Real-time monitoring of wellbore stability during drilling is crucial for the early detection of instability and timely interventions.The cause and type of wellbore instability can be identified by analyzing the dropp...Real-time monitoring of wellbore stability during drilling is crucial for the early detection of instability and timely interventions.The cause and type of wellbore instability can be identified by analyzing the dropped blocks brought to the surface by the drilling fluid,enabling preventive measures to be taken.In this study,an image capture system with fully automated sorting and 3D scanning was developed to obtain the complete 3D point cloud data of dropping blocks.The raw data obtained were preprocessed using methods such as format conversion,down sampling,coordinate transformation,statistical filtering,and clustering.Feature extraction algorithms,including the principal component analysis bounding box method,triangular meshing method,triaxial projection method,local curvature method,and model segmentation projection method,were employed,which resulted in the extraction of 32 feature parameters from the point cloud data.An optimal machine learning algorithm was developed by training it with 10 machine learning algorithms and the block data collected in the field.The XGBoost algorithm was then used to optimize the feature parameters and improve the classification model.An intelligent,fully automated feature parameter extraction and classification system was developed and applied to classify the types of falling blocks in 12 sets of drilling field and laboratory experiments and to identify the causes of wellbore instability.An average accuracy of 93.9%was achieved.This system can thus enable the timely diagnosis and implementation of preventive and control measures for wellbore instability in the field.展开更多
Compressed stabilized earth blocks are the innovation of building materials replacing the earth blocks commonly called adobe. Common stabilizers (cement and lime) have been found to be expensive and harmful to the env...Compressed stabilized earth blocks are the innovation of building materials replacing the earth blocks commonly called adobe. Common stabilizers (cement and lime) have been found to be expensive and harmful to the environment. Finding a natural, available, environmentally friendly stabilizer is vital. The objective of this study was therefore to assess the effects of gum Arabic (GA) as binder on the durability properties of laterite blocks. Compressed laterite blocks were stabilized with 2% and 6% respectively as total percentage of binders in the blocks (cement and/or GA). The results showed that GA improved the abrasion and drop resistances of compressed blocks. It has been found that the abrasion resistance of compressed blocks increased with the increase of GA content and the decrease of cement content. For instance, the mass abraded away of blocks stabilized with cement only was reduced up to 95.18% when GA was used to partially replace cement. As for drop test, the higher the content of GA the higher the resistance of blocks to drop.展开更多
This paper describes the connection establishment of label switched paths (LSP) in IP/MPLS over optical networks. Our investigations on two typical network topologies show that the number of add/drop ports of OXCs has...This paper describes the connection establishment of label switched paths (LSP) in IP/MPLS over optical networks. Our investigations on two typical network topologies show that the number of add/drop ports of OXCs has a significant impact on the LSP blocking performance.展开更多
基金supported by the Scientific research and technology development projects of CNPC“Research on Key Technologies and Equipment for Drilling and Completion of 10000-m Ultra-deep Oil and Gas Resources”(No.2022ZG06)“Development of a Complete Set of 70 MPa Intelligent Managed Pressure Drilling Equipment”(No.2024ZG35).
文摘Real-time monitoring of wellbore stability during drilling is crucial for the early detection of instability and timely interventions.The cause and type of wellbore instability can be identified by analyzing the dropped blocks brought to the surface by the drilling fluid,enabling preventive measures to be taken.In this study,an image capture system with fully automated sorting and 3D scanning was developed to obtain the complete 3D point cloud data of dropping blocks.The raw data obtained were preprocessed using methods such as format conversion,down sampling,coordinate transformation,statistical filtering,and clustering.Feature extraction algorithms,including the principal component analysis bounding box method,triangular meshing method,triaxial projection method,local curvature method,and model segmentation projection method,were employed,which resulted in the extraction of 32 feature parameters from the point cloud data.An optimal machine learning algorithm was developed by training it with 10 machine learning algorithms and the block data collected in the field.The XGBoost algorithm was then used to optimize the feature parameters and improve the classification model.An intelligent,fully automated feature parameter extraction and classification system was developed and applied to classify the types of falling blocks in 12 sets of drilling field and laboratory experiments and to identify the causes of wellbore instability.An average accuracy of 93.9%was achieved.This system can thus enable the timely diagnosis and implementation of preventive and control measures for wellbore instability in the field.
文摘Compressed stabilized earth blocks are the innovation of building materials replacing the earth blocks commonly called adobe. Common stabilizers (cement and lime) have been found to be expensive and harmful to the environment. Finding a natural, available, environmentally friendly stabilizer is vital. The objective of this study was therefore to assess the effects of gum Arabic (GA) as binder on the durability properties of laterite blocks. Compressed laterite blocks were stabilized with 2% and 6% respectively as total percentage of binders in the blocks (cement and/or GA). The results showed that GA improved the abrasion and drop resistances of compressed blocks. It has been found that the abrasion resistance of compressed blocks increased with the increase of GA content and the decrease of cement content. For instance, the mass abraded away of blocks stabilized with cement only was reduced up to 95.18% when GA was used to partially replace cement. As for drop test, the higher the content of GA the higher the resistance of blocks to drop.
文摘This paper describes the connection establishment of label switched paths (LSP) in IP/MPLS over optical networks. Our investigations on two typical network topologies show that the number of add/drop ports of OXCs has a significant impact on the LSP blocking performance.
