Search

The interpretation model for gas saturation in deep clastic reservoirs subject to intensive extrusion stress relies predominantly on experimental petrophysical data and the expanded Archie equation. Nonetheless, these methodologies may not consistently yield optimum results. Specifically, when subsurface pressure impacts formation resistivity, the resulting curve values exhibit substantial elevations, leading to significant inaccuracies in the precise estimation of gas saturation from resistivity logging data. Consequently, the evaluation of logging interpretations becomes a complex undertaking. This paper aims to comprehensively assess gas saturation in deep clastic reservoirs from both electrical and mechanical perspectives. To achieve this goal, we employ a multifaceted approach encompassing the Archie formula, the stress-corrected variable cementation index saturation model, and the resistivity-corrected saturation model. Through rigorous theoretical analysis and the utilization of simulated experimental data, a quantitative relationship equation between resistivity and stress difference has been established. Building upon this fundamental groundwork, an innovative resistivity-corrected saturation calculation model has been proposed. In comparison to the two alternative models, the new model exhibits enhanced accuracy in calculating gas saturation, as it is less influenced by extrusion stress and gravitational compaction. Furthermore, it demonstrates better consistency with core mercury injection capillary pressure data in determining gas saturation. The findings of this research provide valuable insights for the effective evaluation of deep clastic reservoirs, offering a robust framework for advancing the understanding of gas saturation in the face of complex geological and geophysical challenges. [ABSTRACT FROM AUTHOR]

Harmful marine spills, such as algae blooms and oil spills, damage ecosystems and threaten public health tremendously. Hence, an effective spill coverage and removal strategy will play a significant role in environmental protection. In recent years, low-cost water surface robots have emerged as a solution, with their efficacy verified at small scale. However, practical limitations, such as connectivity, scalability, and sensing and operation ranges significantly impair their large-scale use. To circumvent these limitations, we propose a novel asymptotic boundary shrink control strategy that enables collective coverage of a spill by autonomous robots featuring customized operation ranges. For each robot, a novel controller is implemented that relies only on local vision sensors with limited vision range. Moreover, the distributedness of this strategy allows any number of robots to be employed without inter-robot collisions. Finally, features of this approach including the convergence of robot motion during boundary shrink control, spill clearance rate, and the capability to work under limited ranges of vision and wireless connectivity are validated through extensive experiments with simulation. [ABSTRACT FROM AUTHOR]

Multirobot rendezvous control and coordination strategies have garnered significant interest in recent years because of their potential applications in decentralized tasks. In this paper, we introduce a coordinate-free rendezvous control strategy to enable multiple robots to gather at different locations (dynamic leader robots) by tracking their hierarchy in a connected interaction graph. A key novelty in this strategy is the gathering of robots in different groups rather than at a single consensus point, motivated by autonomous multipoint recharging and flocking control problems. We show that the proposed rendezvous strategy guarantees convergence and maintains connectivity while accounting for practical considerations such as robots with limited speeds and an obstacle-rich environment. The algorithm is distributed and handles minor faults such as a broken immobile robot and a sudden link failure. In addition, we propose an approach that determines the locations of rendezvous points based on the connected interaction topology and indirectly optimizes the total energy consumption for rendezvous in all robots. Through extensive experiments with the Robotarium multirobot testbed, we verified and demonstrated the effectiveness of our approach and its properties. [ABSTRACT FROM AUTHOR]