There are three technical pathways to abatement in our program. First, repairs are triggered by a leak tag 278 that is identified by the OGI follow-up crew. Leaks are the only ‘required abatement’ in our program. 279 Second, retrofits are larger redesigns of sites or selective replacement of venting components. These are 280 often pre-planned and funded as a larger capital expenditure. In our prototypical program the low-cost 281 sensors do not help here beyond confirming the presence of the issue or perhaps triaging the order of 282 retrofits in the case of non-routine venting. Examples of retrofits are changing pneumatic controllers from 283 high-bleed to low- or no-bleed and installing refuse venting burners or flares. Third, changes to operational 284 procedures can be instituted as a result of emissions measurement – and be a relatively low-cost and 285 straightforward method to mitigate emissions. Examples include changes to protocols for tank loading to 286 minimize emissions or adding checks for closed thief hatches to operator checklists. Changes to operational 287 procedures can have very material effects on some of the largest emissions events such as pipeline 288 blowdowns. 289 290 These additional abatement benefits that come from the low-cost fixed sensor program data are not 291 explicitly modeled in program deployment and are difficult to quantify, but could be sufficiently valuable 292 for some operators who are motivated to achieve emissions reductions beyond regulatory compliance. 293 294 Program cost 295 Framework 296 To better understand program costs, we developed a cost comparison framework for the entire program. 297 The framework cannot provide precise cost estimates; our goal is to unpack how costs occur and identify 298 how they manifest. We have included a spreadsheet in the Supplemental material that provides a sandbox 299 for program cost modeling (see Supplemental material table S1, Supplemental material text S1). Three300 broad categories of costs exist in low-cost fixed sensor programs: equipment, service and support, and 301 follow-up inspections. These costs are controlled by the size of the program (number of sites), maintenance 302 requirements, and the frequency of alarms triggering follow-up OGI inspections. Our basis for comparison is a periodic visit (quarterly) OGI survey program. The OGI survey program costs ( 303 ) are: 304 = ̅ 305 (1) 306 where is the duration of the program in years, is the number of sites in the program, 307 is the number of OGI inspections per year, and ̅ 308 is the average OGI inspection cost per site. The OGI inspection cost 309 includes the vehicles, staff, OGI camera, and all business-related expenses associated with the service of 310 OGI inspections. 311 The low-cost fixed sensor program costs ( 312 ) are comprised of a mix of low-cost fixed sensor costs and 313 follow-up OGI: 314 = (̅ + ̅ ̅ 315 ) (2) 316 where ̅ 317 is the average cost per year for the network of fixed sensors at a site and ̅ is the average annual 318 number of follow-ups required as a result of low-cost fixed sensor alerts. 319 The cost per year of the fixed sensor infrastructure ̅ 320 is composed of many different sub-costs. For initial 321 capital, the purchase of the fixed sensors is the main cost. The initial capital cost can be internalized many 322 ways, ranging from lease to outright purchase. The low-cost fixed sensors cannot operate without ongoing 323 operational costs such as maintenance, support, periodic replacement, offsite data processing, and business 324 related costs for the low-cost fixed sensor company which are often packaged into a monthly fee. For 325 simplicity, we consider the low-cost fixed sensor costs as a yearly cost that rolls up both capital and ongoing 326 operational costs, although the costs could be modeled as an upfront purchase by some operators. 327 The number of fixed sensors per site is part of fixed sensor infrastructure costs ̅ 328 , and is pre-specified as 329 part of a program design. In general, the more sensors deployed at a site, the higher the data quality. It is 330 up to the fixed sensor vendor to design the deployment to meet a modeled performance specification; the 331 number of sensors on a site cannot reasonably be a free parameter without modeling performance (Bell et 332 al., 2022). 