Three university students studying topics relating to the oil and gas sector have been picked as the winners of the Offshore Mediterranean Conference "five minute speech contest."
Out of about 20 technical papers presented in just five minutes, students Gianluca Longoni, from the University of Bicocca, Milan, Claudia Zoccarato, from the University of Padua, and Paolo Zanini, from Milan Polytechnic University, were picked as the top three.
All the students presented their papers during the conference yesterday (26 March). We summarize their papers below:
Fluid extraction from producing hydrocarbon reservoirs is one of the most frequent causes of anthropogenic land subsidence. In this work, a 3D finite-element (FE) geomechanical model is used to predict the land surface displacements above a gas field where displacement observations are available. An ensemble-based data assimilation (DA) algorithm is implemented that incorporates these observations into the response of the geomechanical model, thus reducing the uncertainty on the geomechanical parameters of the sedimentary basin embedding the reservoir. The calibration focuses on the uniaxial vertical compressibility CM, i.e. the most important geomechanical parameter. The partition of the reservoir into blocks by faults suggests the assumption of a block heterogeneous CM within the reservoir. A synthetic test case is used to evaluate the effectiveness of the DA algorithm in reducing the parameter uncertainty associated with a block heterogeneous CM. In A significant improvement in reducing the CM uncertainty is obtained with respect to the assumption of a homogeneous CM. These preliminary results are encouraging and suggest the extension of the application to a real gas field.
Production Allocation is a well known practice in petroleum industry. It measures the quantities provided by the different sublevels of the reservoir to each well by analyzing the chromatograms of the extracted oils from several wells. This practice represents a crucial technology for oil and gas activities. Accenture (2014) defines Production Allocation “critical to the upstream energy industry but still mostly a manual process not well understood”. Several studies have been carried out to solve this problem. However, existing methods are significantly expensive and strongly invasive for the well operations, or they are based upon knowledge generally unavailable on the operation field(like, for instance, the sublevel chromatograms, also called end-members).
We model the oil chromatogram as a linear combination of the sublevel chromatograms and we exploit a statistical technique named Nonnegative Matrix Factorization - Alternating Least Square (NMF-ALS) to find the solution of the Production Allocation problem. In particular we conside X=C where X gathers the known evaluation of the oil chromatograms, S the unknown evaluation of the end-members and C the unknown concentrations of the end-members for each well. Our goal is to find an accurate estimate (C_hat, S_hat) of (C,S), relying only on the information contained in X. We face this problem using a functional representation for the chromatograms, or a multivariate representation, which takes into account only a fixed number of areas under some relevant chromatogram peaks. We establish a working pipeline built on different steps for data analysis and the a priori and a posteriori checks on data inputs and outputs. The introduction of a priori and a posteriori checks is crucial to obtain an accurate estimate. Within the pipeline we infer on the number of end-members, we identify possible anomalies in the analyzed data and we choose an optimal estimate for both the concentration matrix (C) and the end-member matrix (S). Extensive use of this working pipeline on synthetic datasets prepared in laboratory provided outstanding results with a mean error for the concentrations equal to 3% and very accurate estimates of the end-member matrix, both using the functional and the multivariate representations.
This work was partially supported by Eni - Exploration & Production.
Lithium-ion battery (LIB) technology represents the major share (37%) of the whole battery market, thanks to its high versatility, moderate energy density and high round trip efficiency. The huge exploitation of this technology, together with political issues related to uneven global distribution of raw materials (Li2CO3), and a limited but constant increase in lithium market price, concurred in arising a growing concern about the future sustainability thereof. Added to this, LCA analysis of the most common battery technologies revealed that almost 400 kWh of energy are averagely involved in the production of just 1 kWh LIB).
Rechargeable batteries based on sodium ion (NIB) represents a cheaper and a more environmentally sustainable solution but still a competitive technology, according to the larger availability of raw materials and to the rather similar chemistry between Lithium and Sodium. A cost effective and easily-scalable energy storage technology would be particularly appealing for stationary systems coupled to renewable energies sources, to ensure continuity and self-sufficiency to power grids.
Many efforts have already been spent in designing and characterizing stable and moderate-capacity cathode materials for NIBs, and promising results have been achieved. Anode material, conversely, still represents a challenging topic needy to be explored. The primary aim of the present work is to investigate nanostructured oxides of abundant transition metals (Fe3O4 and Co3O4) as possible candidates as high capacity anode materials for NIBs. Theoretical capacities of such materials are close to 890 mAh g-1, and preliminary results obtained from nanostructured needle-like Co3O4 samples, show capacity values between 400-500 mAh g-1 maintained for more than 30 cycles (130-160% of a graphitic anode capacity of a common LIB) at 92 mA g-1 discharge/charge rate.
Only simple and easily scalable synthetic paths (150-200°C hydrothermal methods) are being considered, in order to keep this solution attractive to large-scale manufacturing. In order to overcome the electric insulating nature of the compound, a conducting carbonaceous matrix obtained from low-temperature hydrothermal carbonization (HTC) of rice husk (an abundant by-product of rice processing) is planned to be used. Preparation and characterization of other materials, apart from those above mentioned, will be performed with the goal of a deeper understanding in how material morphology and porosity affect the electrochemical behavior, in order to guide and refine the future synthetic approaches. Sustainability of the chemical steps is considered a constant driver across all the research activity.