Feasibility Study

Test Your Knowledge

Quiz: Drilling Down into Feasibility Studies

Instructions: Choose the best answer for each question.

1. What is the primary purpose of a feasibility study in the oil and gas industry? a) To estimate the amount of oil or gas reserves. b) To assess the technical, economic, and environmental viability of a project. c) To secure funding for a proposed oil and gas project. d) To develop a detailed operational plan for the project.

2. Which of the following is NOT a key component of a feasibility study? a) Market analysis b) Environmental impact assessment c) Legal and regulatory analysis d) Production scheduling

3. What is the main purpose of financial analysis within a feasibility study? a) To determine the project's profitability. b) To identify potential investors. c) To forecast future oil and gas prices. d) To develop a marketing plan.

4. Which of these factors is considered a subjective assessment in a feasibility study? a) Capitalization costs b) Regulatory environment c) Well drilling technology d) Market demand

5. What is a key benefit of conducting a feasibility study? a) Eliminating all project risks. b) Ensuring a guaranteed profit from the project. c) Reducing the likelihood of costly setbacks. d) Predicting the exact amount of oil or gas that will be extracted.

Exercise: Feasibility Study Evaluation

Scenario:

You are a project manager for an oil and gas company considering a new offshore drilling project. The company has conducted a feasibility study, but the results are mixed. The study indicates strong market demand for the extracted oil and favorable geological conditions. However, there are concerns about the high capitalization costs, potential environmental impact on marine ecosystems, and regulatory hurdles for offshore drilling.

Task:

Based on the provided scenario, outline a decision-making process for the project manager. Consider the following questions in your response:

• What are the key strengths and weaknesses of the project based on the feasibility study?
• What further analysis or data collection is required to address the concerns?
• What factors should the project manager consider when making the final decision about whether to proceed with the project?

Techniques

Chapter 1: Techniques Employed in Oil & Gas Feasibility Studies

Feasibility studies in the oil and gas industry rely on a diverse set of techniques to thoroughly assess project viability. These techniques are applied across various aspects of the project, from technical aspects to market analysis and environmental considerations. Key techniques include:

1. Technical Evaluation: This involves a detailed assessment of the project's technical feasibility. Specific techniques employed here include:

• Reservoir Engineering: Utilizing geological data and reservoir simulation models to estimate recoverable reserves, production rates, and potential challenges like water influx or pressure depletion.
• Drilling Engineering: Analyzing drilling costs, well design, and potential drilling risks based on geological conditions and well location.
• Production Engineering: Assessing production methods, equipment selection, and projected production capacity. This often involves detailed simulations to predict production performance under various scenarios.
• Pipeline Engineering: Evaluating pipeline design, construction feasibility, and potential environmental impacts. This may include route optimization and hydraulic modeling.
• Facility Engineering: Assessing the need for and design of processing facilities, storage tanks, and other infrastructure, including cost estimation and capacity analysis.

2. Cost Analysis: This involves meticulous cost estimation across all project phases:

• Detailed Breakdown: Categorizing costs into exploration, appraisal, development, operation, and decommissioning.
• Cost Estimation Methods: Employing different methods such as parametric estimation, bottom-up estimation, and analogous cost estimation based on similar projects.
• Contingency Planning: Incorporating a buffer to account for unforeseen cost overruns.
• Sensitivity Analysis: Evaluating the impact of potential cost fluctuations on project profitability.

3. Financial Analysis: This employs various financial tools to assess economic viability:

• Discounted Cash Flow (DCF) Analysis: Determining Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period to assess project profitability over time.
• Sensitivity Analysis: Evaluating the impact of changes in key parameters (oil price, production rates, operating costs) on project profitability.
• Monte Carlo Simulation: Utilizing probabilistic models to simulate potential outcomes and assess risk.
• Break-Even Analysis: Determining the conditions under which the project becomes profitable.

4. Environmental Impact Assessment (EIA): This critical component employs techniques such as:

• Baseline Studies: Documenting existing environmental conditions to assess potential project impacts.
• Impact Prediction: Modeling the potential impacts on air and water quality, biodiversity, and greenhouse gas emissions.
• Mitigation Planning: Developing strategies to minimize negative environmental impacts.
• Regulatory Compliance: Ensuring adherence to all relevant environmental regulations and permitting requirements.

