Characterization of the Giant Chicontepec Tight Oil Paleochannel in Mexico and Integration With Actual Cumulative Oil Production
Bibliographic record
Abstract
Abstract The Chicontepec Paleochannel contains unconventional tight oil shaly sandstone reservoirs also characterized by natural fractures. Chicontepec ranks as a giant reservoir with volumes of Original-Oil-in-Place (OOIP) ranging between 137,300 and 59,000 MMbbls (Guzman, 2019). Although the cumulative oil is significant (440.38 MMbbls) it only represents 0.32 to 0.75% of the OOIP. The objective of this study is developing a new characterization methodology with a view to increase oil recovery from Chicontepec. OOIP in Chicontepec paleochannels was estimated originally at 137,300 MMbbls. Despite several studies using state of the art methodologies, contracting major oil field services companies to test new technologies, and significant investments, the OOIP was decreased recently to 59,000 MMbbls due to lack of any significant success on the implemented projects. This study shows that the key to success is understanding the contribution of natural fractures. This is demonstrated with a new dual porosity petrophysical model for naturally fractured laminar shaly sandstone reservoirs developed in this study. The model assumes that matrix and fractures are in parallel. Laminar shaliness is handled with a parameter (Alam) that is a function of true and shale resistivities, and fractional shale volume. The methodology integrates data from observations in outcrops, quantitative evaluation of cores, well logs and actual production data. Past Chicontepec studies have assumed that the porosity exponent (m) in Archie and shaly sandstone equations, is constant. However, core studies indicate that Chicontepec m values become smaller as porosity decreases. The proposed dual porosity petrophysical model, when applied to actual Chicontepec wells, matches properly the laboratory values of m, and generates results that compare well with actual production data, e.g., the larger the value of fracture partitioning the larger is the cumulative oil production. Pattern recognition allows estimating fracture intensity with a partitioning coefficient, which is calculated as the ratio of fracture porosity to total porosity. The novelty of this study is the development of a new petrophysical dual porosity model for naturally fractured shaly sandstone reservoirs that integrates variable values of m from cores, fracture intensity, and cumulative production of individual Chicontepec wells. Thirty-one wells have been evaluated with good results using the proposed model.
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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".