Optimizing continuous monitoring sensor placement on oil and gas sites Article Swipe
Meng Jia
,
Troy Sorensen
,
Dorit Hammerling
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.26434/chemrxiv-2024-5qcnw
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.26434/chemrxiv-2024-5qcnw
We propose a generic, modular framework to optimize the placement of continuous monitoring sensors on oil and gas sites aiming to maximize the methane emissions detection efficiency. Our proposed framework substantially expands the problem scale compared to previous related studies and can be adapted for different objectives in sensor placement. This optimization framework is comprised of five steps: (1) simulate emission scenarios using site-specific wind and emission information; (2) set possible sensor locations under consideration of the site layout and any site-specific constraints; (3) simulate methane concentrations for each pair of emission scenario and possible sensor location; (4) determine emissions detection based on the site-specific simulated concentrations; and (5) select the best subset of sensor locations, under a given sensor budget, using genetic algorithms combined with Pareto optimization. We demonstrate the practicality and effectiveness of our framework through its application to an oil and gas emission testing facility with a large search space of possible sensor locations; a setting which is computationally infeasible to solve with commonly used mixed-integer linear programming formulations. Additionally, a case study illustrates the successful application of our algorithm to a real oil and gas site, showcasing its real-world applicability and effectiveness.
Related Topics
Concepts
Modular design
Integer programming
Set (abstract data type)
Computer science
Pareto principle
Multi-objective optimization
Mathematical optimization
Genetic algorithm
Methane
Wireless sensor network
Environmental science
Real-time computing
Algorithm
Mathematics
Ecology
Computer network
Operating system
Biology
Programming language
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.26434/chemrxiv-2024-5qcnw
- https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/66cd5008a4e53c4876b93af7/original/optimizing-continuous-monitoring-sensor-placement-on-oil-and-gas-sites.pdf
- OA Status
- gold
- Cited By
- 1
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401959246
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401959246Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26434/chemrxiv-2024-5qcnwDigital Object Identifier
- Title
-
Optimizing continuous monitoring sensor placement on oil and gas sitesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-08-28Full publication date if available
- Authors
-
Meng Jia, Troy Sorensen, Dorit HammerlingList of authors in order
- Landing page
-
https://doi.org/10.26434/chemrxiv-2024-5qcnwPublisher landing page
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https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/66cd5008a4e53c4876b93af7/original/optimizing-continuous-monitoring-sensor-placement-on-oil-and-gas-sites.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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-
https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/66cd5008a4e53c4876b93af7/original/optimizing-continuous-monitoring-sensor-placement-on-oil-and-gas-sites.pdfDirect OA link when available
- Concepts
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Modular design, Integer programming, Set (abstract data type), Computer science, Pareto principle, Multi-objective optimization, Mathematical optimization, Genetic algorithm, Methane, Wireless sensor network, Environmental science, Real-time computing, Algorithm, Mathematics, Ecology, Computer network, Operating system, Biology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.five | 56 |
| abstract_inverted_index.pair | 89 |
| abstract_inverted_index.real | 185 |
| abstract_inverted_index.site | 77 |
| abstract_inverted_index.used | 167 |
| abstract_inverted_index.wind | 64 |
| abstract_inverted_index.with | 125, 148, 165 |
| abstract_inverted_index.based | 101 |
