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High accuracy capillary network representation in digital rock reveals permeability scaling functions.

ABSTRACT: Permeability is the key parameter for quantifying fluid flow in porous rocks. Knowledge of the spatial distribution of the connected pore space allows, in principle, to predict the permeability of a rock sample. However, limitations in feature resolution and approximations at microscopic scales have so far precluded systematic upscaling of permeability predictions. Here, we report fluid flow simulations in pore-scale network representations designed to overcome such limitations. We present a novel capillary network representation with an enhanced level of spatial detail at microscale. We find that the network-based flow simulations predict experimental permeabilities measured at lab scale in the same rock sample without the need for calibration or correction. By applying the method to a broader class of representative geological samples, with permeability values covering two orders of magnitude, we obtain scaling relationships that reveal how mesoscale permeability emerges from microscopic capillary diameter and fluid velocity distributions.

SUBMITTER: Neumann RF

PROVIDER: S-EPMC8206086 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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High accuracy capillary network representation in digital rock reveals permeability scaling functions.

Neumann Rodrigo F RF Barsi-Andreeta Mariane M Lucas-Oliveira Everton E Barbalho Hugo H Trevizan Willian A WA Bonagamba Tito J TJ Steiner Mathias B MB

Scientific reports 20210615 1

Permeability is the key parameter for quantifying fluid flow in porous rocks. Knowledge of the spatial distribution of the connected pore space allows, in principle, to predict the permeability of a rock sample. However, limitations in feature resolution and approximations at microscopic scales have so far precluded systematic upscaling of permeability predictions. Here, we report fluid flow simulations in pore-scale network representations designed to overcome such limitations. We present a nov ...[more]

PMID: 34131175

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Project description:BackgroundDigital templating systems foster patient-specific measurements for preoperative planning.Questions/purposesWe aim (1) to verify the accuracy of a templating system, (2) to describe the effects of scaling marker position on the accuracy of digital templating of the hip, and (3) to provide a practical guide for scaling marker position using patient body mass index (BMI).MethodsA scaling sphere was placed in five positions along the anterior-posterior axis of an acetabular implant and pelvis phantom, and x-rays were obtained. Each radiograph was templated for the acetabular component and recorded. A retrospective review identified CT scans of preoperative hip arthroplasty cases. The center of the greater trochanter was calculated from these CT scans as the percent distance from the anterior thigh and recorded with the patient's BMI.ResultsBy centering the scaling sphere on the acetabular component, an accurate cup size was achieved. A difference of 3.5 cm in sphere placement resulted in a full cup size magnification error. Positioning the scaling sphere at the level of the pubic symphysis resulted in a difference of four cup sizes. This patient population had an average BMI of 28.72 kg/m2 (standard deviation 6.26 kg/m2) and an average position of the center of the greater trochanter of 51% (standard deviation of 6%) from the anterior surface of thigh.ConclusionsDigital templating relies on scaling marker position to accurately estimate implant size. Based on the findings in this study, scaling markers for hip imaging should be placed laterally, mid-thigh in the anterior-posterior direction for patients with a BMI between 25 and 40 kg/m2. If abnormal hip anatomy or extremes of BMI are discovered, then scaling sphere positioning should be optimized on a case-by-case basis. Digital templating systems for total hip arthroplasty must use precisely placed scaling markers at the level of the hip joint to allow for accurate implant size estimation.

Dataset Information

High accuracy capillary network representation in digital rock reveals permeability scaling functions.

Publications

High accuracy capillary network representation in digital rock reveals permeability scaling functions.

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