MétaCan
Menu
Back to cohort
Record W2055120513 · doi:10.2118/00-11-01

Application of Heat Treatment to Enhance Permeability in Tight Gas Reservoirs

2000· article· en· W2055120513 on OpenAlexfundno aff
A.K.M. Jamaluddin, D.B. Bennion, F.B. Thomas, T. Ma

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
FundersKing Fahd University of Petroleum and MineralsUniversity of Calgary
KeywordsPetroleum engineeringSwellingTight gasDrilling fluidPermeability (electromagnetism)WellboreDrillingClay mineralsGeologyMaterials scienceHydraulic fracturingMineralogyComposite materialChemistryMetallurgy

Abstract

fetched live from OpenAlex

Abstract During the drilling and completion phases, the primary mechanisms of near-wellbore formation damage can be attributed to the following factors:pore throat constriction caused by clay swelling, deflocculating due to incompatible fluids or clay migration;water blocking resulting in a reduction in relative permeability to hydrocarbons;plugging with drill solids and mud products; andloading of the reservoir with drilling or completion fluids. In tight reservoirs, phase trapping and water-blocking are believed to be the primary causes of near-wellbore formation damage, resulting in very low productivity. Clay swelling and phase trapping in tight gas reservoirs during drilling and completion have long been identified as major problems. Preventive measures have been discussed in literature; however, prevention of clay damage and phase trapping is not always possible or effective and curative measures may then become necessary. Several curative methods have been attempted and presented in literature with mixed success. A formation heat treatment (FHT) process has been developed in the last four years and initial field test results showed promise. The primary mechanisms of the FHT process are to vaporize blocked water, dehydrate clay-bound water, destroy clay lattices and possibly create micro fractures due to thermally induced stresses, with the objective of removing near-wellbore drilling induced skin damage. The objective of this laboratory study was to evaluate the feasibility of applying the formation heat treatment process on cores taken from a tight gas reservoir. The results indicate that the FHT stimulation at 649 ° C resulted in a 210% improvement in permeability from the baseline undamaged value and 675% improvement from the damaged (water-trapped) value. The post FHT waterflooding of the core still showed 50% improvement in permeability from the baseline value and 275% more than the watertrapped value. Laboratory results along with the field logistics are presented in this paper. Introduction Formation damage can occur at any time during the history of a well-from the initial drilling and completion of the wellbore through to the depletion of the reservoir during production. Operations such as drilling, completion, workovers, and stimulation, which expose the formation to a foreign fluid, may cause formation damage because of adverse wellbore-fluid to formation interactions. Such damage is usually severe in horizontal wells, because of the longer exposure of the wellbore to the offending fluids(1 – 7). During the drilling and completion phases, the primary mechanisms of near-wellbore formation damage can be explained by the following factors:Pore throat constriction, caused either by clay swelling due to incompatible fluids or by clay migration,Water blocking due to reduction in relative permeability to hydrocarbon,Plugging with drill solids and mud products,Loading of the reservoir with drilling or completion fluids. In tight gas reservoirs, formation damage, due to phase trapping and water blocking, has long been identified as a major problem. Preventive measures against this type of damage are not always possible or effective, and curative measures may then become necessary. Several curative methods have been attempted and presented in the literature(8–15).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.216
Teacher spread0.212 · 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

Citations26
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Canadian Petroleum TechnologySame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207