Characterization and Control of Halophilic Sulfate-Reducing and Methanogenic Microbial Communities in Shale Oil and Gas Systems
Bibliographic record
Abstract
In recent years, the oil and gas industry has been revolutionized by the expansion of shale oil and shale gas operations due to the advancement of hydraulic fracturing and high economic benefits compared to other unconventional resources. Several mechanisms have been proposed for the possible roles of microorganisms in shale gas fields. However, there remains a lack of knowledge regarding the key microbial players shared by all shale reservoirs and their involvements in the operations. Three case studies were conducted using samples obtained from various shale oil and shale gas reservoirs on the possibility of reservoir souring, microbiologically influenced corrosion (MIC) and microbially enhanced oil recovery (MEOR) through both culture-dependent and independent approaches. Case study I, for the Bakken shale oil field in Saskatchewan Canada, showed that continuous injection of low salinity source water can alter the microbial and geochemical conditions of the reservoir. There is a dominance of halophilic microbial community in the saline shale formations, in which Halanaerobium can synthesize the substrates used by halophilic sulfate-reducing bacteria (SRB) for sulfate-reduction, and halophilic nitrate-reducing bacteria (NRB) can inhibit the growth of SRB through nitrite production. At low salinity, the microbial community is much more diverse involving Halanaerobium, Desulfovibrio, Thiomicrospira, Dethiosulfatibacter and Arcobacter, with high potential for souring and MIC. In addition, at low salinity, nitrate-mediated souring control cannot be as easily achieved as nitrite is further reduced to N2. Case studies II and III were for the Duvernay shale gas field and Montney shale oil field in Alberta, Canada, which showed high MIC potential involving similar halophilic taxa as found in the Bakken field. Finally, samples from all three case studies indicated higher salinities were associated with higher ammonium concentrations, which is a product of methylotrophic methanogenesis using methylamines. The addition of methylamines in the hydraulic fracturing process can facilitate the possible interactions between the key players identified in all three case studies. Through this work, mitigation and monitoring technologies targeting recurring taxa involved in shale reservoirs on souring and MIC can be developed, which is highly beneficial for the environment and the economy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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".