Use of Pressure- and Rate-Transient Techniques for Analyzing Core Permeability Tests for Unconventional Reservoirs
Bibliographic record
Abstract
Abstract The permeability of unconventional gas/oil reservoirs is a critical control on economic viability of unconventional plays, yet its determination, particularly in ultra-low permeability shale reservoirs, remains a challenge. Some of the difficulties in obtaining accurate permeability measurements in the lab include: recreating in-situ stress and fluid saturation conditions; establishing the appropriate sample size for measurement; correcting for sorption of gases on kerogen and clays; accounting for non-Darcy flow (slippage and diffusion); among many others. Unsteady-state measurements are most popular for establishing permeability in ultra-tight rock; both pressure-decay and pulse-decay decay techniques have been used. Analysis methods for these techniques have been established, but there remain some questions about whether these analysis methods are optimal for establishing permeability. In this work, we investigate the use of pressure- and rate-transient analysis (PTA/RTA) methods to analyze data obtained from a new core plug analysis procedure, designed specifically to extract information (permeability and pore volume) from ultra-low permeability reservoir samples (core plugs). The new analysis procedure calls for analyzing the rate and/or pressure data analogously to larger-scale well-test/production data. During a core plug production test for example, derivative analysis of rate-normalized pseudo-pressure change is first analyzed to determine flow-regimes. For homogenous samples, linear flow is followed by boundary-dominated flow; for this scenario, permeability can be established by noting the end of linear flow and using the distance of investigation calculation to calculate permeability (knowing core length). Permeability can also be established independently from a linear flow (square-root of time) plot. Pore volume can also be established. Analytical simulation is used to verify estimates of permeability and pore volume from RTA/PTA. Our solutions allow complex unconventional gas reservoir behavior to be incorporated, including corrections for adsorbed gas and non-Darcy flow. Our new methodology is tested using various simulated cases which differ due to: 1) reservoir type (single or dual porosity, homogenous or heterogeneous); 2) matrix permeability; 3) analysis type (post injection/falloff production test, or post-injection falloff); 4) adsorption (compressed gas storage only or compressed + adsorbed gas storage); Darcy or non-Darcy flow. In all cases, reasonable estimates of permeability and pore volume were obtained, provided the appropriate corrections are made. We believe this new technique for analyzing core data, and the proposed core testing procedure, will considerably improve on current techniques for establishing permeability and pore volume of unconventional reservoir samples.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".