Computing Gas in Place in a Complex Volcanic Reservoir in China

摘要

Gas-bearing reservoirs of the YingCheng Group in thernSongLiao Basin in northeastern China are hosted in a complexrnassemblage of volcanic rocks. These reservoirs present a largernnumber of interpretation challenges that have made thernevaluation of gas-in-place (GIP) problematic. A fit-forpurposernworkflow was developed for one accumulation in thisrnarea to provide robust GIP estimates in support of arndevelopment decision.rnThe workflow involves a number of novel techniquesrndeveloped to address the challenges presented by thesernreservoirs. Rock typing was conducted through integration ofrncore descriptions with neutron capture spectroscopy, nuclearrnmagnetic resonance logs, and borehole images using a neuralrnnetwork approach. These rock types, characterizing variationsrnin chemistry and rock texture, were then propagated in arngeocellular model using multivariate seismic attribute analysisrnand distribution rules based on volcanic analogues. Porosityrnand water saturation from an innovative petrophysicalrninterpretation methodology were propagated throughout thernmodel based on these rock types. The distribution of both rockrntypes and petrophysical properties was performedrnstochastically and a range of potential GIP estimates wasrndeveloped.