Prospect Evaluation and Risk Assessment in Oil & Gas Exploration
Prospect Evaluation and Risk Assessment in Oil & Gas Exploration
Prospect evaluation and risk assessment are fundamental components of the exploration workflow, forming the basis for investment decisions, portfolio ranking, and exploration strategy. A well-structured evaluation ensures that subsurface uncertainties are systematically analyzed and that the probability of commercial success is realistically represented before drilling.
1. Introduction
Oil and gas exploration relies on identifying and maturing prospects that have the potential to host commercially recoverable hydrocarbons. The evaluation process integrates geological, geophysical, petrophysical, and engineering data to estimate volumes, assess risks, and define the economic attractiveness of drilling a well.
2. Key Components of Prospect Evaluation
2.1 Geological Framework
A robust geological model is the foundation of any prospect evaluation. It typically includes:
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Structural interpretation: Mapping faults, closures, traps, and migration pathways.
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Stratigraphic framework: Defining depositional environments, reservoir distribution, and sealing geometries.
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Burial and tectonic history: Understanding maturation and timing relationships.
2.2 Reservoir Properties
Critical parameters include:
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Porosity and permeability
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Net-to-Gross (N/G)
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Reservoir thickness
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Fluid types and saturation
These properties are derived from well logs, core analysis, analog fields, and regional geological models.
2.3 Trap and Seal Analysis
Successful accumulation requires an effective trap configuration and a competent top and lateral seal capable of retaining hydrocarbons under subsurface pressure conditions.
2.4 Source Rock and Maturity
Evaluation includes:
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Total organic carbon (TOC)
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Kerogen type
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Maturity modeling
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Hydrocarbon generation potential
This ensures that the identified prospect is located within a viable petroleum system.
2.5 Hydrocarbon Migration
Analysis of carrier beds, structural orientation, fault conductiveness, and timing of structural growth vs. hydrocarbon generation determines whether hydrocarbons could migrate into the trap.
3. Volumetric Estimation
Prospective resources are estimated using deterministic or probabilistic methods.
3.1 Deterministic Approach
Uses single “best estimate” parameters to calculate GIIP/STOIIP.
3.2 Probabilistic Approach (Monte Carlo Simulation)
Captures the full range of uncertainty for reservoir properties. It defines:
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P10, P50, P90 volumes
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Expected Monetary Value (EMV)
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Probability of Success (POS)
Probabilistic evaluation is now considered industry best practice as it reflects natural subsurface uncertainty more accurately.
4. Risk Assessment
A prospect’s geological chance of success (GCoS) is determined by evaluating the risk in five main elements:
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Trap/Closure Risk
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Reservoir Risk
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Seal Risk
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Source Risk
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Migration/Timing Risk
Each element is assigned a probability (0–1), and the overall GCoS is calculated as:
GCoS=PTrap×PReservoir×PSeal×PSource×PMigration\text{GCoS} = P_{\text{Trap}} \times P_{\text{Reservoir}} \times P_{\text{Seal}} \times P_{\text{Source}} \times P_{\text{Migration}}
This probability is then used in volumetric and economic analysis to generate:
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Risked Resources
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Risked EMV
5. Economic Screening
Once technical evaluation is complete, economic assessment is performed, including:
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Development concept (platform, subsea tie-back, onshore facilities)
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CAPEX & OPEX estimation
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Breakeven price
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NPV, IRR, and EMV calculations
Only prospects with strong economic viability and acceptable risk profile are advanced toward drilling.
6. Prospect Maturation (Play-Based Exploration)
Prospects progress through defined stages:
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Lead Identification
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Lead Maturation
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Prospect Definition
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Drill-Ready Prospect
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Well Proposal Preparation
At each stage, uncertainty decreases and data quality increases. Decisions are typically governed by a prospect maturation workflow and gated reviews (e.g., TRMs, peer reviews, management approvals).
7. Role of Technology in Prospect Evaluation
Modern technologies significantly enhance prospect evaluations:
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3D seismic imaging and advanced processing (RTM, FWI)
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AVO and seismic inversion
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Machine learning for seismic classification
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Geomechanics for prediction of drilling challenges
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Integrated static and dynamic reservoir modeling
These tools reduce uncertainty and improve the reliability of risk assessment.
8. Conclusion
Effective prospect evaluation and risk assessment are essential to maximize exploration success and optimize investment decisions. By integrating geological understanding, seismic interpretation, reservoir characterization, and economic screening, companies can prioritize high-quality prospects and manage portfolio risk in a disciplined, data-driven manner.
A structured approach to risk assessment not only increases the chance of technical success but also ensures that exploration budgets are directed toward opportunities with the greatest value potential.
