Abstarct: Business process management includes simulating, analyzing and planning a business system. Today, information technology is inclined to workflow management. A workflow management system is a computer system that manages and defines a series of tasks within an organization to produce a final outcome or outcomes. In last decade, workflow technology was used in complex information system. For simulating workflow system, process model is used. Constructing a process model from event logs is one of important field in business process management. This thesis survey useful information in event log for constructing a process model. In other words, the goal of this thesis is to investigate minimum number of logs required to construct a process model. Petri net is one of the important and convenient models in this area and this thesis used this model to investigate novel solution. There are many algorithms to construct process model from event log, by attention to workflow model. Completeness event log is very important for construct process model. Whatever knowledge is extracted from event log be more complete, process model will be constructed more accurate and management if system will be better. But extra information in event logs made reduction efficiency in discover algorithm. So consider an optimum event logs made discover algorithm more efficiency. In this thesis, we consider α-algorithm as baxse algorithm and proposed algorithm get optimum event logs baxsed α-algorithm