Abstract Drilling for hydrocarbons in the deep marine environment provides a unique setof challenges for industry. Amongst these are the distinct hazards caused bynatural geological and oceanic processes such as:semi-permanent bottomcurrents,episodic turbidity currents, slope instability and mass transportevents (slides, slumps, debris flows), andgas hydrate escape. We presentdata on the nature, effects and assessment of these deepwater hazards, including current velocities, transport/erosion capacities, recurrenceintervals, and hydrate distribution. It is of upmost importance that theoceanographic conditions are carefully considered prior to deepwater operationsto ensure the work can be carried out safely. Thorough risk assessment requiresknowledge of existing bottom currents, an assessment of potential masstransport events and turbidity currents, and understanding of conditions likelyto induce the formation and destabilisation of gas hydrates. Pipelines, cables, subsea installations, key connections such as the riser and any other seabedinfrastructure are all susceptible to damage. Correct assessment of hazard willallow for the right equipment to be used for the operations including blowoutpreventers, riser size, vibration suppressors, and for the safest siting ofcables and pipelines. It will also aid the subsea architecture design andplanning operations with minimal downtime. All these considerations lead to asafer exploration and production while eliminating unnecessary cost. Introduction Deepwater is defined by different communities in slightly different ways. Forthe marine geologist and oceanographer, it is often taken as that area of theocean beyond the shelf break, i.e. deeper than about 100–200 m water depth. Forthe sedimentologist, it is below storm wave base, which is also around 100–200m. For the industry, deepwater exploration is considered to be that in waterdepths in excess of 500 m. For the purposes of this paper, we consider theshelf-slope transition (i.e. shelf break) as the key boundary between shallowand deep water. This deepwater environment is far from tranquil. It is subject to a range ofprocesses that will significantly affect drilling operations for hydrocarbonexploration and recovery. Bottom currents are everywhere present and in someareas they are especially active and with considerably elevated velocities. Here we first focus on deepwater bottom currents and the hazards they present. Their occurrence and distribution, nature and variability, and damage potentialare discussed, followed by consideration of the methods of hazard assessment. We present a new method using the bedform-velocity matrix.
Large databases of legacy hydrocarbon reservoir and well data provide an opportunity to use modern data mining techniques to improve our understanding of the subsurface in the presence of uncertainty and improve predictability of reservoir properties. A data mining approach provides a way to screen dependencies in reservoir and fluid data and enable subsurface specialists to estimate absent properties in partial or incomplete datasets. This allows for uncertainty to be managed and reduced. An improvement in reservoir characterisation using machine learning results from the capacity of machine learning methods to detect and model hidden dependencies in large multivariate datasets with noisy and missing data. This study presents a workflow applied to a large basin-scale reservoir characterization database. The study aims to understand the dependencies between reservoir attributes in order to allow for predictions to be made to improve the data coverage. The machine learning workflow comprises the following steps: (i) exploratory data analysis; (ii) detection of outliers and data partitioning into groups showing similar trends using clustering; (iii) identification of dependencies within reservoir data in multivariate feature space with self-organising maps; and (iv) feature selection using supervised learning to identify relevant properties to use for predictions where data are absent. This workflow provides an opportunity to reduce the cost and increase accuracy of hydrocarbon exploration and production in mature basins.
