The Study And Implement About The Algorithm Of Reservoir Modeling Constrained By Seismic Data

The reservoir geological modeling technology is a high and new technology in recent decades and it is an important component of reservoir description. It makes the detailed description and modeling of reservoir hydrocarbons come true and it plays an important role in improving reservoir management and petroleum recovery efficiency and output. The normal reservoir modeling method use well log data to model. Reservoir modeling constrained by seismic data is a method that combines well log data with seismic data. It can exert their character and achieve physical property parameter that have a high precision. Reservoir modeling constrained by seismic data has been become a trend in reservoir modeling.Reservoir modeling constrained by seismic data has many methods and each method has its own character. This paper specially focuses on the reservoir modeling constrained by seismic data and explains the advantage of each method and scope of application. According to the needs of the project, the geostatistical inversion algorithm is specially studied. This paper also designs the geostatistical inversion algorithm and displays the algorithm flow. By using the object-oriented analysis and object-oriented design, We realize the geostatistical inversion algorithm. We also use instance data to validate this algorithm. The main innovations and contents of this paper are read as follows:Firstly, this paper is based on the basic theory of reservoir modeling. The theory and the method in reservoir modeling constrained by seismic data are also studied. The paper clarifies the background and the method of reservoir modeling constrained by seismic data.Secondly, this paper specially focuses on the geostatistical inversion algorithm in reservoir modeling constrained by seismic data. This paper uses object-oriented thinking to analyse and design the geostatistical inversion algorithm. It improves the algorithm's maintainability and reusability. How to choose the wavelet and the best result and how to compute the convolution are also studied. This paper gives the solutions to these problems.Thirdly, the geostatistical inversion system has been analysised and designed and the framework is set up. Basing on the VS2005 development pad, we use C++, Qt and mixed-language programming to realize this system. By using these technologies, we improve code reused and shorten the programming periods. It is beneficial to the future maintenance and upgrades of the system.Finally, the observed data of an oil field are applied. It validates this algorithm. By changing parameters in the algorithm, we get many different results. The impact of different parameter are also studied.