Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method to delineate salt-dome structures by tracking manually labeled boundaries through seismic volumes.  first extract texture features from boundary regions using the tensor-based subspace learning method. Then,  utilize one seismic attribute, the gradient of texture (GoT), as a constraint on the tracking process. Using texture features and GoT maps,  can identify tracked points and optimally connect them to synthesize the boundaries. The proposed method is evaluated using real-world seismic data and experimental results show that it outperforms the state of the art in accuracy, robustness, and computational efficiency.
['Zhen Wang', 'Zhiling Long', 'Ghassan AlRegib']
I am writing a research paper on a idea Tensor-based subspace learning for tracking salt-dome boundaries constrained by seismic attributes
[{"from": "human", "value": "I am writing a research paper on a idea Tensor-based subspace learning for tracking salt-dome boundaries constrained by seismic attributes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method to delineate salt-dome structures by tracking manually labeled boundaries through seismic volumes.  first extract texture features from boundary regions using the tensor-based subspace learning method. Then,  utilize one seismic attribute, the gradient of texture (GoT), as a constraint on the tracking process. Using texture features and GoT maps,  can identify tracked points and optimally connect them to synthesize the boundaries. The proposed method is evaluated using real-world seismic data and experimental results show that it outperforms the state of the art in accuracy, robustness, and computational efficiency."}]