333 334 Cost equality between the base OGI program and low-cost fixed sensor program occurs in a situation where 335 Eqn. (1) and (2) are combined: 336 ̅ = (̅ + ̅ ̅ 337 ) (3) 338 339 and simplified to 340 ̅ = ̅ + ̅ ̅ 341 (4) 342 343 For the low-cost fixed sensor to be cost competitive, the number of follow-up surveys in the low-cost fixed 344 sensor program must be less than the regulatory OGI program. This is because the low-cost fixed sensor program carries ongoing operational costs (̅ 345 ) to keep the fixed sensors operating. There is nuance here as346 it is possible that follow-up surveys could be mixed with simple operator follow-up inspections 347 (mobilization costs, but no specialized OGI survey fees), but in our specific program, the OGI inspection 348 must be involved to trigger abatement and meet regulatory imposed emissions reductions, so costs are 349 effectively equivalent. 350 351 OGI surveys are typically quoted on a per-site basis, but the cost is a time-based cost that has two major 352 components: mobilization and survey costs. Mobilization costs for OGI surveys are lower on a per-site 353 basis if sites are surveyed in a focused campaign (as is common when every site requires a survey as part 354 of the regulatory OGI program). Mobilization costs for OGI surveys are higher when ad-hoc travel is 355 required to visit a specific site and candidate sites cannot be visited in some logical order to minimize drive 356 time. Survey costs are higher when the entire site must be surveyed and lower when only a portion of the 357 site requires a survey. While the precise calculations of the mobilization and survey costs for regulatory 358 OGI surveys are site specific, ad-hoc callouts required from low-cost fixed sensor alerts may have higher 359 mobilization costs. However, the localization skill of low-cost fixed sensors could reduce survey costs as 360 only a fraction of a site may require a survey. While these costs are site-specific, there is little evidence to 361 suggest that on average OGI surveys initiated as follow-up from fixed sensor alerts would be significantly 362 less expensive than standard OGI surveys. 363 364 Discussion scenarios 365 To examine how this framework for costing low-cost fixed sensor programs could manifest with real 366 numbers, we examine some prototypical scenarios (Table 1). Our costs are estimates and could vary for 367 any real deployment; specific cost scenarios can be modeled in the Supplemental material (see 368 Supplemental material table S1, Supplemental material text S1). 369 370 Our basic cost estimations are based on a 1-year program with 100 sites and are compared against an incumbent benchmark of quarterly OGI surveys. We use an OGI survey cost estimate (̅ 371 ) of $350 / site. 372 This is consistent with the mid-point of estimates in modeling studies (Fox et al., 2021a, b). The fixed sensor cost (̅ 373 ) is based on a requirement for 4 fixed sensors per site. For each fixed sensor, there are the 374 following costs: (i) hardware capital costs and depreciation ($500 / year, $2000 / year for a total site), which 375 includes periodic replacement (Peltier et al., 2021), (ii) one service visit per year at $350 to perform either 376 installation or perform yearly maintenance, (iii) an offsite compute cost of $100 / year per site (Peltier et al., 2021). Together the yearly fixed sensor cost (̅ 377 ) is $2450 per site – this is likely an underestimate and 378 implies that the low-cost fixed sensor vendor is operating at sufficient scale. 379 380 Reasonable estimates for the number of follow-ups triggered by the low-cost fixed sensor will vary based 381 on the skill of the low-cost fixed sensor and the emissions profile of the sites. With a consensus-developed 382 controlled release protocol, Bell et al. (2022) tested 6 fixed sensors (several of which are similar to our 383 prototypical program, solutions A, C, D, E, F, K). The strongest performer (solution E) issued 2,382 384 detection reports in 104 days, subject to 567 releases – 79% of alerts were false positives. The only low 385 cost fixed sensor tested by Bell et al. (2022) that would issue a potentially cost-effective number of alerts 386 was solution K, which only issued 2 alerts over a 200-day deployment. However, solution K only detected 387 0.3% of releases and likely has a very high detection limit, much higher than OGI. 388 389 The emissions profile of target sites can have a serious effect on program cost, particularly when a program 390 mandates follow-up from all alerts. Emissions such as vents, combustion emissions, and maintenance 391 emissions will likely trigger alerts, which will require follow-up inspection. Even in the situation where the 392 low-cost fixed sensor skill is perfect (a situation not well supported by results from Bell et al., 2022), there393 will be follow-up inspections that do not find abatable emissions – a major issue for cost efficiency. It is 394 possible that a quantification-based alert trigger could help mitigate these issues. For our discussion 395 scenarios we use two very optimistic situations: Scenario 1 uses 4 follow-up visits, and Scenario 2 uses 10 396 follow-up visits per site. 397 398 Table 1. Values for discussion scenarios. 