Environmental Management, Cost Management, and Asset Management for High-Volume Oil Field Waste Injection Projects
Bibliographic record
Abstract
Environmental Management, Cost Management, and Asset Management for High-Volume Oil Field Waste Injection Projects Michael Bruno; Michael Bruno Terralog Technologies Search for other works by this author on: This Site Google Scholar Alex Reed; Alex Reed Terralog Technologies Search for other works by this author on: This Site Google Scholar Susanne Olmstead Susanne Olmstead Terralog Technologies Search for other works by this author on: This Site Google Scholar Paper presented at the IADC/SPE Drilling Conference, New Orleans, Louisiana, February 2000. Paper Number: SPE-59119-MS https://doi.org/10.2118/59119-MS Published: February 23 2000 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Bruno, Michael, Reed, Alex, and Susanne Olmstead. "Environmental Management, Cost Management, and Asset Management for High-Volume Oil Field Waste Injection Projects." Paper presented at the IADC/SPE Drilling Conference, New Orleans, Louisiana, February 2000. doi: https://doi.org/10.2118/59119-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE/IADC Drilling Conference and Exhibition Search Advanced Search AbstractOngoing exploration and production activity, combined with increased regulatory requirements, are increasing the volume and costs associated with disposal of oil field wastes, including produced oily sands and tank bottoms, drilling mud and cuttings, crude contaminated surface soils, and naturally occurring radioactive materials (NORM). A cost-effective and environmentally sound disposal option is to re-inject waste material into the subsurface into non-productive and/or depleted zones under controlled fracture conditions.High volume injection projects often involve annual injection exceeding several hundred thousand barrels of waste for several years. The critical engineering management goals for such operations are to:Maintain waste containment in the target formation (environmental management);Sustain long-term injectivity with minimum equipment repairs and well work overs (cost management); andMaximize formation storage capacity and well life (asset management).More than five years experience operating, analyzing, and managing large volume waste injection projects in the US and Canada has enabled Terralog to develop specific design, monitoring, and operating strategies to achieve these goals. Target injection formations must be selected with appropriate overlying barrier and absorption zones. Offset well completions must be carefully examined. The injection well completion should be appropriately designed to take into account high formation stresses and potential movement. Continuous monitoring and analysis must be performed to evaluate varying formation properties, injectivity, stress conditions, and fracture orientation and height growth. Finally, through continuous monitoring and analysis of formation response, injection parameters and properties (such as solids concentration, density, flow rate, shut-in time, etc...) can be adjusted in order to maintain containment, reduce operating costs, and optimize long-term injectivity.IntroductionDeep well injection of exploration and production wastes provides significant environmental and economic advantages over traditional landfill disposal for oilfield wastes. These include:Improved protection for surface and groundwater;Little impairment of surface land use;Reduced long-term liability risk to waste generator;Reduced transportation and disposal costs.The use of deep well injection, therefore, has expanded significantly in recent years1–5. For example, large-scale E&P waste injection operations have been ongoing in Canada (Srinivasan et al, 1997), Alaska (Schmidt et al, 1998), California (Hainey et al, 1997), and Louisiana (Baker et al, 1999).Large-volume injection, which may involve several hundred thousand barrels or more of waste material injected annually over several years, must be performed in relatively high porosity sands at fracture conditions. In spite of increased use of this technology, however, the mechanics of massive slurry injection into soft formations remain poorly understood, and there are few guidelines available to industry to optimize and manage this process. In some instances injection zones have filled or pressurized prematurely; well casings have been sheared by excessive formation movement; and in extreme instances waste material has broken out of zone and to the surface.To help improve industry practices, Terralog Technologies is currently engaged in a two-year research project, supported in part by the Canadian and US Departments of Energy, to develop and test improved fracture injection disposal techniques and diagnostic tools. This effort involves extensive field data assembly and analysis, model development, and field verification. Keywords: upstream oil & gas, waste injection project, bruno, formation response, enterprise performance management, drillstem/well testing, operation, injection project, tti 6, disposal Subjects: Hydraulic Fracturing, Formation Evaluation & Management, Drillstem/well testing This content is only available via PDF. 2000. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".