MétaCan
Menu
Back to cohort
Record W2904904038 · doi:10.2118/193697-ms

Risk Assessment in Sand Control Selection: Introducing a Traffic Light System in Stand-Alone Screen Selection

2018· article· en· W2904904038 on OpenAlex
Mahdi Mahmoudi, Vahidoddin Fattahpour, Arian Velayati, Morteza Roostaei, Mohammad Kyanpour, Ahmad Alkouh, Colby Sutton, Brent Fermaniuk, Alireza Nouri

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSPE International Heavy Oil Conference and Exhibition · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaRGL Reservoir Management
KeywordsSteam-assisted gravity drainagePetroleum engineeringWellboreMultivariate statisticsSelection (genetic algorithm)Flow (mathematics)Oil sandsGeotechnical engineeringEnvironmental scienceEngineeringComputer scienceMathematicsStatisticsMaterials scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Sand control and sand management require a rigorous assessment of several contributing factors including the sand facies variation, fluid composition, near-wellbore velocities, interaction of the sand control with other completion tools and operational practices. A multivariate approach or risk analysis is required to consider the relative role of each parameter in the overall design for reliable and robust sand control. This paper introduces a qualitative risk factor model for this purpose. In this research, a series of Sand Retention Tests (SRT) was conducted, and results were used to formulate a set of design criteria for slotted liners. The proposed criteria specify both the slot width and density for different operational conditions and different classes of Particle Size Distribution (PSD) for the McMurray oil sands. The goal is to provide a qualitative rationale for choosing the best liner design that keeps the produced sand and skin within an acceptable level. The test is performed at several flow rates to account for different operational conditions for Steam Assisted Gravity Drainage (SAGD) and Cyclic Steam Stimulation (CSS) wells. A Traffic Light System (TLS) is adopted for presenting the design criteria in which the red and green colors are used to indicate, respectively, unacceptable and acceptable design concerning sanding and plugging. Yellow color in the TLS is also used to indicate marginal design. Testing results indicate the liner performance is affected by the near-wellbore flow velocities, geochemical composition of the produced water, PSD of the formation sand and fines content, and composition of formation clays. For low near-wellbore velocities and typical produced water composition, conservatively designed narrow slots show a similar performance compared to somewhat wider slots. However, high fluid flow velocities or unfavorable water composition results in excessive plugging of the pore space near the screen leading to significant pressure drops for narrow slots. The new design criteria suggest at low flow rates, slot widths up to three and half times of the mean grain size will result in minimal sand production. At elevated flow rates, however, this range shrinks to somewhere between one and a half to three times the mean grain size. This paper presents novel design criteria for slotted liners using the results of multi-slot coupons in SRT testing, which is deemed to be more realistic compared to the single-slot coupon experiments in the previous tests. The new design criteria consider not only certain points on the PSD curve (e.g., D50 or D70) but also the shape of the PSD curve, water cut, and gas oil ratio and other parameters.

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.

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 score0.190
Threshold uncertainty score0.614

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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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