399 Values are estimates used with Equations 1 and 2 to provide scenario estimates. For customized scenarios, 400 please use the supplied spreadsheet in Supplementary material table S1. Symbol Description and notes Estimated value Duration of program (years) 1 Number of regulatory OGI inspections per year4| | | | Number of sites in program | 100 | || --- | --- | --- | --- | --- | --- || | | ̅ | Average per-site annual follow-ups triggered | Scenario 1: 4 | || | | | by fixed sensor system | Scenario 2: 10 | || | | ̅ | Average OGI inspection cost per site ($) | $350 | || | | ̅ | Averaged annual per-site cost of fixed sensor | $2450 | |system ($)401 402 Using Eqns. 1 and 2, the costs are: 403 404 = $140000 ($1400 per site) 405 ( 1) = $385000 ($3850 per site) 406 ( 2) = $595000 ($5950 per site) 407 408 Cost parity (Eqn. 4) cannot be achieved in this example as the annual per-site cost of the fixed sensor system 409 is $2450, exceeding the cost of regulatory OGI at $1400 per year. Eqn. 4 also straightforwardly bounds the maximum yearly cost that a fixed sensor network could charge (̅ 410 ) to cover the fixed sensor equipment and service fees as the cost of a regulatory program (Eqn. 1). In our example ̅ 411 cannot exceed $1400 per 412 site per year and be less expensive than regulatory LDAR. From another perspective, Eqn. 4 quantifies the 413 cost of extra data that a low-cost fixed sensor may provide for an operator; the operator can consider the 414 value of that data for strategic emissions management (above meeting regulatory compliance). A 415 spreadsheet is provided for readers to explore their own cost scenarios (see Supplementary material table 416 S1 and Supplementary material text S1). 417 418 Discussion 419 Regulatory efficacy 420 Our prototypical low-cost fixed sensor program is likely close to the basic model that is being actively 421 considered by regulators. The U.S. Environmental Protection Agency’s (EPA’s) new proposed regulations 422 would allow duty holders to use continuous monitors as an alternative to quarterly OGI surveys for methane 423 emissions management (US EPA, 2022). Environment and Climate Change Canada (ECCC) is also 424 considering allowing continuous monitors as part of forthcoming regulations; however, additional details 425 on the potential approach have not been released (Government of Canada, 2022). The EPA’s proposed 426 regulations, if passed, would require continuous monitors to perform site-level emissions quantification ≥ 427 1x every 12 hours, to benchmark against thresholds that trigger operator action (US EPA, 2022). However, 428 reliance on site-level emissions quantification with fixed sensors is “premature” according to results 429 reported by Bell et al. (2022). While regulators are in a position where they are keen to accelerate the430 adoption of new technology into methane emissions management, they are often responsible for the 431 emissions reductions. 432 433 The first regulatory challenge relates to alert interpretation. In our program all alerts proceed to OGI follow 434 up. The process of alert interpretation and OGI follow-up is likely subject to considerable latitude in real 435 world execution. From an operational perspective, follow-up is expensive and in the case that follow-up is 436 unsuccessful at identifying abatable emissions (alerts are from vents or are false positives), the cost can be 437 seen as unproductive. This creates an issue where operators who have dealt with unproductive OGI follow 438 up surveys are keen to avoid the issue again and may reach for explanations that allow the alert to be 439 ignored. This type of behaviour is well-known in other fields involving automation, where high false alarm 440 rates degrade trust and performance (Yamada and Kuchar, 2006; Wickens et al., 2009). 