Hybrid Intelligent Systems
Protocol Moderators as Active Middle-Agents in Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems
Agent-Based Hybrid Intelligent Systems
Agent-Based Hybrid Intelligent Systems
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Petroleum reservoir characterisation is a new practical technology for synthetically studying and evaluating petroleum reservoir. Reservoir properties are a set of parameters which are usually used to recognise the geologic information in spatial variability. Lithology, permeability, and porosity are widely used to determine the oil well or field production rate of hydrocarbon. Since the complexity of the underground geology, a single intelligent technique can not solve the complicated and elaborate geologic problems. It is necessary that those geologic problems are synthetically studied by combining the multiple intelligent techniques. We employed neural networks, fussy algorithms, expert system, etc. to solve complicated lithology identification, porosity prediction, permeability estimation, and well logs curve-digitizing in this paper. We analyse and design an agent-based hybrid intelligent system by following MAHIS (Methodology for constructing Agent-based Hybrid Intelligent System). The system starts with the digitisation of well logs parameter graphs based on expert system. Identification of lithology and prediction of porosity and permeability can be conducted by using hybrid intelligent techniques. Four intelligent technique agents (complicated lithology identification with parthenogenetic algorithm, porosity prediction with neural network, permeability estimation with fuzzy neural network, and well logs curve-digitizing with expert system) has been integrated.