| abstract_inverted_index.given | 118 |
| abstract_inverted_index.large | 150 |
| abstract_inverted_index.scale | 34 |
| abstract_inverted_index.site, | 189 |
| abstract_inverted_index.sites | 18 |
| abstract_inverted_index.solve | 164 |
| abstract_inverted_index.space | 152 |
| abstract_inverted_index.study | 175 |
| abstract_inverted_index.under | 73, 116 |
| abstract_inverted_index.using | 62, 121 |
| abstract_inverted_index.which | 159 |
| abstract_inverted_index.Pareto | 126 |
| abstract_inverted_index.aiming | 19 |
| abstract_inverted_index.layout | 78 |
| abstract_inverted_index.linear | 169 |
| abstract_inverted_index.search | 151 |
| abstract_inverted_index.select | 109 |
| abstract_inverted_index.sensor | 48, 71, 95, 114, 119, 155 |
| abstract_inverted_index.steps: | 57 |
| abstract_inverted_index.subset | 112 |
| abstract_inverted_index.adapted | 43 |
| abstract_inverted_index.budget, | 120 |
| abstract_inverted_index.expands | 31 |
| abstract_inverted_index.genetic | 122 |
| abstract_inverted_index.methane | 23, 85 |
| abstract_inverted_index.modular | 4 |
| abstract_inverted_index.problem | 33 |
| abstract_inverted_index.propose | 1 |
| abstract_inverted_index.related | 38 |
| abstract_inverted_index.sensors | 13 |
| abstract_inverted_index.setting | 158 |
| abstract_inverted_index.studies | 39 |
| abstract_inverted_index.testing | 146 |
| abstract_inverted_index.through | 137 |
| abstract_inverted_index.combined | 124 |
| abstract_inverted_index.commonly | 166 |
| abstract_inverted_index.compared | 35 |
| abstract_inverted_index.emission | 60, 66, 91, 145 |
| abstract_inverted_index.facility | 147 |
| abstract_inverted_index.generic, | 3 |
| abstract_inverted_index.maximize | 21 |
| abstract_inverted_index.optimize | 7 |
| abstract_inverted_index.possible | 70, 94, 154 |
| abstract_inverted_index.previous | 37 |
| abstract_inverted_index.proposed | 28 |
| abstract_inverted_index.scenario | 92 |
| abstract_inverted_index.simulate | 59, 84 |
| abstract_inverted_index.algorithm | 182 |
| abstract_inverted_index.comprised | 54 |
| abstract_inverted_index.detection | 25, 100 |
| abstract_inverted_index.determine | 98 |
| abstract_inverted_index.different | 45 |
| abstract_inverted_index.emissions | 24, 99 |
| abstract_inverted_index.framework | 5, 29, 52, 136 |
| abstract_inverted_index.location; | 96 |
| abstract_inverted_index.locations | 72 |
| abstract_inverted_index.placement | 9 |
| abstract_inverted_index.scenarios | 61 |
| abstract_inverted_index.simulated | 105 |
| abstract_inverted_index.algorithms | 123 |
| abstract_inverted_index.continuous | 11 |
| abstract_inverted_index.infeasible | 162 |
| abstract_inverted_index.locations, | 115 |
| abstract_inverted_index.locations; | 156 |
| abstract_inverted_index.monitoring | 12 |
| abstract_inverted_index.objectives | 46 |
| abstract_inverted_index.placement. | 49 |
| abstract_inverted_index.real-world | 192 |
| abstract_inverted_index.showcasing | 190 |
| abstract_inverted_index.successful | 178 |
| abstract_inverted_index.application | 139, 179 |
| abstract_inverted_index.demonstrate | 129 |
| abstract_inverted_index.efficiency. | 26 |
| abstract_inverted_index.illustrates | 176 |
| abstract_inverted_index.programming | 170 |
| abstract_inverted_index.constraints; | 82 |
| abstract_inverted_index.information; | 67 |
| abstract_inverted_index.optimization | 51 |
| abstract_inverted_index.practicality | 131 |
| abstract_inverted_index.Additionally, | 172 |
| abstract_inverted_index.applicability | 193 |
| abstract_inverted_index.consideration | 74 |
| abstract_inverted_index.effectiveness | 133 |
| abstract_inverted_index.formulations. | 171 |
| abstract_inverted_index.mixed-integer | 168 |
| abstract_inverted_index.optimization. | 127 |
| abstract_inverted_index.site-specific | 63, 81, 104 |
| abstract_inverted_index.substantially | 30 |
| abstract_inverted_index.concentrations | 86 |
| abstract_inverted_index.effectiveness. | 195 |
| abstract_inverted_index.computationally | 161 |
| abstract_inverted_index.concentrations; | 106 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.4377711 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |