Patrick William Michael Corbett
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Automated Classification of Well Test Responses in Naturally Fractured Reservoirs Using Unsupervised Machine Learning Open
Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure transient analysis could play a key role for fracture characterization purposes if better links can be established between the…
Petrophysical Characterization and porosity-permeability log calculation by Dual-Energy CT scan: Morro do Chaves Formation, Sergipe-Alagoas Basin, Brazil Open
Considered important analogues of pre-salt reservoirs in hydrocarbon-producing basins throughout eastern Brazilian shore, the coquinas of the Morro do Chaves Formation (Barremian-Aptian of the Sergipe-Alagoas Basin) were studied in this wo…
Automated Classification of Well Test Responses in Naturally Fractured Reservoirs Using Unsupervised Machine Learning Open
Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure Transient Analysis (PTA) could play a key role for fracture characterization purposes if proper links are built between the pr…
Automated Classification of Well Test Responses in Naturally Fractured Reservoirs Using Unsupervised Machine Learning Open
Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure Transient Analysis (PTA) could play a key role for fracture characterization purposes if proper links are built between the pr…
A Machine Learning-Based Method for Classifying Well Test Responses in Naturally Fractured Reservoirs Open
Complete dataset (raw data), processing codes (MATLAB v2020b) and numerical simulation model (Petrel v2017, ECLIPSE) for clustering of pressure derivatives in Naturally Fractured Reservoirs
A Machine Learning-Based Method for Classifying Well Test Responses in Naturally Fractured Reservoirs Open
Complete dataset (raw data), processing codes (MATLAB v2020b) and numerical simulation model (Petrel v2017, ECLIPSE) for clustering of pressure derivatives in Naturally Fractured Reservoirs
Impact of modelling decisions and rock typing schemes on oil in place estimates in a giant carbonate reservoir in the Middle East Open
We demonstrate how modelling decisions for a giant carbonate reservoir with a thick transition zone in the Middle East, most notably the approach to reservoir rock typing and modelling the initial fluid saturations, impact the hydrocarbon …
Supporting Twenty-First-Century Students with an Across-the-Curriculum Approach to Undergraduate Research Open
An across-the-curriculum (ATC) approach to undergraduate research (UR) is a productive addition to UR ecosystems at equity-oriented institutions.The ATC approach is differentiated from mentored UR experiences and laboratory course-based UR…
The geoengineering approach to the study of rivers and reservoirs Open
This Special Publication contains contributions for two meetings held to explore the links between geoscience and engineering in rivers and reservoirs (surface and subsurface). The first meeting was held in Brazil and, as a result, the vol…
NUCLEAR MAGNETIC RESONANCE TO CHARACTERIZE THE PORE SYSTEM OF COQUINAS FROM MORRO DO CHAVES FORMATION, SERGIPE-ALAGOAS BASIN, BRAZIL Open
Submitted by Jairo Amaro ([email protected]) on 2019-06-03T17:50:32Z No. of bitstreams: 1 8-2018_NUCLEAR-MAGNETIC-RESONANCE-TO-CHARACTERIZE-THE-PORE-SYSTEM-OF-COQUINAS-min-min.pdf: 371441 bytes, checksum: 77f27294859de27385091d1e2a3…
Facies and depositional environments for the coquinas of the Morro do Chaves Formation, Sergipe-Alagoas Basin, defined by taphonomic and compositional criteria Open
Lacustrine carbonate rocks form important hydrocarbon accumulations along the Brazilian continental margin, some of which are contained in oil fields in which coquinas are one of the main reservoirs (viz. Campos Basin). The complexity and …
View article: Improving the learning of chemical-protein interactions from literature using transfer learning and specialized word embeddings
Improving the learning of chemical-protein interactions from literature using transfer learning and specialized word embeddings Open
In this paper, we explore the application of artificial neural network ('deep learning') methods to the problem of detecting chemical-protein interactions in PubMed abstracts. We present here a system using multiple Long Short Term Memory …
Quantifying Porosity through Automated Image Collection and Batch Image Processing: Case Study of Three Carbonates and an Aragonite Cemented Sandstone Open
Modern scanning electron microscopes often include software that allows for the possibility of obtaining large format high-resolution image montages over areas of several square centimeters. Such montages are typically automatically acquir…