441 442 Practically, alerts could be justifiably ignored if the source is interpreted as a known vent, emissions from 443 incomplete combustion, maintenance emissions, or some intermittent process event that cannot justify 444 further follow-up. Improved localization skill and possibly quantification could help improve the 445 interpretability of alerts, but the interpretation cannot be easily automated as it requires considerable 446 knowledge of the actual sites and process conditions (e.g., maintenance events). Operators are best 447 positioned to make these interpretations. 448 449 Regulators very likely face a situation where there is strong incentive to ignore alerts from fixed sensors. 450 This is a concerning issue as it suggests the emissions management program that exists on paper is different 451 from the program that is executed. Regulators would likely meet this challenge by codifying operations in 452 a prescriptive manner, as we did for our prototypical program. For example, they would require all alerts 453 to be investigated with a certain method in a prescriptive manner – or require some auditable explanation 454 of why the alert was ignored. 455 456 A regulatory situation where all alerts must trigger follow-up creates pressure on low-cost fixed sensor 457 companies to improve the accuracy of their alerts. This is productive, as preliminary results from Bell et al. 458 (2022) suggest that there is considerable room for improvement. It also may lead to more considered 459 deployments as some sites with closely spaced equipment or known persistent venting may be unsuitable 460 for low-cost fixed sensor programs. 461 462 To ensure program performance, regulators also need to manage the risk of low-cost fixed sensor non 463 performance. Core to this is maintenance of the gas sensing element. Results from the research community 464 underscore serious issues with many low-cost sensors, suggesting considerable maintenance requirements 465 to maintain performance standards (Peltier et al., 2021). A sensor that does not work will not issue alerts, 466 which may be a desirable state in some company cultures given the incentives against incurring follow-up 467 costs. 468 469 Additionally, blind testing of performance, and attaching those results to certain deployment standards, is 470 required to ensure reliable maintenance of performance standards. For example, the number of sensors per 471 site is an important qualifier of performance (Bell et al., 2022). The more sensors on a site, theoretically the 472 better the results. To ensure performance regulators need to carefully validate that the exact configurations 473 during testing (as a qualifier of results) are extended to deployments. 474 475 Program cost476 One of the primary concerns of industry when confronted with methane emissions management is cost. 477 While the initial deployment costs of low-cost fixed sensors are attractive, this discussion reveals that the 478 total program cost could be much larger than expected; there are important cost linkages between different 479 components of a program. When compared against a regulatory periodic OGI program, there is relatively 480 little room for low-cost fixed sensor costs. Low-cost fixed sensor vendors face considerable pressure to 481 reduce the deployment cost while simultaneously increasing the skill of alerts. 482 483 Localization skill could help reduce costsin two ways: (i) reducing costs of follow-up OGI as only a fraction 484 of a site needs to be inspected (the on-site survey time only, not mobilization costs), and (ii) allowing 485 operators to triage known vents without triggering a follow-up survey (if allowed in regulations). While 486 both may reduce total program costs, it is not clear by how much. Mobilization costs of ad-hoc follow-up 487 surveys could dominate follow-up OGI costs and some reduction in survey times could be negligible. While 488 we use the $350 / site visit value for both follow-up and regulatory OGI inspections, it is possible that ad 489 hoc callouts could be much more expensive due to inefficient mobilization. Furthermore, there are 490 important operational management issues (e.g., availability of OGI cameras and operators) associated with 491 managing capacity for timely ad-hoc surveys. 