Geological heterogeneity in hydrocarbon reservoirs is normally related to variability in depositional facies, diagenesis and structure. On the Loppa High, Norwegian Barents Sea, reservoir quality in prospective Upper Palaeozoic carbonates is considered to be controlled mainly by primary depositional facies variability linked to active faulting, with a secondary overprint of palaeokarst. The best quality reservoirs are anticipated in build-up facies. Although high-quality 3Dseismic data exist over the prospect, it is a challenge to map the buildups and palaeokarst in three-dimensional space using conventional 3Dseismic interpretation tools. This is mainly due to the internal heterogeneity of the build-ups and palaeokarst, which are characterized by a range of seismic reflection/attribute patterns.A procedure for multi-attribute mapping of seismic facies is described and utilized to provide a truly threedimensional interpretation of build-up and palaeokarst geobodies. A neural network classifier is used to analyse a set of 3D attributes that capture the seismic stratigraphical and structural patterns inherent in the data. These attributes are referred to as 3D texture attributes since they describe the reflector-geometry in a small 3D neighbourhood. Pattern recognition is interpreter-guided, with the desired seismic facies to be mapped input as ‘training data’ and analysed prior to their presentation to the 3D-classification system. Once the classification is made, the interpreter is presented with a 3D classified volume and an uncertainty analysis of each of the mapped facies/classes. This is used to evaluate the results prior to their visualization in 3D space. The method allows the interpreter to identify quickly a volume where the features of interest occur and to focus the interpretation work directly on them. In addition, the 3D visualization of the mapped geobodies brings important new information that might be overlooked when inspecting data in vertical or horizontal data windows.In the Norwegian Barents Sea case study, 3Dseismic facies mapping provides the first truly three-dimensional interpretation of the build-ups and palaeokarst, where their external form, juxtaposition, cross-cutting relationships and structural information are preserved. These data give new insights as to the stratigraphic distribution and internal variability of the build-ups and palaeokarst system; this information is important to estimation of reservoir volume, connectivity and variability.
16This study contributes to the reconstruction of the geological and palaeoenvironmental 17 setting of the Mufara Formation (Upper Triassic, Sicily), which consists of monotonous marly 18 deposits intercalated with relatively thin limestones levels. Field study included description of 19 sixteen sections corresponding to thirteen outcrops, from which ~500 samples were taken.
South Sumatra Basin is an inverted post-arc Tertiary basin, which has a complex evolution history from late Eocene-Oligocene extension to late Miocene and Pliocene compression. To evaluate the overall basin prospectivity, a regional analysis is conducted at 8 stratigraphic levels from pre-Tertiary unconformity to Pleistocene. An integrated interpretation including more than 1400 2D seismic lines, 4 seismic 3D surveys, and formation evaluation from 80 key wells is used to run the basin analysis. A series of regional seismic transects are defined through key wells and major structural elements to capture the characteristics of structural styles, lithostratigraphy and hydrocarbon distribution across the basin.Structural restorations unravels the timing of fault activity showing basin rifting until ~23 Ma with main depocenters in Benakat Gully, Limau Graben, Central Palembang and Lematang Depression followed by sagging until 14.6 Ma. The compressive event is recorded from 5 Ma to present day. The buckling of syn-rift sediments suggests shortening expressed by inversion and fault reactivation rather than thrusting. Review of the source rock data, reservoir distribution, hydrocarbon phase and source to reservoir correlation data are evaluated in perspective of the basin configuration in order to select sections for basin modeling. The modeling results show onset of expulsion varying from ~10-15 Ma from Lemat Fm. and Talangakar Fm., and 5 Ma from Telisa Fm. Modeling suggests that Talangakar Fm. reservoirs are completely filled, whereas Lemat Fm. reservoirs are partially filled due to limited lateral and downward migration. Baturaja Fm. reservoirs in proximity to depressions are filled, and partial charge risk away from kitchen area. Most of the hydrocarbon are generated, expelled and accumulated between sedimentation of Lower Palembang Fm. to inversion time (10-5 Ma). The subsequent inversion is likely to have re-migrated hydrocarbon in Talangakar and Baturaja reservoirs along Benakat Gulley and associated fault bound folds.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.