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A geopressure interpretation technique known as the seismic velocity method is a common workflow in which shale compaction functions are characterized at offset control wells, matched to interval seismic velocities, and then used to predictively calculate geopressure away from well control. The seismic velocity method is used to interpret the expected geopressure profile at the Deep Blue subsalt exploration well in Green Canyon 723 in the deep water Gulf of Mexico. The Deep Blue prospect is distinct from other prospects in the play fairway in that the prospective section is overlain by a salt withdrawal minibasin, whereas the offsetting fields are positioned either along the flanks of minibasins or under a thick allochthonous salt canopy. Predrill geopressure interpretations using numerous tomographic imaging velocity data sets shows a large degree of consistency with the magnitude of geopressure encountered in offsetting supra salt and subsalt fields. Results from the Deep Blue 1 exploration well indicate the predrill geopressure interpretation from interval seismic velocities failed to anticipate the extreme degree overpressure encountered in the subsalt section of the well due to poor deep velocity resolution and an “unloaded” compaction signature. The magnitude of overpressure in the primary section is attributed to the emplacement of an unconformable halokinetic sequence over the primary subsalt basin. An interpretive paradigm is described in which the Deep Blue pressure cell is created through two halokinetic episodes: (1) rapid progradation of a salt canopy followed by (2) subsequent salt withdrawal and emplacement of an overlying minibasin. The linkage between halokinetic sequences, burial history, and the development of overpressure can be used to predictively characterize subsalt geopressure environments.

Dynamic and real-time MRI (rtMRI) of human speech is an active field of research, with interest from both the linguistics and clinical communities. At present, different research groups are investigating a range of rtMRI acquisition and reconstruction approaches to visualise the speech organs. Similar to other moving organs, it is difficult to create a physical phantom of the speech organs to optimise these approaches; therefore, the optimisation requires extensive scanner access and imaging of volunteers. As previously demonstrated in cardiac imaging, realistic numerical phantoms can be useful tools for optimising rtMRI approaches and reduce reliance on scanner access and imaging volunteers. However, currently, no such speech rtMRI phantom exists. In this work, a numerical phantom for optimising speech rtMRI approaches was developed and tested on different reconstruction schemes. The novel phantom comprised a dynamic image series and corresponding k-space data of a single mid-sagittal slice with a temporal resolution of 30 frames per second (fps). The phantom was developed based on images of a volunteer acquired at a frame rate of 10 fps. The creation of the numerical phantom involved the following steps: image acquisition, image enhancement, segmentation, mask optimisation, through-time and spatial interpolation and finally the derived k-space phantom. The phantom was used to: (1) test different k-space sampling schemes (Cartesian, radial and spiral); (2) create lower frame rate acquisitions by simulating segmented k-space acquisitions; (3) simulate parallel imaging reconstructions (SENSE and GRAPPA). This demonstrated how such a numerical phantom could be used to optimise images and test multiple sampling strategies without extensive scanner access.

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