Characterization of Reservoir Qualityin Tight Rocks using Drill Cuttings: Examples from the Montney Formation Alberta, Canada
Bibliographic record
Abstract
Abstract Identification of petrophysical and geomechanical "sweet spots" along multi-fractured horizontal wells (MFHWs)is an important step in the optimization of hydraulic fracture treatments in unconventional reservoirs. However, drill cuttings, which are usually the only reservoir samples available from MFHWs, are not suitable for routine laboratory-based measurement of permeability and rock mechanical properties (e.g. unconfined compressive strength; UCS)due in part to the generally small masses collected (<5 g) and cuttings size distributions. Focusing on prolific tight oil and liquid-rich gas reservoirs within the Montney Formation in Western Canada, the primary objectives of the current study are to 1) characterize reservoir quality –in particular matrix permeability/diffusivity –along selected laterals using drill cuttings, 2) identify the influence of drill cuttings' particle size on a variety of petrophysical properties including pore volume, surface area, pore size distribution and matrix permeability/diffusivity, 3) examine key drilling controls on the "quality" (i.e. particle size distribution) of drill cuttings and 4) investigate the relationship between the quality of drill cuttings and drilling-derived UCS data. For a diverse suite of drill cuttings samples obtained along two MFHWs, 1) particle size distributions are examined after sieving/weighting of drill cuttings into a series of standard mesh sizes and 2) elemental composition, pore volume, surface area, pore size distribution andmatrix permeability/diffusivity are quantified using particles with two different mesh sizes (i.e. 20-35 mesh size: 0.5 mm - 0.84 mm; 35-60 mesh size: 0.25 mm - 0.5 mm). The methods used for characterization of eachmesh size are helium pycnometry (grain density); X-ray fluorescence (XRF; elemental composition), low-pressure gas (N2) adsorption (LPA) (pore volume, surface area, pore size distribution), rate-of-adsorption (ROA) N2analysis and crushed-rock gas (N2) permeability. The drilling-derived UCS data are estimatedalong the same laterals using previously-derived rate of penetration (ROP) models. For the 20-35 and 35-60 mesh sizes, the early-time apparent gas (N2) permeability values obtained from the ROA analysis are similar (within the experimental error margin), suggesting that drill cuttings withinthe 35-60 mesh size may be usedfor characterizing reservoir quality (as inferred from permeability). This finding is of particular importance when there is a greater amount of 35-60 mesh size samples compared to 20-35 samples. Experimental observations indicate that there are significant relationships between drilling parameters (i.e. drill bit type, etc.) and particle size distributions of drill cuttings. The hybrid and rollercone bits generate higher quality drill cuttings compared to PDC (Polycrystalline Diamond Compact) bits. However, the effect of enhanced hydraulic energy at the bit for generating higherquality drill cuttings is more pronounced for PDC bits compared to the rollercone and hybrid bits. In addition, well intervals with higher rock strength (i.e. drilling-derived UCS values > 100 MPa) are more likely to generate higher quality drill cuttings. There are major uncertainties associated with identifying an optimal development strategy for horizontal drilling within the Montney, due to the large thickness of the targeted vertical intervals and substantial heterogeneity observed along the laterals. In this study, through the application of multiple non-destructive analysis techniques toa diverse suite of drill cuttings samples, variations in pore structure and fluid flow characteristics of the Montney are characterized along selected laterals. Demonstrated application of this integrated workflow will be of interest to Montney operators who aim to optimize stimulation treatments through identification of petrophysical and geomechanical "sweetspots" along horizontal laterals.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".