| With the development of easily exploitable oil and gas resources in major domestic oilfields entering the late stage,oil exploration projects are gradually moving towards mature stage.The main force direction of oil exploration technology turns to complex oil and gas reservoirs,which also has higher requirements for the development of drilling guidance engineering in China.It is clearly pointed out in the "14th Five-year Plan outline" issued by the state that the field of oil and gas exploration and development should strengthen original and leading technology research,promote the intelligent upgrading of oil and gas fields,and build a community of shared future in cyberspace.Intelligent guided drilling technology is of great significance to the steady development of the petroleum industry and the realization of the national long-term goal of 2035.LWD guidance technology is the mainstream drilling guidance technology in the world at present.This technology can realize downhole data acquisition and processing when the formation is just or less affected by invasion,and send formation information parameters back to the surface for drilling decision analysis.However,due to the complex geological conditions,it is difficult to ensure the reliability of formation data and the timeliness of return.At the same time,the key steps of drilling decision are taken by manual experts,which may lead to human error.Based on the above problems,this study abstractions complex geological conditions into a simulated formation environment with distributed obstacles,and proposes an intelligent drilling guide technology integrating spatial attention mechanism.The technology can control the whole process of the bit to make autonomous drilling decisions,reasonable avoidance of obstacles to reach the target formation.Main work is summarized as follows:(1)An intelligent drilling guidance system based on deep reinforcement learning framework is proposed.The system can observe the formation information by controlling the guide bit to learn,and extract the formation features with the attention mechanism to guide the drilling action of the bit.In this paper,each link of the system is defined in detail,including the overall framework of drilling guide system,drilling encounter data processing,drilling guide algorithm network structure,drilling guide effect evaluation system,etc.The experimental results show that the drilling guidance system can guide the bit to drill the target zone in real time while avoiding obstacles intelligently,and the drilling guidance effect is better than that of the control group in the simulated formation environment;(2)In order to improve the obstacle avoidance ability of guided drilling method and to meet higher requirements of drilling effect,a spatial domain intelligent guided drilling algorithm is proposed.This algorithm expands the detection range of formation information from two-dimensional to three-dimensional,further extracts spatial formation features by spatial attention mechanism,and reconstructs obstacle penalty function by artificial potential field method to guide drilling decisions.Through a series of comparative experiments,it can be found that compared with the intelligent drilling guide algorithm designed in the first step,the spatial domain intelligent drilling guide algorithm has better drilling performance and obstacle avoidance performance in the simulated formation environment;(3)The intelligent drilling simulation system is constructed.The system combines the three-dimensional formation environment with the intelligent drilling guidance model.The user can build the simulation formation environment by inputting the corresponding formation information parameters and choose different drilling guidance algorithms independently.The system displays the training situation of intelligent drilling guidance model in the simulated formation environment in real time from three dimensional drilling environment,two dimensional formation profile and attention mechanism annotation. |
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