Challenges Associated with the Acid Gases Production and Capture in Hydrocarbon Reservoirs: A Critical Review of the Venezuelan Cases
Bibliographic record
Abstract
Abstract Acid gases production, such as hydrogen sulfide and carbon dioxide, from heavy oil reservoirs in Venezuela is generally associated with the application of thermal enhanced oil recovery methods. These undesired gases, especially H2S, can be removed by injecting chemical additives that promote chemical reactions with oxidative or nonoxidative mechanisms in the producing system to generate fewer toxic byproducts. According to the literature, H2S scavengers evaluated in the oil industry are amines, alkaline sodium nitrite, hydrogen peroxide, triazine, among others. To mitigate both H2S and CO2 from a reservoir, some novel proposals are under study to offer alternatives to control them from the reservoir and reduce their production in surface. This article presents a review of the key parameters that play a role in the generation of acid gases, mainly H2S and CO2, in Venezuelan oil reservoirs. The operational field data, the main reactions and mechanisms involved in the process (e.g., aquathermolysis, hydro pyrolysis), and the type of byproducts generated will be reviewed. The results and knowledge gained will assist in identifying the main insights of the process, associating them with other international field cases published in the literature, and establishing perspectives for the evaluation of the most convenient techniques from health, safety, technical and economic points of view. Lab and field results have shown that the application of thermal EOR methods in reservoirs of the main Venezuelan basins promote the generation of acid gases due to physicochemical transformations of sulfur, and/or fluid-rock interactions. Sulfur content in Venezuelan viscous oil reservoirs, together with rock mineralogy (clay type) has a significant impact on H2S production. Reported lab results also indicated that H2S scavengers reduce the amount of sulfur, and the presence of CO2 also affects the H2S removal mechanisms, depending on which type of scavenger is selected (e.g., amines, triazine, etc.). Solubilization, hydrolysis, adsorption, absorption, and complex sequestrant reactions (oxidation, neutralization, regeneration, and precipitations) are the main mechanisms involved in the removal of H2S. The literature reported that the application of triazine liquid scavengers is found to generate monomeric dithiazine byproducts (amorphous polymeric dithiazine) which might cause formation damage or inflict flow assurance issues upstream and downstream. This work presents a state of the art review on H2S generation mechanisms and new technologies for the mitigation of acid gases in Venezuelan reservoirs. It also provides perspectives for the application of the most convenient technologies for the reduction of greenhouse gas emissions (mostly CO2), which is critical to producing hydrocarbons with low environmental impact.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".