MétaCan
Menu
Back to cohort
Record W2003342886 · doi:10.2118/0406-0098-jpt

New Developments in Steamflood Modeling

2006· article· en· W2003342886 on OpenAlexaboutno aff
Karen Bybee

Bibliographic record

VenueJournal of Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsOil in placeSteam injectionPetroleum engineeringOil sandsPetroleumSteam-assisted gravity drainageReservoir engineeringReservoir simulationGeologyOil fieldEnhanced oil recoveryEnvironmental scienceAsphaltArchaeology

Abstract

fetched live from OpenAlex

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 97719, "New Developments in Steamflood Modeling," by M. Kumar, SPE, C. Satik, SPE, and V. Hoang, SPE, Chevron Energy Technology Co., prepared for the 2005 SPE International Thermal Operations and Heavy Oil Symposium, Calgary, 1–3 November. Using results from fine-scale, multipattern, geostatistical models, the full-length paper reviews key issues related to steamflood modeling. Pattern-element and single-sand models used in many previous studies are not sufficient to explain observed field performance, and larger heterogeneous models give more-realistic recovery predictions. Current computing improvements make larger-scale steamflood modeling viable compared with what was possible earlier, and a realistic steamflood performance is attained when necessary details are included in the model. Introduction Steam injection is the most widely used enhanced-oil-recovery method. Current oil production by steam injection is estimated to be more than 1.1 million BOPD. Most conventional heavy-oil steamflooding projects in California, Canada, Indonesia, and Venezuela employ vertical wells, although use of horizontal producers is growing. On the other hand, extra-heavy oils may require both horizontal injectors and producers, such as in steam-assisted gravity drainage. Oil recovery can exceed 20% of the original oil in place (OOIP) for cyclic steaming and more than 50% OOIP by continuous steam injection. Geologic Models The geologic model used in this study is from portions of the Kern River field, one of the largest oil fields in the U.S. on the basis of OOIP and reserves. The Kern River field is a shallow heavy-oil field 5 miles northeast of Bakersfield, California. The field has been on steam injection since the mid-1960s. Production is from from several distinct sand zones with high permeabilities and porosities deposited in a braided river environment. The sandstones are typically medium- to very coarse-grained, poorly to very poorly sorted, and have little to no detrital clay. The high-quality reservoir sandstones are interbedded with poor-quality sandstones, siltstones, and mudstones, that may be barriers to fluid flow. The individual sand bodies, typically 50 to 100 ft thick, are separated by competent and correlatable shale layers and are steamflooded one at a time. However, some of the shales may not be continuous over the entire project area. In addition, shale continuity varies both areally and vertically. As a result, significant fluid migration can occur between sands, making reservoir management and analysis more challenging. The Kern River field properties of low reservoir pressure, high permeability, and high oil saturations are all favorable for steamflooding. Flow Simulation Model Input Parameters. An average sand porosity of 32% was used in the study. Average permeability was approximately 2,500 md. Vertical permeability was considered to be one-half the horizontal permeability. Initial reservoir temperature and pressure were 90°F and 260 psia, respectively. Initial oil saturation was approximately 50%, and initial gas saturation was 0% in the oil zone. Crude gravity was 14°API and its molecular weight was 400. Dead-oil viscosities range from 4,749 cp at 90°F to 3.6 cp at 400°F. Steam quality at the sandface was 70%. Measured relative permeability values were used. Endpoint saturations and relative permeabilities were considered to be independent of temperature. Three-phase oil relative permeabilities were calculated by use of linear interpolation.

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 score0.255
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Petroleum TechnologySame topicReservoir Engineering and Simulation MethodsFrench-language works237,207