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Record W4242842720 · doi:10.2118/2003-208

Design and Performance of a Water Disposal Well Stimulation Treatment in a High Porosity and Permeability Sand

2003· article· en· W4242842720 on OpenAlexaff
T.G. Harding, J. Varner, L.A. Flexhaug, D.B. Bennion

Bibliographic record

VenueCanadian International Petroleum Conference · 2003
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsNexen (Canada)
FundersConsolidated Contractors Company
KeywordsPermeability (electromagnetism)PorosityGeologyEnvironmental scienceGeotechnical engineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Injectivity problems associated with produced water disposal have been on going in the Masila project in Yemen. Disposal wells experience an immediate low injectivity upon commencement of injection as compared to the productivity measured during pumping clean up of the wells. It has been hypothesized that this behaviour, referred to as the check-valve effect, is caused mainly by mobile formation fines in the near-well vicinity. Injectivity often declines further because of plugging by impurities in the disposal water. Laboratory and field work has been done to test several methods of improving water disposal well performance including the application of horizontal wells and proppant fracture stimulation of vertical wells. Another technique tried in the field was a stimulation treatment involving HCl/HF acid followed by a thin-film polymer. The intent of the treatment was to destroy potentially mobile formation fines in the near wellbore area and then to stabilize those that remained in an attempt to reduce the check-valve effect. The acid and polymer treatment was developed through laboratory core testing and was employed on a newly drilled water disposal well. The procedures and results of the laboratory work are described along with the design and implementation of the stimulation treatment. The injection performance of the well is examined relative to other disposal wells in the field. Initial results of the stimulation treatment were disappointing but the well has improved over time to become a moderately good injector. However, the results of the test have not provided enough encouragement to date to warrant further work in the field. Introduction The disposal of produced water in the Masila project in the Republic of Yemen has been the subject of a number of earlier papers1–3. Field water production has been rising steadily in recent years due to the strong aquifer support in the Upper Qishn reservoir section. These reservoirs are high porosity and permeability and exhibit superior production characteristics. Current oil and water production levels are 230,000 BOPD and 1,250,000 BWPD, respectively. All of the produced water is disposed of through reinjection into the producing formations. Injectivity problems continue due to the nature of the formations and the quality of the disposal water. Details of the injectivity problems and investigations as to their causes have been discussed previously1. The performance of four horizontal disposal wells and the results of four proppant fracture stimulated vertical disposal wells have been presented2. In addition, a study has been published of continuous high-pressure injection above formation parting pressure as an aid to injectivity3. Laboratory and field trials have indicated that injectivity problems are caused by a combination of native reservoir fines migration, formation plugging by injected solids and oil, and the formation of calcite scale downhole. Several authors have discussed such injectivity problems and their causes in some detail4–8. In addition to the use of horizontal wells and proppant fractured stimulated vertical wells, a field trial was conducted of an acid stimulation technique designed in the laboratory. This technique was intended to first destroy reservoir fines in the near wellbore area and then to stabilize those that remained.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.995

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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 designSimulation or modeling
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

Citations3
Published2003
Admission routes1
Has abstractyes

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