Anisotropic Modeling with Geometric Multigrid Preconditioned Finite Element Method

Formation anisotropy in complicated geophysical environments can have a significant impact on data interpretation of electromagnetic surveys. To facilitate full 3D modeling of arbitrary anisotropy, we have adopted an h-version geometric multigrid preconditioned finite-element method based on vector basis functions. By using a structured mesh, instead of an unstructured one, our method can conveniently construct the restriction and prolongation operators for multigrid implementation, and then recursively coarsen the grid with the F-cycle coarsening scheme. The geometric multigrid method is used as a preconditioner for the biconjugate-gradient stabilized method to efficiently solve the linear system resulting from the finite-element method. Our method avoids the need of interpolation for arbitrary anisotropy modeling as in Yee’s grid-based finite-difference method, and it is also more capable of large-scale modeling with respect to the p-version geometric multigrid preconditioned finite-element method. A numerical example in geophysical well logging is included to demonstrate its numerical performance. Our h-version geometric multigrid preconditioned finite-element method is expected to help formation anisotropy characterization with electromagnetic surveys in complicated geophysical environments.

Fluorescent Microspheres Method Efficiency in Horizontal Wells with Gas Condensate Liquid

The proportion of hard-to-recover reserves is currently increasing and reached more than 65% of total conventional hydrocarbon reserves. This results in an increasing number of horizontal wells put into operation. When evaluating the resource recovery efficiency in horizontal wells, and, consequently, the effectiveness of the development of gas condensate field, the key task is to evaluate the well productivity. To accomplish this task, it is necessary to obtain the reservoir fluid production profile for each interval. Conventional well logging methods with proven efficiency in vertical wells, in case of horizontal wells, will require costly asset-heavy applications such as coiled tubing, downhole tractors conveying well logging tools, and Y-tool bypass systems if pump is used. In addition, the logging data interpretation in the case of horizontal wells is less reliable due to the multiphase flow and variations of the fluid flow rate. The fluorescent-based nanomaterial production profiling surveillance technology can be used as a viable solution to this problem, which enables cheaper and more effective means of the development of hard-to-recover reserves. This technology assumes that tracers are placed downhole in various forms, such as marker tapes for lower completions, markers in the polymer coating of the proppant used for multi-stage hydraulic fracturing, and markers placed as fluid in fracturing fluid during hydraulic fracturing or acid stimulation during bottom-hole treatment. The fundamental difference between nanomaterial tracers production profiling and traditional logging methods is that the former offers the possibility to monitor the production at frac ports in the well for a long period of time with far less equipment and manpower, reduced costs, and improved HSE.

GPU UTILIZATION IN GEOPROCESSING BIG GEODATA: A REVIEW

The expansion of data collection from remote sensing and other geographic data sources, as well as from other technology such as cloud, sensors, mobile, and social media, have made mapping and analysis more complex. Some geospatial applications continue to rely on conventional geospatial processing, where limitation on computation capabilities often lacking to attain significant data interpretation. In recent years, GPU processing has improved far more GIS applications than using CPU alone. As a result, numerous researchers have begun utilising GPUs for scientific, geometric, and database computations in addition to graphics hardware use. This paper summarizes parallel processing concept and architecture, the development of GPU geoprocessing for big geodata ranging from remote sensing and 3D modelling to smart cities studies. This paper also addresses the GPU future trends advancement opportunities with other technologies, machine learning, deep learning, and cloud-based computing.

Comparison of 3D, 2D, and 1D Magnetotelluric Inversion Results on the Example of Data from Fore-Sudetic Monocline

This study’s main objective is to better define and understand results for the most commonly used inversion algorithms in magnetotelluric data interpretation as part of geological exploration of the region of the Dolsk fault and the Odra fault. The data obtained from the eastern part of Fore-Sudetic Monocline measurements were used to describe the boundaries of lithospheric blocks (terranes) and recognize their origin. The magnetotelluric (MT) soundings were carried out to achieve this goal. There were conducted 51 soundings on five quasiparallel profiles. That allows constructing a quasiregular mesh in the area of the Fore-Sudetic Monocline. This arrangement of the measuring grid allowed reducing the influence of the largest sources of disturbances on MT data. 1D and 2D models were created by using the inverse algorithms. The models were prepared for each profile separately. Further, parallel (ModEM) 3D inversion codes were applied. The area where the investigation was done involves the region of the Dolsk fault and the Odra fault. These zones are essential geologic borders of a regional nature, and they pull apart the crust blocks with different origins. It was vitally needed to correctly identify the crust and upper mantle structure around a part of the Fore-Sudetic Monocline. The paper shows how these key features of the geological structures are revealed using 1D, 2D, and 3D algorithms.

