Dynamics and Geometry Effects on the Capillary Flows in Porous Media for Enhanced Oil Recovery

The continuing depletion of light oil supplies and the rapidly growing demand for energy are forcing oil and gas companies to explore unconventional oil extraction techniques. The structure and flow rate implies an impact on the trapping and mobilization of oil in the reservoir. This article studies the effect of pore geometry and dynamics on water-oil displacement as a two-phase flow system. The pore geometries of sandstone were extracted using the non-destructive 3D micro computational tomography (micro-CT) technique. Two-phase flow simulations were performed using COMSOL Multiphysics on the micro-CT images to show the effect of the capillary number and the flow pattern. Velocity and relative permeability of the non-wetting phase at different points of the porous structure was computed. The effect of viscosity of wetting fluid on the pore structure was also studied to evaluate the parameters affecting enhanced oil recovery (EOR).

Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer (Preprint)

BACKGROUND There is an unmet need for non-invasive imaging markers that help identify the aggressive sub-type(s) of pancreatic ductal adenocarcinoma (PDAC) at diagnosis and to evaluate the efficacy of therapy prior to tumor reduction. In the last few years, there are two major developments that can have a significant impact in developing imaging biomarkers for PDAC: I) hyperpolarized metabolic Magnetic Resonance (HP-MR) and II) applications of Artificial Intelligence (AI). OBJECTIVE Our objective is to discuss these two exciting but independent developments in the realm of PDAC imaging and detection from the available literature to date. METHODS A systematic review following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines was conducted. The manuscript addressing the utilization of Hyperpolarization-based magnetic resonance (HP-MR) and/or Artificial Intelligence for early detection, assessing aggressiveness, and interrogating the early efficacy of therapy in PDAC cited in recent clinical guidelines were extracted from PubMed and Google Scholar. The studies were reviewed by reviewers following the exclusion and inclusion criteria and grouped based on the utilization of HP-MR and AI in PDAC diagnosis. RESULTS HP-MR increases the sensitivity of conventional MR by over 10,000-fold enabling real-time metabolic measurements. The utility of HP-MR in PDAC has been verified in several preclinical studies, but has not been proven in a clinical setting. In contrast, AI applications in PDAC imaging in the clinic are nascent, but mostly limited to Computational Tomography (CT) imaging datasets. CONCLUSIONS Combining AI and HP-MR applications may lead to the development of real-time biomarkers of early detection, assessing aggressiveness, and interrogating the early efficacy of therapy in PDAC.

Proptosis with Increased Orbital Fat in an Obese Patient

Computational tomography (CT) is a well-documented modality in the workup of proptosis. We present a case of proptosis due to increased orbital fat in an obese patient. We review the literature to discuss the most likely causes of increased orbital fat, and we discuss the utility of CT imaging in assessing this pathology.

A new tool for 3D segmentation of computed tomography data: Drishti Paint and its applications

Computational tomography is more and more widely used in many fields for its non-destructive and high-resolution in detecting internal structures of the samples. 3D segmentation of computed tomography data, which sheds light into internal features of target objects, is increasingly gaining in importance. However, how to efficiently and precisely reconstruct computed tomography data and better represent the data remains a hassle. Here, using a set of scan data of a fossil fish as a case study, we present a new release of open-source volume exploration, rendering, and 3D segmentation software, Drishti v2.6.6, and its protocol for performing 3D segmentation and other advanced applications. We provide new toolsets and workflow to segment computed tomography data thus benefit the scientific community with more accurate and precise digital reconstruction, 3D modelling and 3D printing results. Our procedure is widely applicable not only in palaeontology, but also in biological, medical, and industrial researches, and can be used as a framework to segment computed tomography and other forms of volumetric data from any research field.

Experimental hydraulic fracturing of Berea sandstone under triaxial stress state

In this work, a newly designed experimental setup is used to perform in-lab fracking under controlled triaxial loading on cylindrical cores of Berea sandstone. Fracking tests are conducted at 10 MPa confining pressure, with vertical compressive loading, as well as two horizontal stresses that simulate reservoir triaxial stress state. Multiple injection scenarios are tested to investigate the effect of the pore fluid injection conditions on the fracking and failure mechanisms. In-situ micro-seismic monitoring via eight acoustic emissions sensors is used for logging the fracking events evolution with time. Post-experimental characterization included computational tomography (CT) scanning to characterize the resulting fracture patterns.