ALBERT

Description: Deepwater spills pose a unique challenge for reliable predictions of oil transport and fate, since live oil spewing under very high hydrostatic pressure has characteristics remarkably distinct from oil spilling in shallow water. It is thus important to describe in detail the complex thermodynamic processes occurring in the near-field, meters above the wellhead, and the hydrodynamic processes in the far-field, up to kilometers away. However, these processes are typically modeled separately since they occur at different scales. Here we directly couple two oil prediction applications developed during the Deepwater Horizon blowout operating at different scales: the near-field Texas A&M Oilspill Calculator (TAMOC) and the far-field oil application of the Connectivity Modeling System (oil-CMS). To achieve this coupling, new oil-CMS modules were developed to read TAMOC output, which consists of the description of distinct oil droplet “types,” each of specific size and pseudo-component mixture that enters at a given mass flow rate, time, and position into the far field. These variables are transformed for use in the individual-based framework of CMS, where each droplet type fits into a droplet size distribution (DSD). Here we used 19 pseudo-components representing a large range of hydrocarbon compounds and their respective thermodynamic properties. Simulation results show that the dispersion pathway of the different droplet types varies significantly. Indeed, some droplet types remain suspended in the subsea over months, while others accumulate in the surface layers. In addition, the decay rate of oil pseudo-components significantly alters the dispersion, denoting the importance of more biodegradation and dissolution studies of chemically and naturally dispersed live oil at high pressure. This new modeling tool shows the potential for improved accuracy in predictions of oil partition in the water column and of advancing impact assessment and response during a deepwater spill.

Description: Petroleum is one of the most complex naturally occurring organic mixtures. The physical and chemical properties of petroleum in a reservoir depend on its molecular composition and the reservoir conditions (temperature, pressure). The composition of petroleum varies greatly, ranging from the simplest gas (methane), condensates, conventional crude oil to heavy oil and oil sands bitumen with complex molecules having molecular weights in excess of 1000 daltons (Da). The distribution of petroleum constituents in a reservoir largely depends on source facies (original organic material buried), age (evolution of organisms), depositional environment (dysoxic versus anoxic), maturity of the source rock (kerogen) at time of expulsion, primary/secondary migration, and in-reservoir alteration such as biodegradation, gas washing, water washing, segregation, and/or mixing from different oil charges. These geochemical aspects define the physical characteristics of a petroleum in the reservoir, including its density and viscosity. When the petroleum is released from the reservoir through an oil exploration accident like in the case of the Deepwater Horizon event, several processes are affecting the physical and chemical properties of the petroleum from the well head into the deep sea. A better understanding of these properties is crucial for the development of near-field oil spill models, oil droplet and gas bubble calculations, and partitioning behavior of oil components in the water. Section 3.1 introduces general aspects of the origin of petroleum, the impact of geochemical processes on the composition of a petroleum, and some molecular compositional and physicochemical background information of the Macondo well oil. Section 3.2 gives an overview over experimental determination of all relevant physicochemical properties of petroleum, especially of petroleum under reservoir conditions. Based on the phase equilibrium modeling using equations of state (EOS), a number of these properties can be predicted which is presented in Sect. 3.3 along with a comparison to experimental data obtained with methods described in Sect. 3.2.

Description: Landslide is one of the dangerous types of natural hazards. This phenomenon causes damages in many countries every year. A detailed landslide hazard assessment is necessary to reduce these damages. This research aims to map the landslide susceptibility zoning (LSZ) using the fuzzy logic method and GIS in the Sorkhab basin as a part of the Zagros fold and thrust belt (FTB), northwestern Iran. All slide types were recorded in fieldwork as landslide inventory. Based on the results, four types, i.e., debris slide, earth slide, and rock fall and complex of landslides, was identified in the region. Then, the effect of each landslide contributing factor including topographical elevation heights, slope classes, aspect classes, geological units, proximity to faults, land covers, rainfall classes, and proximity to streams was constructed in GIS and subsequently normalized using fuzzy membership functions. Finally, by combining all standardized layers using the fuzzy gamma operator, a final map of LSZ was produced. The results showed that a 0.9 fuzzy gamma operator has a high accuracy for the LSZ map in the study area. Besides, the accuracy of the LSZ map revealed a strong relationship (R2) between susceptibility classes, and landslide inventory was calculated using a scatter plot equal to 0.79. Hence, the method represented an appropriate accuracy in predicting the landslide susceptibility in the study area.

Description: Maria S. Merian - MSM94 - SNAP Westlicher Subpolarer Atlantik 02.08.2020 - 06.09.2020

Description: 31.8.-6.9.2020

Description: 7.9.-13.9.2020

Description: 17.-23.8.2020

Description: 14.9.-20.9.2020

Description: 21.07 – 31.07.2020, Warnemünde (Germany) – Kiel (Germany) BALTEACH - 1