Dataset Information

Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells.

ABSTRACT: This article contains the dataset on the failure frequencies of the barrier and mechanical plugs in place within the hydrocarbon-containing wellbore during plugging and abandonment operation. The interpretation and application of this data can be found in the research article ("https://doi.org/10.1016/j.psep.2019.09.015" Babaleye et al., 2019). These datasets were collected through a comprehensive hazard identification technique workshop involving 10 engineers and academics with considerable years of field experience. The data were collected based on how likely it is for each causation to occur and these likelihoods are ranked from 1 to 10. The process is experience-driven and is complemented by a 1-10 rating of the duration of leak of hydrocarbon before remediation, should the leak reach the mudline. The ranked data was a representative of raw failure data (failure rate or mean time to failure (MTTF)) for each causation and are coded in MATLAB using gamma distribution based on hierarchical Bayesian analysis. The dataset offers unique opportunity for reuse due to its accessibility and discreteness.

SUBMITTER: Babaleye A

PROVIDER: S-EPMC7371746 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells.

Babaleye Ahmed A Kurt Rafet Emek RE Khan Faisal F

Data in brief 20200705

This article contains the dataset on the failure frequencies of the barrier and mechanical plugs in place within the hydrocarbon-containing wellbore during plugging and abandonment operation. The interpretation and application of this data can be found in the research article ("https://doi.org/10.1016/j.psep.2019.09.015" Babaleye et al., 2019). These datasets were collected through a comprehensive hazard identification technique workshop involving 10 engineers and academics with considerable yea ...[more]

PMID: 32715038

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Project description:Orphaned oil and gas wells are unplugged nonproducing wells with no solvent owner of record to plug and mitigate them, such that the responsibility often falls on government agencies and the general public. Unplugged wells pose risks to the environment, climate, and human health. To develop a national framework to quantify the environmental benefits of plugging and optimize mitigation, we analyze oil and gas well data from state agencies across the United States to estimate the number of documented orphaned wells over time and evaluate their attributes. We find at least 81,857 documented orphaned wells as of September 2021 and 123,318 as of April 2022, representing 2% and 3%, respectively, of all estimated abandoned wells in the United States. We identify at least 20,286 potentially documented orphaned wells as of September 2021 (0.5% of all estimated abandoned wells in the country), of which 8% became documented orphaned wells as of April 2022. We estimate annual methane emissions to average 0.016 ± 0.001 MMt of CH4 for the 123,318 documented orphaned wells as of April 2022, corresponding to 5-6% of the total methane emissions estimated by the U.S. EPA for all abandoned wells. Although well type (i.e., oil vs gas) is generally available (83% of the 81,857 documented orphaned wells as of September 2021), only 49% and 16% of the wells have information on depth and last production date, respectively. Overall, documented orphaned wells and their attributes, including location, well type, depth, and last production date, require additional characterization and studies to constrain the uncertainties. Nevertheless, our identification and analysis of documented orphaned wells represent the first steps toward characterizing the full set of wells eligible to be plugged and remediated with the federal funding available in the U.S. via the Infrastructure Investment and Jobs Act. Our results can also be useful for the management of the hundreds of thousands, potentially a million, undocumented orphaned wells likely to exist across the nation.

Project description:Over the last decade, metagenomic studies have revealed the impact of oil production on the microbial ecology of petroleum reservoirs. However, despite their fundamental roles in bioremediation of hydrocarbons, biocorrosion, biofouling and hydrogen sulfide production, oil field and oil production infrastructure microbiomes are poorly explored. Understanding of microbial activities within oil production facilities is therefore crucial for environmental risk mitigation, most notably during decommissioning. The analysis of the planktonic microbial community from the aqueous phase of a subsea oil-storage structure was conducted. This concrete structure was part of the production platform of the Brent oil field (North Sea), which is currently undergoing decommissioning. Quantification and sequencing of microbial 16S rRNA genes, metagenomic analysis and reconstruction of metagenome assembled genomes (MAGs) revealed a unique microbiome, strongly dominated by organisms related to Dethiosulfatibacter and Cloacimonadetes. Consistent with the hydrocarbon content in the aqueous phase of the structure, a strong potential for degradation of low molecular weight aromatic hydrocarbons was apparent in the microbial community. These degradation pathways were associated with taxonomically diverse microorganisms, including the predominant Dethiosulfatibacter and Cloacimonadetes lineages, expanding the list of potential hydrocarbon degraders. Genes associated with direct and indirect interspecies exchanges (multiheme type-C cytochromes, hydrogenases and formate/acetate metabolism) were widespread in the community, suggesting potential syntrophic hydrocarbon degradation processes in the system. Our results illustrate the importance of genomic data for informing decommissioning strategies in marine environments and reveal that hydrocarbon-degrading community composition and metabolisms in man-made marine structures might differ markedly from natural hydrocarbon-rich marine environments.

Dataset Information

Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells.

Publications

Dataset for estimating occurrence probability of causations for plugged, abandoned and decommissioned oil and gas wells.

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