A5013265039- Reservoir Engineering and Simulation Methods
- Hydraulic Fracturing and Reservoir Analysis
- CO2 Sequestration and Geologic Interactions
- Hydrocarbon exploration and reservoir analysis
- Enhanced Oil Recovery Techniques
- Forensic and Genetic Research
- Remote-Sensing Image Classification
- Drilling and Well Engineering
- Distributed and Parallel Computing Systems
- Geological Modeling and Analysis
- Advanced Data Processing Techniques
- Geochemistry and Geologic Mapping
- Molecular Biology Techniques and Applications
- Archaeological Research and Protection
- Gene expression and cancer classification
- Scientific Computing and Data Management
- Model-Driven Software Engineering Techniques
- Epigenetics and DNA Methylation
- Advanced Clustering Algorithms Research
- Hydrological Forecasting Using AI
- Injection Molding Process and Properties
- Carbon Dioxide Capture Technologies
- Groundwater flow and contamination studies
- Cloud Data Security Solutions
- Research Data Management Practices
Battelle
2014-2024
National Energy Technology Laboratory
2022-2024
Government of the United States of America
2022
Cancer Genetics (United States)
2012
The Ohio State University
2010-2012
DNA-based methods for human identification principally rely upon genotyping of short tandem repeat (STR) loci. Electrophoretic-based techniques variable-length classification STRs are universally utilized, but limited in that they have relatively low throughput and do not yield nucleotide sequence information. High-throughput sequencing technology may provide a more powerful instrument identification, is currently validated forensic casework. Here, we present systematic method to perform...
Summary Considerable amounts of data are being generated during the development and operation unconventional reservoirs. Statistical methods that can provide data-driven insights into production performance gaining in popularity. Unfortunately, application advanced statistical algorithms remains somewhat a mystery to petroleum engineers geoscientists. The objective this paper is some clarity issue, focusing on how build robust predictive models develop decision rules help identify factors...
High circular tombs (HCTs) in southern Arabia provide valuable information for anthropologists who seek fundamental understanding of the transition ancient peoples from a nomadic pastoral lifestyle, to agro-pastoralism, and eventually formation states. In particular, knowing geographical distribution HCTs across region informs theories on patterns territoriality environmental social factors that are implicated emergence civilizations. The small size HCTs, vast search regions, rugged terrain...
Considerable amounts of data are being generated during the development and operation unconventional reservoirs. Statistical methods that can provide data-driven insights into production performance gaining in popularity. Unfortunately, application advanced statistical algorithms remains somewhat a mystery to petroleum engineers geoscientists. The objective this paper is some clarity issue, focusing on: (a) how build robust predictive models, (b) develop decision rules help identify factors...
We compare two approaches for building a statistical proxy model (metamodel) CO2 geologic sequestration from the results of full-physics compositional simulations. The first approach involves classical Box-Behnken experimental design with quadratic polynomial response surface. second used space-filling maxmin Latin Hypercube sampling choice four different meta-modeling techniques: polynomial, kriging, multivariate adaptive regression spline (MARS) and additivity variance stabilization...
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding diagnosis.
Abstract Examinations of soil traces associated with forensic evidence can be used to narrow potential source area(s) by characterizing features the trace assemblage, some which are limited specific regions. Soil characteristics may infer likelihoods being derived from distinct areas within digital maps, including both maps discrete classes such as formations on geologic and land cover, continuous geospatial data, distance a point source. Seldom do precisely represent observable in trace....
Algorithms are taking over the world, or so we led to believe, given their growing pervasiveness in multiple fields of human endeavor such as consumer marketing, finance, design and manufacturing, health care, politics, sports, etc. The focus this article is examine where things stand regard application these techniques for managing subsurface energy resources domains conventional unconventional oil gas, geologic carbon sequestration, geothermal energy. It useful start with some definitions...
Abstract CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, full-physics compositional simulations are routinely used to understand key processes and parameters affecting pressure propagation buoyant plume migration. As these models data computation intensive, development computationally-efficient alternatives conventional numerical simulators has become...
Abstract The use of statistical modeling and machine learning techniques to replace computationally expensive simulation models with an equivalent “proxy” or “surrogate” model is becoming commonplace in petroleum reservoir modeling. traditional approach a classical experimental design such as the Box-Behnken (BB) design, results fitted quadratic response surface. An alternative Latin Hypercube sampling (LHS) based Monte Carlo framework, using some advanced regression technique...
Abstract Data mining for production optimization in unconventional reservoirs brings together data from multiple sources with varying levels of aggregation, detail, and quality. Tens variables are typically included sets to be analyzed. There many statistical machine learning techniques that can used analyze summarize the results. These methods were developed work extremely well certain scenarios but terrible choices others. The analyst may or not trained experienced using those methods....
Teams of researchers on Task 5 the SMART project have developed a variety modeling architectures to predict subsurface behavior during carbon injection and post-injection periods. One important part this task was compare candidate approaches in terms accuracy, reliability, speed, memory use, all using common set metrics visualizations for an "apples apples" comparison. Dr. Jared Schuetter will share details task, results that were obtained, lessons learned.
The poster discusses the modeling workflow to generate ensemble of geologic realizations Illinois Basin Decatur Project (IBDP) site, based on available site characterization data and inherent uncertainty those data, for use by project collaborators in DOE SMART Initiative (Phase 2) build their forward modeling, history matching, optimization workflows. This is summarized from technical report submitted U.S. earlier this year.
The objective of this study is to develop and validate a portfolio simplified modeling approaches for CO2 sequestration in deep saline formations. It important ensure that the models, developed using reduced physics or statistical learning-based approaches, are also capable reproducing full spectrum uncertainty sensitivity analysis results from detailed numerical simulators. A 97-run LHS design with full-physics model used generate reference cumulative distribution function (CDF) two key...