A Material Balance Equation for Stress-Sensitive Shale Gas Reservoirs Considering the Contribution of Free, Adsorbed and Dissolved Gas
Bibliographic record
Abstract
Abstract Unconventional shale gas reservoirs around the world have been proven to store gigantic volumes of natural gas. It has been demonstrated with both laboratory and mathematical work that these reservoirs can be represented by a quintuple porosity formulation plus an additional storage mechanism provided by dissolved gas in kerogen. All these storage mechanisms must be considered for estimation of original gas in place (OGIP). Otherwise pessimistic values of OGIP and recoveries will be obtained by ignoring any of these mechanisms. This paper presents a new easy-to-use Material Balance Equation (MBE) for shale gas reservoirs that considers the contribution of free, adsorbed and dissolved gas and their effects on cumulative gas production. Furthermore the proposed MBE takes into account the stress-dependency of permeability and porosity as the reservoir is depleted. Aguilera (2008) formulated a MBE to account for the effect of fracture compressibility on OGIP determination in stress-sensitive naturally fractured reservoirs. Cabrapan et al. (2014) extended the method by incorporating adsorption in shale gas reservoirs. The authors used the Langmuir Adsorption theory for quantifying the adsorbed gas volume as a function of average reservoir pressure. In this paper, the method is further extended to include the effect of production by diffusion of dissolved gas from kerogen. The volume of dissolved gas depends on the total fractional volume of kerogen in shale and the methane concentration in the kerogen body, which is in turn a function of pressure and temperature, as proposed by Swami et al. (2013). Results are presented as crossplots of P/Z (pressure/gas deviation factor) vs. Gp (cumulative gas production), Gp vs. time and gas rate vs. time. The plots allow detecting four stages of production in a shale gas reservoir: 1) production of free gas from fractures and organic porosity, 2) production of free gas from the inorganic matrix when fractures start closing, 3) production by desorption from the organic material and 4) production by diffusion of dissolved gas. The same trends have been observed in Devonian Shales of the Appalachian Basin where long production histories are available. It is concluded that dissolved gas is not only an additional storage mechanism but it also provides an important pressure and production contribution in shale reservoirs. The new consideration introduced in the MBE proposed in this paper is of importance because although diffusion from kerogen in shale gas reservoirs is by nature a slow process, it provides long term production rates with relatively small declines. To the best of our knowledge, an analytical MBE that includes simultaneously stress-dependent porosity and permeability, free gas, adsorbed gas and dissolved gas has not been published previously in the literature.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".