Bibliographic record
Abstract
Abstract There are four major stakeholders in the oil and gas production process. These are the oil companies, the shareholders, the society and the host communities. The cost of protecting and reclaiming the environment has different impacts on the financial conditions of each of these stakeholders. Each stakeholder therefore has its unique economic perspective defined by its minimum rate of return and its view of project profitability. For a win-win situation for all stakeholders, the project must be profitable from the unique point of view of each of the stakeholders. In the past, emphasis was placed only on the perspectives of the oil companies and the shareholders. Economic models captured environmental costs as economic externalities that increased project operational and salvage costs, thus decreasing company profitability and shareholders’ dividend payments. But, the devastating impact of environmental pollution of the finances of the inhabitants of the host communities is now being recognized. The host communities need the regenerative capacity of the environment to maintain basic farming and fishing activities needed for their survival. The society, represented by the national government, suffer revenue loss in the face of oil pollution. This paper develops a model that captures project profitability from the four perspectives. The perspective of the oil companies uses the cost of borrowing capital as its absolute minimum rate for determining profitability while that of the shareholder uses the bank (saving) rate of return as an absolute minimum. For the society, the absolute minimum rate of return must capture the replacement of oil and gas as wasting assets. In the case of the host communities, this absolute minimum rate must encompass the replacement of income generating capacity lost due to environmental pollution as well as the cost of maintaining the economic regenerative capacity of the environment. The paper concludes that for a project to be profitable, it must meet the profitability criteria from these four perspectives. The profitability of projects from the perspectives of the society and host communities is the critical test for environmentally friendly oil and gas operations. Introduction Pollutants generated during oil and gas operations include produced formation water, drilling fluids, drilling cuttings, CO, SOx, NOx, particulates, oil leaks, oil spills, deck drainage, heat, noise, produced sands and all kinds of solid waste. These pollutants have a negative impact on the environment. Air, water and land have a lot of use value but little or no exchange value. In their natural state, they are often treated as free goods with no market value because of their abundance. Therefore, the costs of the pollution is often passed on to the society.1 The resulting outcry by environmental groups and non-governmental organizations encouraged many national governments to enact laws that protected the air, water and environmental quality as well as define and constrain the handling and disposal of hazardous waste.2 The oil companies treated the cost of meeting the new environmental laws as externalities and passed them on to the consumers. In 1990, externalities were estimated at 12%, 25% and 45% of the existing natural gas, oil and coal plants respectively.3 Some state regulatory commissions in USA and Canada now require that environmental externalities be incorporated into conventional resource selection, planning and decision making processes. This paper presents an approach of incorporating environmental impacts into conventional project economic models used in decision making in oil and gas operations. The new approach encompasses the costs and benefits to the major stakeholders in the process. The profitability of an investment opportunity is evaluated from the perspective of each major stakeholder. The opportunities that are profitable from all perspectives are screened out before they are ranked. This ensures that only the opportunities that are environmentally friendly are utilized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".