492 493 Some site configurations will be more costly than others. Vents, non-routine venting, and combustion 494 emissions should all trigger alerts. Vent alerts must be ignored to make a low-cost fixed sensor program 495 tenable. If there is no capacity to selectively ignore alerts from vents in regulations, sites with vents may be 496 unsuitable for low-cost fixed sensor programs. If vent alerts are ignored or ‘blacked out,’ this creates another 497 issue where the equipment containing vents must be surveyed for leaks with some other method such as 498 periodic OGI as it can be difficult to confidently say there is no leak next to the vent. Equipment-scale 499 quantification may help unravel the emissions signature of a piece of venting equipment with a leak – but 500 this may be beyond the present capabilities of low-cost fixed sensors (Bell et al., 2022). Despite these 501 limitations, low-cost fixed sensors may help with extreme non-routine vents or large magnitude leaks, but 502 interpretation demands very careful analysis of both process conditions and alert accuracy metrics by an 503 operator who understands the specifics of the site in question. 504 505 Our analysis does not consider cost of abatement. It is possible that a low-cost fixed sensor program could 506 produce most emissions reductions through fast identification of large emitters in situations with highly 507 skewed emissions distributions. Abatement costs should be lower if fewer repairs are conducted of large 508 sources, instead of repairing many sources following each periodic OGI survey – while producing 509 equivalent emissions reductions. However, it is unclear if low-cost fixed sensors have sufficient skill to 510 effectively triage emissions and reduce abatement costs (Bell et al., 2022). 511 512 Technical performance discussion 513 This discussion suggests that low-cost fixed sensor technical performance is imperative and even small 514 inaccuracies carry significant cost, trust, and regulatory penalties. It is worthwhile to consider the technical 515 barriers to improved performance and discuss whether improved performance is technically feasible within 516 use case constraints. 517 518 First, low-cost fixed sensor hardware demands formalized, transparent, and effective quality management. 519 Accurate alerts require quality measurements, which requires care in installation and a maintenance 520 schedule. For example, an issue where an anemometer is bent out of alignment could read incorrect wind 521 directions and mis-locate an emissions source or provide false confidence in a detection. The error is 522 sourced at the instrument. Maintaining a performance specification for weather station type instruments523 requires care and is technically feasible – but it may require more than one technician visit per year as 524 assumed in our scenarios. 525 526 Second, low-cost fixed sensor algorithms require considerable reflection. Most low-cost fixed sensor 527 algorithms are proprietary but are unlikely to vary considerably from our prototypical description. 528 Localization performance has reasonable paths to improvements in total program cost effectiveness, and in 529 the case where accuracy was sufficiently validated, could provide a case to regulators that localization could 530 be used to streamline follow-up and make defensible interpretations about known vents. However, 531 emissions quantification has proven to be a considerable challenge (Bell et al., 2022; Riddick et al., 2022); 532 it is unclear whether sufficiently large improvements to quantification are likely to occur in the near future. 533 534 Third, it is not clear that metal oxide sensors are fit for this purpose (Peltier et al., 2021). The incredible 535 program costs associated with follow-up visits suggest that utilizing an extremely low-cost commodity 536 sensor in a central position with such considerable leverage carries significant risk. There is abundant 537 justification for more expensive sensors to mitigate cost escalation risk, simplify the anomaly filtering 538 algorithms (e.g., Riddick et al., 2022), and improve performance. 539 540 Closely related to these issues is the slow pace to market reward for technical improvements. After 541 development, technical developments such as new algorithms must be tested to show regulators and clients 542 the performance gains. Unfortunately, the only feasible method to demonstrate performance involves 543 controlled release testing experiments (Bell et al., 2022), leading to a lengthy develop, seal, deploy 544 workflow that inherently slows technical improvements. 545 546 Conclusions 547 Here we discuss a prototypical low-cost fixed sensor emissions management program for the upstream oil 548 and gas industry. Inter-relations between the various technologies dominate costs and issues, mostly in the 549 form of follow-up costs. Although the initial cost of low-cost fixed sensors could be low, and as a result 550 attractive to operators, costs could be significantly more expensive than periodic regulatory OGI surveys. 