5. Market Analysis: This comprises:

• Demand Forecasting: Estimating future demand for the produced hydrocarbons based on market trends and projections.
• Price Forecasting: Analyzing potential future oil and gas prices, considering various market scenarios.
• Competitive Analysis: Assessing the competitive landscape and the project’s market share potential.

These techniques, when used in combination, offer a comprehensive assessment of a project's feasibility. The specific techniques used will vary based on the project's scale, complexity, and location.

Chapter 2: Models Used in Oil & Gas Feasibility Studies

Feasibility studies heavily rely on various models to simulate different aspects of the project and predict future outcomes. These models range from simple spreadsheets to complex, integrated simulations. Key models include:

1. Reservoir Simulation Models: These sophisticated models predict reservoir performance, including fluid flow, pressure changes, and hydrocarbon recovery. They use geological data and engineering parameters to simulate the behavior of the reservoir over time, helping predict production rates and ultimate recovery. Examples include Eclipse, CMG, and INTERSECT.

2. Economic Models: These models assess the financial viability of the project. Common models include:

• Discounted Cash Flow (DCF) Models: These models calculate the net present value (NPV) and internal rate of return (IRR) of the project, incorporating factors such as capital expenditures, operating costs, revenue, and discount rates.
• Monte Carlo Simulation Models: These probabilistic models use random sampling to simulate the range of possible outcomes, considering the uncertainties inherent in various parameters (e.g., oil price, production rates). This provides a more realistic assessment of risk.
• Sensitivity Analysis Models: These models assess the impact of changes in key parameters on the project's profitability.

3. Environmental Models: These models predict the environmental impacts of the project:

• Air Dispersion Models: Simulate the spread of air pollutants from facilities and predict their concentration levels in the surrounding environment.
• Water Quality Models: Predict the impacts of project activities on water quality, considering factors like wastewater discharge and potential spills.
• Ecological Models: Assess the potential impacts on biodiversity and ecosystem health.

4. Production Optimization Models: These models aim to maximize production efficiency and profitability:

• Linear Programming Models: Optimize production strategies by considering various constraints (e.g., reservoir pressure, production capacity).
• Simulation-Optimization Models: Combine reservoir simulation and optimization techniques to find the best production strategy.

5. Risk Assessment Models: These models quantify and manage risks associated with the project:

• Decision Tree Models: Visualize different scenarios and their probabilities, aiding decision-making under uncertainty.
• Fault Tree Analysis (FTA): Identifies potential causes of failure and their probabilities.

The selection of appropriate models is crucial for the accuracy and reliability of the feasibility study. The complexity of the models used will vary depending on the project’s characteristics and the available data. Model validation and uncertainty analysis are crucial aspects of ensuring the credibility of the study.

Chapter 3: Software Used in Oil & Gas Feasibility Studies

Numerous software packages are employed to facilitate the various aspects of an oil and gas feasibility study. These tools automate complex calculations, provide visualization capabilities, and improve the overall efficiency of the process. Key software categories include:

1. Reservoir Simulation Software: Specialized software packages simulate reservoir behavior and predict hydrocarbon recovery. Examples include:

• Schlumberger Eclipse: A widely used industry-standard simulator for modeling reservoir performance under various operating conditions.
• CMG (Computer Modelling Group) Software: Offers a suite of reservoir simulation tools, including IMEX, STARS, and GEM.
• Roxar RMS: An integrated reservoir modeling and simulation platform.

2. Petrophysical Analysis Software: Used to analyze well logs and other data to determine reservoir properties such as porosity, permeability, and saturation. Examples include:

• Interactive Petrophysics (IP): A popular software package for petrophysical interpretation.
• Techlog: Provides a comprehensive suite of tools for well log analysis and interpretation.

3. Financial Modeling Software: Facilitates financial analysis, including discounted cash flow (DCF) analysis and sensitivity analysis. Examples include:

• Microsoft Excel: While a basic tool, Excel is widely used for creating financial models, especially for smaller projects.
• Specialized Financial Modeling Software: More sophisticated packages exist for larger, complex projects, offering advanced features for risk analysis and scenario planning.

4. GIS (Geographic Information Systems) Software: Used for spatial data analysis and visualization, especially for mapping infrastructure and potential environmental impacts. Examples include:

• ArcGIS: A widely used GIS software package.
• QGIS: A free and open-source GIS software.

