Characteristics of Canister Core Desorption Gas from Unconventional Reservoirs and Applications to Improve Assessment of Hydrocarbons-in-Place
Bibliographic record
Abstract
Canister core desorption has been successfully applied to coal-bed methane evaluation and exploitation as the technique eliminates the need for time-consuming down-hole fluid retrieval through flow testing. The technique has also been used for the evaluation and exploration of early-stage tight and shale gas reservoirs in recent years, although its success and applicability are poorly understood. In this study, we analyzed a comprehensive canister desorption data set on 230 core samples from nine exploration wells drilled into the Montney Formation in northeastern British Columbia part of the Western Canada Sedimentary Basin (WCSB). The purpose of the study was to illustrate the desorption characteristics of tight rocks and the relationship to reservoir properties and operational parameters. Based on the measured core properties (e.g., porosity, fluid saturation, permeability, total organic carbon (TOC) content, and adsorption isotherms) of canister samples and adjacent core samples, non-isothermal gas transport in cores was modeled to quantify the lost gas during core recovery and lost gas time at the surface. Gas volumes were measured and subsampled by canister desorption tests. The results show that the gas contents measured by on-site canister desorption only accounts for a minor (but significant) portion (about 2 to 25%) of the total gas-in-place in the Montney Formation cores, with the lower percentages being associated with samples of better reservoir qualities (e.g., higher porosity). Over 60–90% (mainly free gas) of the total gas-in-place can be lost during core recovery, and up to 10% can be lost at surface, prior to canister desorption. The measured canister desorption gas is mainly from adsorbed gas, and hence shows strong positive correlation to TOC content. The study shows that the current canister desorption test method severely underestimates in-situ gas content because it fails to correctly estimate the total lost gas content, limiting the successful application of the desorption technique. Nevertheless, the bulk properties and molecular compositions of the desorption gases are strongly correlated to those of the gases produced in the same area, exhibiting distinctive gas composition profiles throughout core desorption for different reservoir types or thermal maturity, and thus can provide invaluable information for the initial evaluation of unconventional plays. A workflow of EOS-based PVT property and compositional modeling is proposed to integrate the core desorption gas test results with core analysis data and mud gas and/or produced gas data for improved characterization of in situ reservoir fluids, and hence, better assessments of hydrocarbons-in-place and evaluations of tight and shale reservoirs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".