551 This noted, operators may see sufficient additional value in the low-cost fixed sensors to justify the cost 552 premium. 553 554 Regulators face a considerable challenge addressing flexibility in alert interpretation and follow-up. 555 Flexibility to selectively ignore alerts (particularly from vents) is likely to be the only way that such a 556 program could be cost competitive, but in some situations this creates opportunity for abuse of that 557 flexibility. 558 559 While fixing the issue of ineffective alerts in low-cost fixed sensors is very likely possible through better 560 sensors, improved quality management, and better algorithms, the need for root cause interpretation and 561 the widespread presence of known emissions sources indicate that there could be a ceiling for alert 562 improvements. The latest performance results from Bell et al. (2022) suggest there is considerable distance 563 to go to improve results. 564 565 In summary, this discussion suggests that the cost and operational penalties associated with inefficient and 566 unnecessary follow-up could be a definable hallmark of low-cost fixed sensor programs, and considerable 567 work is required across all aspects of sensor performance, program design, and regulations to achieve 568 desired results. We recommend considerable caution with low-cost fixed sensors at present. 569570 References 571 Abdelghaffar, HM, Woolsey, CA, Rakha, HA 2017. Comparison of three approaches to atmospheric source 572 localization. Aerospace Information Systems 14: 1. DOI: https://doi.org/10.2514/1.I010440. 573 574 AER 2020 [Internet]. Directive 060: Upstream petroleum industry flaring, incinerating, and venting. 575 Alberta Energy Regulator. https://www.aer.ca/regulatingdevelopment/rules-and 576 directives/directives/directive-060. 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EPA proposes new source performance standards updates, emissions guidelines to reduce 676 methane and other harmful pollution from the oil and natural gas industry. United States Environmental 677 Protection Agency. https://www.epa.gov/controlling-air-pollution-oil-and-natural-gas-industry/epa-issues 678 supplemental-proposal-reduce. Accessed March 16, 2023. 679 680 Wang, L, Daniels, WS, Hammerling, DM, Harrison, M, Burmaster, K, George, FC, Ravikumar, A 2022. 681 Multiscale Methane Measurements at Oil and Gas Facilities Reveal Necessary Frameworks for Improved 682 Emissions Accounting. Environmental Science & Technology 56: 14743-17752. 683 684 Wickens, CD, Rice, S, Keller, D, Hutchins, S, Hughes, J, Clayton, K 2009. False alerts in air traffic control 685 conflict alerting system: Is there a “cry wolf” effect? Human Factors 51: 446–462. 686 687 Yamada, K, Kuchar, JK 2006. Preliminary study of behavioral and safety effects of driver dependence on 688 a warning system in a driving simulator. IEEE Transactions on Systems, Man and Cybernetics, Part A: 689 Systems and Humans 36: 602– 610. 690 691 Contributions 692 Contributed to conception and design: TEB, CHH, TG, CV, MG. Drafted and/or revised the article: TEB, 693 CHH, TG, CV, MG. Approved the submitted version for publication: TEB, CHH, TG, CV, MG. 694 695 Data accessibility statement 696 All data are available either in main manuscript or supplemental materials. 697 698 Funding information 699 The authors have no funding to report. 700 701 Competing interests 702 The authors have no competing interests. 703 704 Supplemental material 705 Supplemental material table S1. User editable low-cost fixed sensor budget. 706 A user-editable budget for exploring different cost scenarios using Eqns. 1-4. The budget also includes a 707 more nuanced cost breakdown than discussed in the main paper to aid more realistic cost modeling. All 708 costs estimates are approximate and do not represent any specific vendor or sensor. Available in this 709 repository as a Microsoft Excel file.710 711 Supplemental material text S1. Description of user editable budget. 712 Enhanced description of the mechanics of Supplemental material table S1. Available below. 