BasinMod Risk

BasinMod Risk addresses those risks associated with the elements and processes of petroleum systems, plays and prospects. Unlike deterministic modelling programs, BasinMod Risk utilizes a stochastic approach to modelling which tests thousands of assumptions and produces a range, or probability distribution, of results.

Risk Model Building

• Uncertainty is assigned to model parameters using one of several probability distributions, including lognormal, BetaPERT, discrete, and others.
• Charge parameters: Lithologies and their rock properties, kerogen type, saturation threshold, TOC, initial HI, source area and thickness, migration efficiency, heat flow, etc.
• Trap parameters: Hydrocarbon saturation potential, formation volume factor, reservoir porosity & thickness, net/gross ratio, seal efficiency and area of closure.
• Chance Factors: While the parameters of charge and trap can be assigned an uncertainty, source rock, reservoir, seal and structure can be risked as to their presence or absence.
• Sampling: Sampling within BasinMod Risk may be done using either Monte Carlo or Latin Hypercube methods.

Output:

• The output is a spatial risk assessment map of the key elements (charge, trap including reservoir, seal and structure), and regional distribution of geologic probability of success (PS) for an area(s) of interest (Fig 1). Areas of higher probability of success can evaluated in greater detail.
• The results of the simulation run provides a distribution of charge migrated, seal effectiveness, oil and/or gas in-place, recoverable reserves or other user defined parameters. Each of the critical components is defined by a probability distribution that may or may not be calibrated. Sampling the set of critical probabilities yields a distribution of prospect ‘value’, i.e., a probabilistic ranking of the identified prospects. Risk can be simultaneously assessed on multiple traps within a play, or multiple compartments within a structural trap.
• Additionally, for each of the parameters with uncertainty, probability density histograms, cumulative probability plots, rank correlation (“tornado” diagrams), scatter plots, parameter vs. event time and value vs. event depth plots are provided.