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Record W2160711287 · doi:10.2118/04-08-01

Achieving Zero Liquid Discharge in SAGD Heavy Oil Recovery

2004· article· en· W2160711287 on OpenAlexaboutno aff
W.F. Heins, K. Schooley

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsReuseProduced waterBrineWaste managementSteam-assisted gravity drainageWastewaterZero wastePetroleum engineeringEnvironmental scienceSteam injectionConcentratorEngineeringOil sandsAsphaltChemistryMaterials science

Abstract

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Abstract Designing a plant for maximum water recycle and reuse (i.e., zero liquid discharge) is not the mystery it once was. Planning to implement zero liquid discharge right from the start wins faster community acceptance, streamlines the permitting process, eliminates the need for deep well injection or other disposal methods, and minimizes make-up water requirements. Over 100 mechanical zero liquid discharge systems are now in operation worldwide using Ionics RCC Brine Concentrator and Crystallizer technologies, including two SAGD heavy oil recovery projects currently underway in Alberta. Wastewater is converted by the Brine Concentrator to extremely pure distilled water for reuse in the steam generator or other process applications. The waste from the Brine Concentrator is reduced to dry solids in the Crystallizer, while recovering the remaining wastewater for reuse. This paper will discuss the various applications of Brine Concentrators and Crystallizers as they apply to the treatment of SAGD heavy oil recovery produced water. Specific examples will be used to illustrate the wastewater recycling process and demonstrate how the zero liquid discharge system is integrated into the SAGD heavy oil recovery process. Introduction Traditional Heavy Oil Recovery Process Water treatment is a necessary operation in the heavy oil recovery process. In order to recover heavy oil from certain geologic formations, steam is required to improve the mobility of the oil. Traditionally, "once-through" steam generators have been used to produce 80﹪ quality steam (80﹪ vapour, 20﹪ liquid) for injection into the well to fluidize the heavy oil and allow the oil/water mixture to be pumped to the surface. The oil and water are separated. The oil is recovered as product and the water, referred to as produced water, is de-oiled and treated for reuse in the steam generator. The produced water, which must typically be < 8,000 mg/l of total dissolved solids (TDS) as well as meeting other specific constituent requirements, is typically pre-treated using hot or warm lime softening, a weak acid cation system, and other processes prior to use in the steam generator The SAGD Heavy Oil Process A relatively new heavy oil recovery process, referred to as SAGD (Steam Assisted Gravity Drainage), requires 100﹪ quality steam to be injected into the well (i.e., no liquid water). To produce 100﹪ quality steam using once-through steam generators, aeries of vapour-liquid separators are required to separate the liquid water from the steam. The 100﹪ quality steam is then injected into the well. The separated water is then either disposed of via deep-well injection or, if deep well injection is not possible, the separated water may be taken to Zero Liquid Discharge (ZLD) using a Brine Concentrator and/or a salt Crystallizer. Brine Concentrators and Crystallizers Prior to addressing the details of applying Brine Concentrators and Crystallizers to the SAGD process, a brief history of evaporation and a technical explanation of the Brine Concentration and Crystallization process is presented. Following these technical descriptions, specific examples of Brine Concentration and Crystallization in the SAGD industry are presented.

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 score0.485
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.005
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

Citations31
Published2004
Admission routes1
Has abstractyes

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