Hydrocarbon Saturation From Total Organic Carbon Logs Derived From Inelastic and Capture Nuclear Spectroscopy
Bibliographic record
Abstract
Abstract The accurate determination of formation hydrocarbon or water saturation is an essential step in the petrophysical evaluation of petroleum reservoirs. A novel method has been developed for estimating hydrocarbon saturation directly from a total organic carbon (Corg) log and a porosity log. The method is enabled by the recent development of a pulsed-neutron logging tool that combines inelastic and capture gamma ray spectroscopy measurements to provide a robust and accurate total organic carbon estimate. The method differs from the well-known approach of using carbon-to-oxygen ratios that is most often applied in cased-hole evaluation. The main advantages of this new method are that it does not require knowledge of formation water resistivity, it does not rely on a resistivity model, it does not require an extensive calibration database, and it is largely independent of clay or other lithology effects. Calculations are available to explore uncertainties in the saturation estimates arising from uncertainties in the log inputs. The statistical uncertainty in the estimate of hydrocarbon saturation is as good as 10 saturation units (s.u.) in conventional reservoirs with porosities of 15 p.u. or greater. The method has been applied to the determination of hydrocarbon saturation in a variety of formations, including bitumen-filled dolomite, heavy oil sand, and shaly sands with both open-hole and cased-hole wells. The method works equally well in formations drilled and logged with either oil- or water-based mud. The saturation estimates have been benchmarked against a combination of conventional and new logging approaches (e.g., resistivity, magnetic resonance, and dielectric logs) and core measurements, with generally excellent agreement among independent determinations. Hydrocarbon saturations can be determined accurately using the method in a number of formation types where conventional methods and models for estimating fluid saturation commonly fail, such as freshwater and unknown water salinity in formations under enhanced oil recovery. The case studies demonstrate that a Corg log derived from geochemical spectroscopy logs can be used to obtain reliable estimates of hydrocarbon saturation in a wide range of environmental conditions and formations.
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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".