MétaCan
Menu
Back to cohort
Record W4242339750 · doi:10.2523/75667-ms

Well Performance Prediction of a Well Experiencing Changes in Completion

2002· article· en· W4242339750 on OpenAlex
T. Marhaendrajana, J. Desroches

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of SPE Gas Technology Symposium · 2002
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCitationComputer scienceDownloadProduction (economics)Information retrievalLibrary scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Well Performance Prediction of a Well Experiencing Changes in Completion T. Marhaendrajana; T. Marhaendrajana Schlumberger Oilfield Services Search for other works by this author on: This Site Google Scholar J. Desroches J. Desroches Schlumberger Oilfield Services Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, April 2002. Paper Number: SPE-75667-MS https://doi.org/10.2118/75667-MS Published: April 30 2002 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Marhaendrajana, T., and J. Desroches. "Well Performance Prediction of a Well Experiencing Changes in Completion." Paper presented at the SPE Gas Technology Symposium, Calgary, Alberta, Canada, April 2002. doi: https://doi.org/10.2118/75667-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Unconventional Resources Conference / Gas Technology Symposium Search Advanced Search AbstractThis paper presents a new semi-analytical method to predict the production performance of a well stimulated by acid or hydraulic fracture treatment. The new method considers the production history before stimulation, in contrast to current analytical methods that ignore the production history of the "old" well. The initial condition of the "new" well is based upon an "assumed stabilized condition" of the old well.The superposition technique has been extensively used in the literature to model production history (i.e., variable flow rate and variable bottomhole pressure history) and predict well performance. There has not been a detailed study using analytical or semi-analytical solutions that includes the change in well completion (well model change) and that investigates the influence of the production history of the unstimulated well on the well performance prediction of the "stimulated" well. This paper addresses both issues.The semi-analytical method presented here considers changes in well completion, which are becoming more frequent as recompletions become more common. We present validations of this approach using a numerical reservoir simulator for oil and gas reservoirs in which the wells are recompleted with a hydraulic fracture treatment after some initial production.IntroductionThe effect of production history on the analysis of well performance data has been investigated by many authors for years. Horner1 provides a method for treating the variable-rate case based on the application of the superposition theorem. This method requires knowledge of production history as a function of time. Van Everdingen and Meyer2 also presented the use of the general superposition for analyzing pressure buildup data preceded by variable production rate history. More applications of the van Everdingen and Meyer method can be found in Whitson and Sognesand.3 Odeh and Jones4 use a superposition method based on the logarithmic solution, which should be used only during a radial flow regime.The drawback of using full superposition is that the computation is lengthy when there are many significant rate changes. In addition, the complete rate history may not always be available.A simple method was proposed by Horner1 to obtain an equivalent producing time by dividing the total cumulative production by the last established rate, which is later known as material balance time. Although Horner did not present a theoretical justification for this method, it is still used by the majority of reservoir analysts today.The theoretical justification of the material balance time was presented by Blasingame et al.5 The authors showed that the material balance time concept is rigorously accurate for "stabilized flow" or a pseudosteady-state-like flow regime. The lower bound for the start of the stabilized flow is the time to reach pseudosteady state for a constant rate production. This means that any new transient introduced by large changes in rate after this time will eventually die and that stabilized flow will dominate.To our knowledge, the effect of production history has not been investigated for a case where the well completion changes (i.e., the well model changes). This paper examines this phenomenon and provides a semi-analytical method for predicting the well performance under this condition by implementing the material balance time approach. The primary application of this method is the evaluation of the performance of a proposed recompletion.Approximate Solution for a Well Experiencing Changes in CompletionFig. 1 is an illustration of a well experiencing changes in completion. The well model change may represent a conventional vertical well that is hydraulically fractured or otherwise recompleted. Well model 1 refers to the unstimulated well that has been produced up to t = t2, with rates q1 and q2. At t = t2, the well is stimulated and is produced with rate q3. In a case where the well is not stimulated (well models are the same), this problem reduces to a variable-rate problem. Keywords: production control, completion, fluid dynamics, unstimulated well, gas case, permeability, production monitoring, bottomhole, semi-analytical solution, well performance prediction Subjects: Well & Reservoir Surveillance and Monitoring, Reservoir Fluid Dynamics, Formation Evaluation & Management, Flow in porous media, Drillstem/well testing, Well performance, inflow performance This content is only available via PDF. 2002. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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