Bibliographic record
Abstract
Abstract A tight gas reservoir is commonly defined as a reservoir having less than 0.1 milliDarcies permeability. Because of the very low permeability, hydraulic fracturing is usually carried out in efforts to establish commercial production. There are several basic concepts and field cases of different well tests in tight gas reservoirs in the literature. In this paper, we gather information and provide a guide to some of the most important tests. Generally because of low permeability, a well will not flow initially at measurable rates and conventional well testing cannot be applied. We review procedures for design of pre- and postfracture tests in single and dual porosity reservoirs. The prefracture test permits estimating preliminary values of reservoir permeability and initial pressure. The post-fracture test provides data for estimating fracture half length and conductivity. We also review the application of convolution/deconvolution methods to analyze well tests with significant wellbore storage. Because of economic and environmental reasons, short duration procedures are preferred. However, although effective in many instances, these methods also have their own limitations. Introduction Unconventional reservoirs (tight gas, coal bed methane, shales gas and gas hydrates) will be an important pat of the global energy mix for decades to come. Large reserves, long-term potential, costs and gas prices and some other factors account for the great influence of these resources on the future of energy. There is no formal definition for "tight gas." A commonly used definition, describes tight gas reservoirs as those having permeabilities smaller than 0.1 milliDarcies. Well testing is generally done as an aid to estimate gas in-place and recoverable volumes. Initial pressure (pi) is a critical parameter not only for estimating gas in-place, but also for determining how much field development is required and whether or not the field is overdeveloped. In addition to pi, well testing provides an estimate of permeability and skin. A problem associated with well testing in tight gas sands is that usually long times are required to reach radial flow, due to their extremely low permeabilities. Therefore, conventional well tests cannot be applied to these reservoirs. Because of initial uneconomic rates, fracturing is usually required. Lee(2) has suggested procedures for pre- and post-fracture tests design. In order to have measurable gas rates for pre-frac testing, often a breakdown with acid, KCl water or N2 is necessary.
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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 | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".