Bibliographic record
Abstract
Summary Flowing-material-balance (FMB) analysis is a practical method for determining original hydrocarbon volumes in place. It is attractive because it enables performing material-balance calculations without shutting in wells to obtain estimates of reservoir pressure. However, with some exceptions, its application is limited to single-phase oil and/or gas reservoirs over limited pressure ranges during depletion. In unconventional reservoirs, reservoir and/or production complexities may further restrict FMB use. Among these complexities are significant production/injection of water, production resulting in higher gas/oil ratios (GORs) and pressure drawdowns, geomechanical effects, and multiwell-production effects. As a result, application of the conventional FMB to unconventional reservoirs may lead to significant errors in hydrocarbons-in-place estimation. This paper first discusses the application of conventional FMB to the analysis of single-phase or multiphase flow in single or multiwell scenarios, and then provides a new, comprehensive version of the FMB to address the previously mentioned complications. For the new FMB, pseudopressure is used to account for two-phase oil/gas flow. In addition, by use of a general material-balance equation, water production/injection and multiwell effects are included in the analysis. The new FMB-analysis approach is validated by comparing results with numerical simulation of multifractured horizontal wells (MFHWs). These comparisons demonstrate that, not only gas production, but also water production/injection can have a significant effect on the calculated original-in-place hydrocarbon volumes. The new FMB-analysis approach provided herein successfully accounts for all flowing phases in the reservoir, and is demonstrated to be applicable for multiwell scenarios. The methodology presented in this paper maintains the simplicity of FMB, yet accounts for multiphase flow and multiwell complications. The developed FMB and the presented approach can be used by reservoir engineers to reasonably determine the original volumes of hydrocarbons in place in both conventional and unconventional reservoirs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".