713714 Supplementary Text S1 for “Low-cost fixed sensor deployments for leak detection in upstream oil 715 and gas: operational analysis and discussion of a prototypical program” 716 Thomas E. Barchyn *,1, Chris H. Hugenholtz 1, Tyler Gough 1, Coleman Vollrath 1, Mozhou Gao 1 717 718 719 *Corresponding author: tbarchyn@ucalgary.ca 720 1 721 Centre for Smart Emissions Sensing Technologies, Department of Geography, University of Calgary, 2500 722 University Drive NW, Calgary, AB, T2N 1N4, Canada 723 724 This supplemental material provides a reference for Supplemental Table S1, which provides a user-editable 725 budged for low-cost fixed sensor programs. 726 727 Nomenclature Symbol Description and Notes Total cost of OGI program ($) Total cost of fixed sensor program, including follow-ups ($) Duration of program (years) Number of regulatory OGI inspections per year Number of sites in program ̅ Average per-site annual follow-ups triggered by fixed sensor system ̅ Average OGI inspection cost per site ($) ̅ Averaged annual per-site cost of fixed sensor system ($) ̅ Averaged annual per-site persistent leak production rate ̅ Averaged annual per-site venting and maintenance emission (controlled emissions events) rate ̅ Averaged annual per-site intermittent leak production (uncontrolled emissions events) rate Fixed sensor false positive rate (%). Interpreted as false alarm rate. Fixed sensor false negative rate (%). Interpreted as rate of emission events missed. Fixed sensor localization capacity (%). Interpreted as the proportion of the site eliminated from OGI Inspection by fixed sensor localization. ̅̅̅̅ Averaged annual per-site follow-up visits ̅̅̅̅ Averaged annual per-site follow-up visits leading to repair ̅̅̅̅ Averaged annual per-site follow-up visits not leading to repair Total cost of fixed sensor systems for program ($) Total cost of follow-ups ($) Total cost of follow-up visits leading to repair ($) Total cost of follow-up visits not leading to repair ($) Budget effectiveness, interpreted as the portion of spending that contributed to repair (%) 728 Notes: In this table, the variables in bold text are those used for the ‘simple’ model currently written in the 729 manuscript as equation 1-4 and for the ‘simple’ sheet in the excel document. All other variables are for the 730 ‘advanced’ (as in more complex than the ‘simple’) version sheet in the excel document. 731 732 Equations733 Note: These equations apply to the ‘advanced’ budget in the supplementary Excel document. Equations 1- 734 4 in the main text address the ‘simple’ budget. Expected follow-ups per site is the number of true positives 735 plus the number of false positives: 736 ̅̅̅̅ = ((1 − ) + )(̅ + ̅ 737 ) (S1) 738 739 The number of follow-ups per site ignores the ECE value, with the logic being that these emissions are 740 known to the operator and any alarm triggered (or not) will be ignored by the operator. In fact, ECE is not741 used in any of the calculations, but is included here for completeness.742 The number of follow-ups per site expected to lead to repair is:743̅̅̅̅ = (1 − )̅ 744 (S2)745746 The logic here is that only persistent leaks that are not false positives will be able to be found and repaired.747 The number of follow-ups not expected to lead to repair is:748̅̅̅̅ = (̅ + ̅ ) + (1 − )( ̅ 749 ) (S3)750751 The logic here is that follow-up events that are false positives (left side of the addition) or are for unknownintermittent emissions (right side of the addition) will not lead to repairs. It follows that for each of ̅̅̅̅ 752and ̅̅̅̅ 753 , the cost of spending expected to leadi to repairs and no repairs are:754= ̅̅̅̅ (̅ 755 (1 − )) (S4)= ̅̅̅̅ (̅ 756 (1 − )) (S5)757758 where LC is a scalar ranging from 0-1 that is the ‘localization capacity’ of the fixed sensor system, which759 can be interpreted as the answer to the question ‘what percentage of the site is eliminated from consideration760 as the potential leak source?’. As discussed in the main text, this is an estimate and and does not separate761 deployment costs and survey times. This value could conceivably exceed 1 if the cost of follow-up is762 expected to be greater than a standard OGI survey.. The total cost of the program is:763= + + 764 . (S6)765766 Finally, there is a ‘budget effectiveness’ metric included in the Excel document, which can be interpreted767 as what percentage of total spending is leading to repairs:768=+( )769 . (S7)770771 This metric considers the only effective spending to be the cost of the follow-up leading to repair plus772 whatever fraction of the fixed sensor cost is contributing to follow-ups that lead to repair. A value of 1773 would mean all follow-ups lead to repair.774775
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PublishedApr 11, 2023
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