Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thic...Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.展开更多
In the complex and variable deep-sea environment,the compensation control of ship motion ensures the safety and efficiency of equipment installation and transportation in offshore wind farms.However,the ship motion po...In the complex and variable deep-sea environment,the compensation control of ship motion ensures the safety and efficiency of equipment installation and transportation in offshore wind farms.However,the ship motion posture compensation control system is severely affected by uncertainties,which significantly impact the accuracy of compensation control.In this paper,we propose a ship three-degree-of-freedom(3-DoF)motion posture stabilization control method based on the DTW-LSTM-MATD3 algorithm.We use the multi-agent twin delayed deep deterministic policy gradient(MATD3)to control a platform with six electric cylinders to achieve stable control.However,owing to random noise affecting the ship’s motion posture,we use a dynamic time warping(DTW)algorithm to distinguish between high-frequency noise and low-frequency tracking signals.Further,we embed a long short-term memory(LSTM)network into the MATD3 network to better align the Critic network’s training with the true Q-value.We use a combined reward function to enhance the agent’s exploration capability in complex dynamic environments.Finally,verification was conducted under sixth-level,abrupt sea conditions with high-frequency noise,as well as under real abrupt sea conditions,and a generalization test was also carried out.Simulation results show that the proposed DTW-LSTM-MATD3 method has great compensation control ability.展开更多
基金Supported by the National Natural Science Foundation of China(42272110)CNPC-China University of Petroleum(Beijing)Strategic Cooperation Project(ZLZX2020-02).
文摘Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.
基金supported by the National Natural Science Foundation of China(No.52105466).
文摘In the complex and variable deep-sea environment,the compensation control of ship motion ensures the safety and efficiency of equipment installation and transportation in offshore wind farms.However,the ship motion posture compensation control system is severely affected by uncertainties,which significantly impact the accuracy of compensation control.In this paper,we propose a ship three-degree-of-freedom(3-DoF)motion posture stabilization control method based on the DTW-LSTM-MATD3 algorithm.We use the multi-agent twin delayed deep deterministic policy gradient(MATD3)to control a platform with six electric cylinders to achieve stable control.However,owing to random noise affecting the ship’s motion posture,we use a dynamic time warping(DTW)algorithm to distinguish between high-frequency noise and low-frequency tracking signals.Further,we embed a long short-term memory(LSTM)network into the MATD3 network to better align the Critic network’s training with the true Q-value.We use a combined reward function to enhance the agent’s exploration capability in complex dynamic environments.Finally,verification was conducted under sixth-level,abrupt sea conditions with high-frequency noise,as well as under real abrupt sea conditions,and a generalization test was also carried out.Simulation results show that the proposed DTW-LSTM-MATD3 method has great compensation control ability.
