Research On Real - Time Optimization Method Of Drilling Parameters

Nowadays, problems in drilling deep well needed urgently to be solved are low Rate of Penetration and long time of drilling. Experts abroad have researched successfully in the field of real-time drilling optimization. National Science and Technology Major Project set up a branch (Contract Number:2011ZX05021-006) named "Drilling System of real time monitoring and decision making" for analyzing and dealing with the low efficiency in drilling deep well. As a part of the branch, this paper studied on monitoring parameters and establishing models in real-time with the data of logging.Based on the traditional drilling model, the research studied on optimizing parameters in real-time drilling without data of logging. It established the drilling speed model via the method of inversion, which only build up with data of real-time logging and overcome the defect of traditional five-points method. Verified by examples, the coincidence rate achieved81.03%on average between the prediction results of inversion method and the actually rate of penetration. At the same time, add the diameter factors into traditional drilling speed model, expanding the scope of utilization. Using this new model, even if the bit diameter changed, the prediction results still maintain the precision.Based on the relationship between bit grading, rate of penetration, and the variation of ROP along with the footage of bit, designed the main to set up the tooth wear number real-time without the data of logging. This method to establish the bit wear profile overcome the defect of traditional method which have to dependent on the data of well nearby. Evaluating dynamical utilization of bit and provide the basis for accurate judgment of drilling based on the wear profile established real-time. Built PDC bit tooth wear model through using multiple regression method. Without LWD data, the research established the model of drill ability through combining the ROP model and the principle of drill ability test. This model can establish the profile of drill ability in drilling process. Compared with experimental data, average coincidence rate were more than80%. Moreover, this method are able to calculate the drill ability to build models in real-time without core test, which evaluated and optimized dynamically bits in real-time. Monitored the low working efficiency and analyzed the reason through hydraulic and mechanical parameters, theory of specific energy, optimizing parameters, evaluation of bit in real-time.With all above research, has formed a series of theory for optimizing drilling work, only using logging data real-time and parameters on the working spot. Designed and developed the drilling parameters monitor and optimizing decision system. Based on SQL Server2008database platform and Visual Studio2010, developed the real-time optimization software.The outcome of testing the system with data on well L2-6had a highly coincidence with real performance, which meant the system is truly useful in the drilling deep well.