Abstract:

The combination probability, the possibility that at least one segment contains hydrocarbons, can be used to assess the discovery probability of a trap.Obviously,‘at least one segment containing oil/gas’ reflects all possibilities of trap combinations.However, some traps should not be treated as one combination due to the constraint of special geological conditions.The trap combinations have direct influences on the estimation of geological resource.In order to calculate trap combination probability under the constraint of geologic models, this paper first cleared geological meaning of current evaluation model for segment and demystified its mysterious hype.It is in fact a classical Bayes mathematical model consisting of marginal and conditional probability, which quantifies separately the overall accumulation conditions or play-level and local accumulation conditions.Geological correlations do exist among different traps when hydrocarbons accumulate in them, thus the evaluation of single trap should be based on the prerequisite of possibility of overall hydrocarbon accumulation.Secondly, corresponding to the value range of marginal probability, this paper recognizes three geological risk dependence types including full independence, partial dependence and full dependence.These dependence types can directly determine which traps are concordant with current geologic knowledge.Finally, an improved probability tree technique was designed for the petroleum integrated assessment software (PetroV).When integrated with the non-deterministic volumetric method, it can realize resource volume estimation through‘summation of probability combinations based on geological risk dependency’.Case study shows that geological risk dependence types play a key role in quantitative evaluation of traps and mapping of uncertain petroleum resource distribution corresponding to reasonable geologic model interpretations.

Key words: summation of probability combination, probability tree, undeterministic volumetric method, discovery risk dependence, trap assessment and target optimization