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Record W2094094241 · doi:10.1115/imece2005-80460

Evolution of Oil and Gas Waste/Soil Remediation Regulations

2005· article· en· W2094094241 on OpenAlexaboutno aff
Lloyd E. Deuel, George H. Holliday

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsLimitingWaste managementEnvironmental remediationPetroleumPetroleum industryJurisdictionResource Conservation and Recovery ActHazardous wasteEnvironmental scienceEnvironmental protectionEngineeringEnvironmental engineeringLawPolitical scienceChemistry

Abstract

fetched live from OpenAlex

The meaningful United States regulation of onshore oil and gas field waste/soil commenced in the mid 1980’s in response to a series of state, federal, industry and international initiatives. Most initiatives centered on the design, construction and operation of earthen pits used in the exploration and production of oil and gas (E&P). Prior to this time, earthen pits were constructed as needed by the operator and used in all phases of E&P activity. Chief concerns of the regulators were focused on what had gone into pits historically, what was going into them currently and was the E&P exemption excluding high volume E&P wastes from the Resource Conservation and Recovery Act (RCRA) regulations justified. Several investigations, including the comprehensive field study by the Environmental Protection Agency in 1987, determined E&P wastes are ostensibly non-hazardous. EPA concluded regulation of E&P wastes under RCRA Subtitle C was not necessary. To this day there is no U. S. federal regulatory program with exclusive jurisdiction over exempt E&P wastes. Other studies, primarily industry and academic, focusing on land limiting constituents, management practices and pit closure strategies revealed sodium salts and petroleum hydrocarbon in the form of diesel range organics were the primary limiting constituents. One state, Louisiana, adopted the technical aspects of these studies and developed a comprehensive regulation known as Statewide Order 29-B, which was based on the concept of limiting constituents and defined post closure performance standards. These standards limited salinity, sodicity, total metals and total petroleum hydrocarbon (oil & grease) with values varying with respect to landform, land use and closure technique. Other states have adopted some of the concepts and criteria advanced under 29-B but none are as comprehensive. Obviously there is a need to control what goes into pits and how pits should be closed. The industry would best be served by adopting the concepts and standards set forth in the Louisiana 29-B regulation. A few of the provisions could be changed to make it more palatable to industry without sacrificing the protection afforded human and animal health, safety and the environment. Internationally, particularly countries in South America embraced USEPA protocol for testing characteristically hazardous wastes, but 1) without the framework to handle the relatively large volume of non-hazardous E&P waste generated and 2) no regulations or protocols for on-site waste management. Several operators, although partners with state owned oil companies, on their own volition, applied the concepts and standards under Louisiana’s 29-B to rainforests in South America and rice paddies in Indonesia. Canada and European oil and gas producing countries have developed stringent standards not based on science, which favor costly treatment technologies. Generally, these countries prohibit cost effective on-site waste management and closure techniques. This paper traces the evolution of waste/soil remediation within the United States and internationally. We trace the progress as a function of time; the impetus for regulation; and probable future controls.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.197
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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