Visualizing hydrocarbon migration pathways associated with the Ringhorne oil field, Norway: An integrated approach

Norway's Ringhorne Field is a faulted anticline, which produces oil from Triassic (Statfjord) and Paleocene (Hermod) sands. It is located on the Utsira High. Geochemical studies of the produced oil indicate that the oil is generated from mature Upper Jurassic marine shales in the adjacent Viking Graben. However, it is not clear how oil migrated into the Triassic reservoirs and charged the overlying Paleocene reservoirs. Lateral hydrocarbon migration is not detectable on seismic data. However, vertical hydrocarbon migration can be observed as a vertically aligned, low-amplitude, chaotic signature on normally processed seismic data. Gas-chimney detection is a proven neural network technique to detect these vertical hydrocarbon migration pathways. The processing results are then validated using a set of criteria to determine if they represented true hydrocarbon migration rather than seismic artifacts. The chimney processing results using this traditional (shallow) neural network are compared with convolutional neural network (deep learning) results and geomechanical modeling on key lines. Key reservoirs are delineated using a deterministic simultaneous seismic inversion approach. Reliable chimneys are then visualized in the vicinity of the producing reservoirs. The results indicate pathways by which the Triassic fluvial sands received the charge and how these reservoirs have flank leakage to provide the charge to shallower Paleocene reservoirs. This approach is currently being used over hundreds of fields and dry holes in the Norwegian North Sea and worldwide as analogs to assess the hydrocarbon charge and top seal risk predrill.