Geothermal Energy Production in Venezuela: Challenges and Opportunities
Bibliographic record
Abstract
Abstract Geothermal energy is a useful source for the generation of electricity, heat, cooling, mineral extraction, oxygen, and hydrogen. For several decades, Venezuela has focused its energy model on its immense hydrocarbon reserves. Nevertheless, the need to diversify energy sources for the transition to net-zero carbon emissions entails considering the potential of renewable geothermal resources that have been largely exploited for recreational purposes until now (i.e., thermal waters), as well as exploring the geothermal characteristics of potential hydrocarbon deposits. The objective of this article is to perform a state-of-the-art investigation of the geothermal resources available in Venezuela (i.e., hydrothermal reservoirs, hot dry rocks, hydrocarbon reservoirs with high water cut production and at high temperature, among others), along with existing exploitation techniques for the generation of geothermal energy in the country. This article reviews the prevailing physics of geothermal reservoirs (fluid flow in porous media, heat transfer, the thermodynamics of fluids, chemical reactions, etc.), and international geothermal techniques such as Enhanced Geothermal Systems, Closed-Loop Geothermal systems, the integration of the organic Rankine cycle and proton exchange membrane electrolyzer to produce electricity and hydrogen, mineral extraction, geothermal CO2 plume for CO2 emission management, among others. Based on available technical reports, each method will be discussed in terms of its underlying technique, as well as its environmental impact. The results of this review indicate that within the scenarios that could be predicted in Venezuela for geothermal power generation are the following: the production of electricity and hydrogen from hydrothermal and/or aquifer systems, the conversion of depleted/abandoned oil and gas wells or high-water cut reservoirs to geothermal, combination of geothermal and CO2 storage/management, or other potential energy sources like hydrogen, together with mineral extraction from the produced water. Results based on international experiences indicate the importance of considering physicochemical and geochemical reactions, as well as an adequate heat transfer from reservoir to surface equipment, which can have an impact on the efficiency and cost of the processes. This article will provide one of the strategic tools to help in the exploitation of renewable geothermal resources in Venezuela and the transition to decarbonization. It opens up opportunities for the development of geothermal resources in the country where up to now these resources have remained underexploited. It also brings in international experiences on geothermal technologies to promote field applications and practical implementation of this technology in Venezuela.
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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".