The impact of methodology on the reproducibility and rigor of DNA methylation data

Epigenetic modifications are crucial for normal development and implicated in disease pathogenesis. While epigenetics continues to be a burgeoning research area in neuroscience, unaddressed issues related to data reproducibility across laboratories remain. Separating meaningful experimental changes from background variability is a challenge in epigenomic studies. Here we show that seemingly minor experimental variations, even under normal baseline conditions, can have a significant impact on epigenome outcome measures and data interpretation. We examined genome-wide DNA methylation and gene expression profiles of hippocampal tissues from wild-type rats housed in three independent laboratories using nearly identical conditions. Reduced-representation bisulfite sequencing and RNA-seq respectively identified 3852 differentially methylated and 1075 differentially expressed genes between laboratories, even in the absence of experimental intervention. Difficult-to-match factors such as animal vendors and a subset of husbandry and tissue extraction procedures produced quantifiable variations between wild-type animals across the three laboratories. Our study demonstrates that seemingly minor experimental variations, even under normal baseline conditions, can have a significant impact on epigenome outcome measures and data interpretation. This is particularly meaningful for neurological studies in animal models, in which baseline parameters between experimental groups are difficult to control. To enhance scientific rigor, we conclude that strict adherence to protocols is necessary for the execution and interpretation of epigenetic studies and that protocol-sensitive epigenetic changes, amongst naive animals, may confound experimental results.

An electrodynamics model for Data Interpretation and Numerical Analysis of ionospheric Missions and Observations (DINAMO)

We introduce a new numerical model developed to assist with Data Interpretation and Numerical Analysis of ionospheric Missions and Observations (DINAMO). DINAMO derives the ionospheric electrostatic potential at low- and mid-latitudes from a two-dimensional dynamo equation and user-specified inputs for the state of the ionosphere and thermosphere (I–T) system. The potential is used to specify the electric fields and associated F-region E × B plasma drifts. Most of the model was written in Python to facilitate the setup of numerical experiments and to engage students in numerical modeling applied to space sciences. Here, we illustrate applications and results of DINAMO in two different analyses. First, DINAMO is used to assess the ability of widely used I–T climatological models (IRI-2016, NRLMSISE-00, and HWM14), when used as drivers, to produce a realistic representation of the low-latitude electrodynamics. In order to evaluate the results, model E × B drifts are compared with observed climatology of the drifts derived from long-term observations made by the Jicamarca incoherent scatter radar. We found that the climatological I–T models are able to drive many of the features of the plasma drifts including the diurnal, seasonal, altitudinal and solar cycle variability. We also identified discrepancies between modeled and observed drifts under certain conditions. This is, in particular, the case of vertical equatorial plasma drifts during low solar flux conditions, which were attributed to a poor specification of the E-region neutral wind dynamo. DINAMO is then used to quantify the impact of meridional currents on the morphology of F-region zonal plasma drifts. Analytic representations of the equatorial drifts are commonly used to interpret observations. These representations, however, commonly ignore contributions from meridional currents. Using DINAMO we show that that these currents can modify zonal plasma drifts by up to ~ 16 m/s in the bottom-side post-sunset F-region, and up to ~ 10 m/s between 0700 and 1000 LT for altitudes above 500 km. Finally, DINAMO results show the relationship between the pre-reversal enhancement (PRE) of the vertical drifts and the vertical shear in the zonal plasma drifts with implications for equatorial spread F.

Analisis Presepsi Guru Tentang Pembelajaran Ilmu Pengetahuan Sosial Sekolah Dasar Berbasis Lingkungan

Environmental-based elementary school social science learning is a very important lesson in building a sense of concern for students about the surrounding environment both at school and in the community. However, teacher perceptions are needed in understanding environmental-based learning in order to apply it to classroom learning. Therefore, this study aims to analyze the teacher's perception of environmental- based Social Science learning. This research was conducted through surveys and giving questionnaires to school teachers, the sample of this study was 25 respondents from SDN Watugolong 02 teachers. The data of this study were analyzed using data interpretation analysis. The results of this study indicate that teachers' perceptions are positive about environmental-based Social Science-based learning with a percentage of 60% of 25 respondents and teachers give reasons that this learning will have a positive impact on elementary school students. In conclusion, the teacher's perception of environmental- based social studies learning is very positive. The positive thing in question is to build the character of students to foster a sense of care for the environment such as throwing garbage in its place.

Taking action to advance the study of race and ethnicity: the Women’s Health Initiative (WHI)

Abstract“Race” and “ethnicity” are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as “the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by “race,” have been largely ignored in medical research. The Women’s Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020–2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include “race” and/or “ethnicity” in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant’s self-identified “race” and “ethnicity”, and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.