5. Environmental Modeling Software: Simulates environmental impacts, including air and water quality. Examples include:

• AERMOD: A widely used air dispersion model.
• Hydrologic modeling software: Various packages simulate water flow and water quality.

6. Project Management Software: Assists in project planning, scheduling, and tracking. Examples include:

• Microsoft Project: A common project management software.

The choice of software depends on the project's specific needs, budget, and available expertise. Often, a combination of software packages is used to effectively address the diverse requirements of a feasibility study. Data integration and interoperability between different software packages are crucial for efficient workflow.

Chapter 4: Best Practices for Oil & Gas Feasibility Studies

Conducting a robust and reliable feasibility study requires adherence to best practices. These practices ensure the accuracy, objectivity, and usefulness of the study's findings.

1. Define Clear Objectives and Scope: Before starting, clearly define the study's objectives and scope. This includes specifying the project's goals, the geographical area covered, and the key aspects to be analyzed.

2. Assemble a Competent Team: The study team should include professionals with expertise in various disciplines, including geology, engineering, finance, and environmental science. Expertise specific to the project's type and location is essential.

3. Utilize Reliable Data: The study should be based on high-quality, reliable data. Data sources should be clearly identified and documented. Data validation and quality control are critical.

4. Apply Appropriate Techniques and Models: Select the most appropriate techniques and models based on the project’s complexity and available data. The limitations of the chosen models should be clearly stated.

5. Conduct Thorough Sensitivity and Risk Analysis: Assess the impact of uncertainties on project outcomes through sensitivity and risk analysis. Identify and quantify key risks and their potential impact.

6. Document Assumptions and Limitations: Clearly document all assumptions made and the limitations of the study. This ensures transparency and allows for a critical review of the findings.

7. Peer Review and Validation: Independent peer review of the study is recommended to ensure the quality and objectivity of the analysis. External validation can enhance credibility.

8. Transparent Reporting: The final report should clearly present the study's methodology, data sources, results, and conclusions. The report should be easily understandable to stakeholders with varying levels of technical expertise.

9. Iterate and Adapt: Feasibility studies are often iterative. New information or changing circumstances may require adjustments to the scope, methods, and conclusions.

10. Maintain Confidentiality: Confidential information should be handled securely and in accordance with industry best practices and regulations.

Adhering to these best practices minimizes bias, increases the reliability of the study's findings, and ultimately supports informed decision-making.

Chapter 5: Case Studies in Oil & Gas Feasibility Studies

Several case studies illustrate the application and value of feasibility studies in the oil and gas industry. These examples highlight different project types, challenges encountered, and the insights provided by the studies:

Case Study 1: Deepwater Offshore Development: A feasibility study for a deepwater oil and gas field in the Gulf of Mexico revealed significant technical and economic challenges associated with the project's remoteness and water depth. The study led to modifications in the development plan, including the selection of more robust and cost-effective subsea infrastructure, ultimately enhancing project viability.

Case Study 2: Unconventional Resource Development: The feasibility study of a shale gas project in North America involved detailed assessments of reservoir characteristics, drilling techniques, and environmental impacts. The study helped optimize the well spacing and completion design, maximizing production while mitigating environmental risks.

Case Study 3: Pipeline Construction Project: A feasibility study for a major pipeline project evaluated potential routes, environmental impacts, and regulatory hurdles. The study identified the most suitable route based on cost, environmental considerations, and regulatory approval timelines. This resulted in significant cost savings and accelerated project delivery.

Case Study 4: Offshore Wind Integration: An offshore wind farm project requiring integration with an existing oil and gas platform necessitated a comprehensive feasibility study assessing technical compatibility, grid connection feasibility, and regulatory compliance. The study provided insights into potential synergies and risks associated with the integrated development.

Case Study 5: Carbon Capture and Storage (CCS): A feasibility study for a CCS project assessed the technical viability of CO2 capture from an oil refinery, pipeline transportation, and geological storage. The study identified potential technical challenges and cost implications, informing decisions regarding project scope and technology selection.

These case studies demonstrate the diverse applications of feasibility studies and their crucial role in mitigating risks, optimizing project design, and ensuring the responsible development of oil and gas resources. Each case highlights the importance of a tailored approach considering the specific challenges and opportunities of each project. By learning from these examples, industry professionals can enhance their approach to conducting feasibility studies and improve decision-making processes.