Non-Destructive Techniques to Determine the Effective Stress Coefficient of Sandstone Formations
Bibliographic record
Abstract
Abstract The concept of effective stress coefficient, "n," is critical for the study of stress and pressure-dependent behaviour of rocks. This parameter is used to scale the pore fluid pressure for the computation of effective stress and impacts on the accuracy of pore pressure and saturation predictions in reservoirs. However, "n" is relatively unknown and difficult to estimate and, in many cases, is often incorrectly assumed to be equal to one. We present a general review of "n" and give a theoretical proof that "n" is less than one for porous rocks. We also introduce a laboratory methodology to measure the value of "n" employing ultrasonic P-wave velocity (Vp) and attenuation quality factor (Qp). We then confirm the value of "n' experimentally by using this laboratory method to estimate "n" of quartz sandstone. We compare our experimental value of "n" to both theoretical and practical results obtained from other literature that used different estimation methodology. We argue from our experimental results that:"n" is not one but varies from zero to one;there is no single value of "n" for a particular reservoir rock;"n" depends on internal factors (porosity and pore geometry) and external factors (pore pressure and confining pressure) of the rock;velocity derived "n" and quality factor derived "n" are slightly different for the same rock; and,for the quartz sandstone used in this experiment, the velocity derived "n" is smaller and also less sensitive to changes in pressure than quality factor derived "n." Introduction Most of the pioneering work on what is now known as effective stress coefficient was done by Terzaghi(1), who showed that most rocks are porous to some degree due to the pore spaces and micro cracks within them. The effect of these pores on the strength of rocks has widely been documented(1–5). A rock with a few or without pores is considerably stronger than porous ones since pore spaces are unsupported within the rock. With the presence of unsupported spaces, the intact rock between the pores has to take larger loads to sustain an overall applied stress. This important phenomenon has a direct bearing on the effective stress of the rock (Figure 1). Thus, the effective stress (Pe) is not directly equal to the differential pressure (Pd). Many writers(4–12) have highlighted the problem caused by this phenomenon and the resulting uncertainties associated with the estimated pressures and saturation in reservoirs. This uncertainty is increasingly significant for reservoir engineering due to the expanding use of seismic techniques for remote estimation of abnormal pore pressures for drill planning and for monitoring reservoir pore pressure changes during production. For example, Carcione and Helle(13) applied a new technique for estimating reservoir pressures from seismic data to an overpressured gas field in the Norwegian North Sea and concluded that once a reliable velocity field was determined for the reservoir formation, the most important part of the prediction process was the determination of the effective stress coefficients and related dry-rock moduli.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".