EAGE Petroleum Geostatistics 2019
Our consultant Jean-Marc Chautru, an expert in geostatistics applied to reservoir modeling, will present a methodology enabling automatic trap detection and reservoir area uncertainty analysis. Attend his talk at the poster session of Thursday 5 September 2019 lunchtime.
AUTOMATIC SCENARIOS EXTRACTION FROM DEPTH UNCERTAINTY EVALUATION
Authors: Yves-Marie Méric, Pedro Correia, Jean-Marc Chautru*, Hélène Binet, Geovariances; Paolo Ruffo, Livia Bazzana, ENI
The poster presents a methodology that automatically identifies spill points and their associated traps for multiple realizations of depth horizons using stochastic simulations. Of special importance is a fault trap where subtle differences in the values for the depth horizons cause a drastically different scenario where the fault interface permeable-impermeable becomes inadequate in containing hydrocarbons. The case study is provided by ENI.
Abstract – The structurally lowest point in a hydrocarbon trap that can retain hydrocarbons is called a Spill Point and characterizing these locations over a depth horizon is a common approach in trap analysis. However, a horizon is an uncertain object typically produced through a time-to-depth conversion procedure which might involve several different variables like time, velocity, and fault position. Each of those variables brings its own uncertainty. By using geostatistical simulations, we produce different realizations of the depth horizons and further process them individually to determine the probability of the presence of reservoirs and spill points associated with highly probable reservoirs. This paper presents a methodology to achieve such results including our analysis algorithm for trap and spill point characterization. By using a case-study we demonstrate that only proper characterization of all relevant realizations in the uncertainty space shows us the possible scenarios and their impact on traps volume.