Abstract: A system for recovering hydrocarbons from a subterranean formation includes an upper tunnel extending through the formation. In addition, the system includes a lower tunnel extending through the formation below a portion of the upper tunnel. Further, the system includes a plurality of conduits extending from the upper tunnel through the formation to the lower tunnel. Still further, the system includes a plurality of wellbores extending from the lower tunnel into a hydrocarbon-bearing portion of the formation.

Abstract: A closed loop drilling fluids circulation system includes a first drilling fluid circulation system disposed at a first subterranean drill site. The first drilling fluid circulation system includes a supply tank for holding clean drilling fluid and a solids control device configured to separate solids from used drilling fluid. In addition, the system includes a central processing facility disposed at a location remote from the first drill site and configured to receive used drilling fluid from the solids control device and supply clean drilling fluid to the supply tank.

Abstract: A method for accessing a hydrocarbon reservoir in a subterranean formation from a subterranean tunnel system includes (a) drilling a first bore between an upper tunnel and a lower tunnel. In addition, the method includes (b) drilling a second bore downward from the lower tunnel.

Abstract: A rig for drilling a borehole from an underground tunnel includes a base assembly, a drilling assembly mounted to the base assembly, an upper frame assembly mounted to the drilling assembly above the base assembly, and a support hood coupled to the drilling assembly and positioned above the upper frame assembly. The support hood is configured to bear against a ceiling of the tunnel during drilling operations.

Abstract: A segmentation method comprises clustering spatial, intensity and volumetric shape index to automatically segment a medical lesion. The algorithm has the following steps: (1) calculating volumetric shape index (SI) for each voxel in the image; (2) combining the SI features with the intensity range and the spatial position (x, y, z) to form a 5-dimensional feature vector set; (3) grouping the 5-dimensional feature vector set into clusters; (4) employing a modified expectation-maximization algorithm (EM) considering not only spatial but also shape features on an intensity mode map from the clustering algorithm to merge the neighbouring regions or modes. The joint spatial-intensity-shape feature provides rich information for the segmentation of the anatomic structures of interest, such as lesions or tumours.

Abstract: A segmentation method comprises clustering spatial, intensity and volumetric shape index to automatically segment a medical lesion. The algorithm has the following steps: (1) calculating volumetric shape index (SI) for each voxel in the image; (2) combining the SI features with the intensity range and the spatial position (x, y, z) to form a 5-dimensional feature vector set; (3) grouping the 5-dimensional feature vector set into clusters; (4) employing a modified expectation-maximization algorithm (EM) considering not only spatial but also shape features on an intensity mode map from the clustering algorithm to merge the neighbouring regions or modes. The joint spatial-intensity-shape feature provides rich information for the segmentation of the anatomic structures of interest, such as lesions or tumours.

Abstract: In a method of performing CAD analysis of a medical image, the medical image volume is processed in a pre-processing module to generate intermediate data, and the intermediate data is processed by a filtering module to generate CAD result data. The different modules may be executed by different processing nodes or devices, enabling a variety of different system architectures. The intermediate data may be stored in accordance with a standard, such as the Digital Imaging and Communications in Medicine (DICOM) standard. For instance, the intermediate data may be stored in accordance with the DICOM secondary capture image information object definition (SCI IOD) format. The CAD result data may be displayed on a viewer workstation, for example.