Abstract This work presents a detailed study of CONTOURIBER and Integrated Ocean Drilling Program 339 sediment data targeting sand‐rich contourites in the Eastern Gulf of Cadiz. All of the collected sediments are interpreted as contourites (deposited or reworked by bottom currents) on the basis of oceanographic setting, seismic and morphometric features, and facies characteristics. A variety of sandy and associated facies are found across the study area including: (i) bioturbated muddy contourites; (ii) mottled silty contourites; (iii) very fine mottled and fine‐grained bioturbated sandy contourites; (iv) massive and laminated sandy contourites; and (v) coarse sandy/gravel contourites. The thickest sands occur within contourite channels and there is a marked reduction in sand content laterally away from channels. Complementary to the facies descriptions, grain‐size analysis of 675 samples reveals distinctive trends in textural properties linked to depositional processes under the action of bottom currents. The finest muddy contourites (<20 μ m) show normal grain‐size distributions, poor to very poor sorting, and zero or low skewness. These are deposited by settling from weak bottom currents with a fine suspension load. Muddy to fine sandy contourites (20 to 200 μ m) trend towards better sorting and initially finer and then coarser skew. These are typical depositional trends for contourites. As current velocity and carrying capacity increase, more of the finest fraction remains in suspension and bedload transport becomes more important. Clean sandy contourites (>200 μ m) are better sorted. They result from the action of dominant bedload transport and winnowing at high current speeds. The results highlight the importance of bottom current velocity, sediment supply and bioturbational mixing in controlling contourite facies. Despite growing interest in their hydrocarbon exploration potential, contourite sands have remained poorly understood. This research therefore has important implications for developing current understanding of these deposits and aiding the correct interpretation of deep marine sands and depositional processes.
Abstract The Makassar Strait is an important oceanic gateway, through which the main branch of the Indonesian Throughflow (ITF) transports water from the Pacific to the Indian Ocean. This study identifies a number of moderate (>10 km 3 ) to giant (up to 650 km 3 ) mass transport deposits within the Makassar North Basin Pleistocene–Recent section. The majority of submarine landslides that formed these deposits originated from the Mahakam pro-delta, with the largest skewed to the south. We see clear evidence for ocean-current erosion, lateral transport and contourite deposition across the upper slope. This suggests that the ITF is acting as an along-slope conveyor belt, transporting sediment to the south of the delta, where rapid sedimentation rates and slope oversteepening results in recurring submarine landslides. A frequency for the >100 km 3 failures is tentatively proposed at 0.5 Ma, with smaller events occurring at least every 160 ka. This area is therefore potentially prone to tsunamis generated from these submarine landslides. We identify a disparity between historical fault rupture-triggered tsunamis (located along the Palu-Koro fault zone) and the distribution of mass transport deposits in the subsurface. If these newly identified mass failures are tsunamigenic, they may represent a previously overlooked hazard in the region.
Abstract The efficiency of virtual field trips (VFTs) compared to their physical counterparts, is often regarded as one of their key benefits. Virtual field trips are typically more time, cost and environmentally efficient and logistically easier to plan and execute. This is largely due to the lack of travel, however, the nature of these efficiencies, which is essential for deciding whether a trip should be virtual, physical or blended, have not previously been quantified. Here we present a quantitative evaluation of several measures of efficiency, using data from a like-for-like comparison between 10 day long virtual and physical field trips to Utah, USA, from the University of Aberdeen, UK. For this case study, our results demonstrate that virtual field trips are more efficient across all the categories of time, cost, environmental impact, and logistics. In addition to saved air travel days at the start and end of the physical trip, a further 33.3% of the time on the physical field trip was spent travelling (walking and driving). This time saving allowed an additional 16 localities to be visited on the virtual field trip. The virtual field trip localities also ran in an order that best suited the geological narrative rather than their geographic location which the physical field trip was restricted by. Flights and driven kilometres for the physical trip produced c. 4 t of carbon dioxide equivalent (CO 2 ) per student. The virtual trip produce <1% of the CO 2 and was comparable to a typical teaching week, making it significantly more environmentally efficient. The cost of the virtual trip was negligible compared to that of the physical trip (saving up to £ 3000 GBP per student). These findings were compared to the fulfilment of learning outcomes, quantified primarily through questionnaires, the student responses suggest that the PFT and VFT perceptions of learning outcomes were generally comparable. Efficiency is not the only measure of a successful field trip, with other parameters such as social cohesion and embodiment within the outdoor environment that must also be considered when planning a field trip. Therefore, the authors do not advocate or support an abandonment of physical field trips. Rather, this study aims to provide a first attempt to quantify efficiency to inform decision making when planning field training.