CPG Risk Assessment & Mitigation 2 — Questions and Answers
Question 1: Which statistical method is most appropriate for quantifying the probability of a petroleum system being active when data are sparse?
- Monte Carlo simulation
- Bayesian inference using analog data (Correct answer)
- Deterministic volumetric calculation
- Decline curve analysis
Correct answer: Bayesian inference using analog data
Bayesian inference allows geologists to update prior probabilities from analog basins with sparse site-specific data to estimate petroleum system risk.
Question 2: What does a 'probability of success' (Ps) value of 0.12 indicate for an exploration prospect?
- A 12% chance the well will encounter any hydrocarbons
- A 12% chance the prospect will be commercially viable after drilling
- A 12% chance that all geologic risk factors are simultaneously satisfied (Correct answer)
- A 12% chance the trap will contain gas rather than oil
Correct answer: A 12% chance that all geologic risk factors are simultaneously satisfied
Ps represents the joint probability that all required geologic elements (trap, reservoir, seal, source, migration) are simultaneously present and effective.
Question 3: In risked resource estimation, which of the following best defines the 'chance of geological success' (CGoS)?
- Probability that drilling reaches target depth without mechanical failure
- Probability that the prospect contains a producible accumulation given drilling (Correct answer)
- Probability that the discovered volume exceeds the economic threshold
- Probability that seismic interpretation correctly identifies the structure
Correct answer: Probability that the prospect contains a producible accumulation given drilling
CGoS is the probability that a drilled prospect contains a producible hydrocarbon accumulation, encompassing all geologic risk components.
Question 4: A geologist estimates reservoir presence risk at 0.7, trap integrity risk at 0.8, seal risk at 0.6, and source/charge risk at 0.75. What is the approximate Ps?
- 0.70
- 0.25 (Correct answer)
- 0.50
- 0.35
Correct answer: 0.25
Ps = 0.7 × 0.8 × 0.6 × 0.75 = 0.252, approximately 0.25, as risk factors multiply when independent.
Question 5: Which scenario best illustrates a 'common risk segment' (CRS) in prospect portfolio analysis?
- Two prospects sharing the same operator and drilling rig
- Multiple prospects that would all fail if the regional source rock is immature (Correct answer)
- Prospects located in the same country subject to the same fiscal regime
- Wells targeting the same reservoir formation at different structural positions
Correct answer: Multiple prospects that would all fail if the regional source rock is immature
A CRS groups prospects sharing a risk element that, if absent, causes all prospects in the group to fail simultaneously, affecting portfolio diversification.
Question 6: What is the primary purpose of a 'decision tree' in petroleum exploration risk assessment?
- To sequence drilling operations for maximum efficiency
- To map geological structures from seismic reflection data
- To enumerate possible outcomes and their probabilities to calculate expected value (Correct answer)
- To rank prospects by their estimated ultimate recovery
Correct answer: To enumerate possible outcomes and their probabilities to calculate expected value
Decision trees systematically lay out possible outcomes at each decision node with associated probabilities, enabling calculation of expected monetary value (EMV).
Question 7: Which risk mitigation strategy involves acquiring additional seismic data before committing to an exploration well?
- Risk transfer through joint venture participation
- Risk reduction through technical de-risking (Correct answer)
- Risk avoidance by relinquishing the license
- Risk acceptance with contingency reserves
Correct answer: Risk reduction through technical de-risking
Acquiring additional seismic data reduces geological uncertainty and is a technical de-risking approach that lowers structural and stratigraphic risk before drilling.
CPG Risk Assessment & Mitigation 2
Which statistical method is most appropriate for quantifying the probability of a petroleum system being active when data are sparse?