• Dying intestate or with a will on toxic estate? an evaluation of petroleum fiscal systems and the economic and policy implications for decommissioning of onshore crude oil fields in Nigeria

      Afieroho, Erovie-Oghene Uyoyou-karo; Patil, Shirish L.; Dandekar, Abhijit; Reynolds, Douglas B.; Perkins, Robert (2018-05)
      Many giant fields in the world like the onshore fields in Nigeria which were initially discovered over half a century ago, have begun to see consistent decline in production and profit, and are gradually entering into the economic end of field life or decommissioning phase. Characteristically, in most regions with mature fields, the large multinational oil companies have begun to sell their oil fields to small indigenous companies who may not be financially robust enough to complete the decommissioning, when it occurs. Because of the pervasive societal impact of the oil industry, if an investor fails to properly decommissioning the infrastructure, a responsible government will have to pay for the proper decommissioning, else society will suffer the socioeconomic, political, health and environmental impact. Therefore, society needs to be effectively engaged in the development of a sustainable decommissioning policy framework, which is hindered if society is uninformed and lacks access to pertinent information. Currently, there is abysmal information in the public space on the cost of decommissioning liabilities of oil fields, especially in developing countries like Nigeria. The public also need simple interpretative ways to determine the vulnerability of a county or entity to decommissioning default risk and the imminence of a default risk. Furthermore, there is currently, no way to benchmark the level of maturity or level of preparedness for decommissioning phase such that countries and entities can identify their gaps to a sustainable decommissioning policy framework and define a roadmap to close the gaps. These are important challenges to vigorous public participation, which is an essential requirement for development and implementation of any sustainable public policy for a public issue like decommissioning of crude oil fields. This study adopted several research methods to develop and introduce a new cost estimating methodology that uses publicly declared cost of asset retirement obligations (ARO) to determine a plausible cost estimate range for decommissioning liabilities. It was demonstrated with Nigeria onshore crude oil fields, which it determined to have a rough order of magnitude cost estimate for decommissioning liabilities that could be as high as $3 billion. Secondly, it also introduced decommissioning coverage ratio (DCR) and decommissioning coverage ratio vector (DCRV) as new metrics to evaluate the vulnerability to and imminence of decommissioning default risk. In demonstrating these new metrics, this study determined that the imminence of and vulnerability to decommissioning default risk for the onshore crude oil fields in Nigeria, with respect to any of the available revenue streams, is high. Thirdly, it developed a graded scale maturity model for sustainable decommissioning of petroleum fields. The model described as Fairbanks maturity model for sustainable decommissioning in the petroleum industry, has five progressive levels of maturity. It leveraged the methodology used for similar maturity models developed in other industries and for business management, and a comparative analysis of level of progress in decommissioning frameworks between some countries with leading decommissioning experience in the petroleum industry, to develop the Fairbanks maturity model. Based on the Fairbanks maturity model, frameworks for sustainable decommissioning of Nigeria onshore crude oil fields were evaluated to be at Level 1, Ad hoc maturity level, which is the lowest maturity level. Recommendations to close the identified gaps were also were made. These methodologies can be applied to any petroleum producing region or entity in the world and are advancements to the frontier of knowledge in the management of decommissioning phase for petroleum fields in general and Nigeria onshore fields in particular.
    • Dynamics simulation of human box delivering task

      Owens, Paul Davis; Xiang, Yujiang; Peterson, Rorik; Chen, Cheng-fu (2018-05)
      The dynamic optimization of a box delivery motion is a complex task. The key component is to achieve an optimized motion associated with the box weight, delivering speed, and location. This thesis addresses one solution for determining the optimal delivery of a box. The delivering task is divided into five subtasks: lifting, transition step, carrying, transition step, and unloading. Each task is simulated independently with appropriate boundary conditions so that they can be stitched together to render a complete delivering task. Each task is formulated as an optimization problem. The design variables are joint angle profiles. For lifting and carrying task, the objective function is the dynamic effort. The unloading task is a byproduct of the lifting task, but done in reverse, starting with holding the box and ending with it at its final position. In contrast, for transition task, the objective function is the combination of dynamic effort and joint discomfort. The various joint parameters are analyzed consisting of joint torque, joint angles, and ground reactive forces. A viable optimization motion is generated from the simulation results. It is also empirically validated. This research holds significance for professions containing heavy box lifting and delivering tasks and would like to reduce the chance of injury.
    • Maximum weight lifting prediction considering dynamic joint strength

      Rana, G M Rahid uz zaman; Xiang, Yujiang; Chen, Cheng-fu; Peterson, Rorik (2018-05)
      This thesis describes an efficient optimization method for predicting the maximum lifting weight considering dynamic joint strength in symmetric box lifting using a skeletal model. Dynamic joint strength is modeled as a three-dimensional function of joint angle and joint angular velocity based on experimentally obtained joint strength data. The function is further formulated as the joint torque limit constraint in an inverse dynamics optimization formulation to predict the lifting motion. In the proposed optimization formulation, external load is treated as design variables along with joint angle profiles, which are represented by control points of B-spline curves. By using this new formulation, dynamic lifting motion and strategy can be predicted for a symmetric maximum weight box lifting task with given initial and final box locations. Results show that incorporating dynamic strength is critical in predicting the lifting motion in extreme lifting conditions. The prediction outputs in joint space are incorporated in OpenSim software to find out muscles force and activity during the movement. Electromyography data are collected for a regular weight lifting to validate the integration process between the predictive model (joint model) and OpenSim model (muscle model). The proposed algorithm and analysis method based on motion prediction and OpenSim can be further developed as a useful ergonomic tool to protect workers from injury in manual material handling.