1.

Record Nr.

UNINA9910463083303321

Autore

Mohaghegh Shahab D

Titolo

Artificial intelligence & data mining applications in the E&P industry [[electronic resource] /] / Shahab D. Mohaghegh, Saud M. Al-Fattah, Andrei S. Popa

Pubbl/distr/stampa

Richardson, TX, : Society of Petroleum Engineers, c2011

ISBN

1-61399-064-2

Descrizione fisica

1 online resource (271 p.)

Collana

Getting up to speed

Altri autori (Persone)

Al-FattahSaud M

PopaAndrei S

Soggetti

Petroleum engineering

Neural networks (Computer science)

Data mining

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

""Foreword""; ""Contents""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 1�Artificial Neural Networks""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 2�Evolutionary Computing""; ""Virtual-Intelligence Applications in Petroleum Engineering: Part 3�Fuzzy Logic""; ""Using Artificial Neural Nets To Identify the Well-Test Interpretation Model""; ""Discriminant Analysis and Neural Nets: Valuable Tools To Optimize Completion Practices""; ""An Investigation Into the Application of Fuzzy Logic to Well Stimulation Treatment Design""

""Predicting Production Using a Neural Network (Artificial Intelligence Beats Human Intelligence)""""Application of Neural Networks to Modeling Fluid Contacts in Prudhoe Bay""; ""Predicting Well-Stimulation Results in a Gas-Storage Field in the Absence of Reservoir Data With Neural Networks""; ""Candidate Selection for Stimulation of Gas Storage Wells Using Available Data With Neural Networks and Genetic Algorithms""; ""Neural Network Model for Estimating the PVT Properties of Middle East Crude Oils""; ""Intelligent Systems Can Design Optimum Fracturing Jobs""



""Neural-Network Approach To Predict Well Performance Using Available Field Data""""Neural Network Approach Predicts U.S. Natural Gas Production""; ""Integration of Multiphase Flowmetering, Neural Networks, and Fuzzy Logic in Field Performance Monitoring""; ""Recent Developments in Application of Artificial Intelligence in Petroleum Engineering""; ""Zonal Allocation and Increased Production Opportunities Using Data Mining in Kern River""; ""Self-Organizing Maps for Lithofacies Identification and Permeability Prediction""; ""Optimizing Cyclic Steam Oil Production with Genetic Algorithms""

""Analysis of Best Hydraulic Fracturing Practices in the Golden Trend Fields of Oklahoma""""Application of Artificial Intelligence in Gas Storage Management""; ""Using Neural Networks for Candidate Selection and Well Performance Prediction in Water-Shutoff Treatments Using Polymer Gels�A Field-Case Study""; ""The Development of an Artificial Neural Network as a Pressure Transient Analysis Tool for Applications in Double-Porosity Reservoirs""; ""Flow Pattern and Frictional-Pressure-Loss Estimation Using Neural Networks for UBD Operations""

""Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model""""Artificial-Intelligence Technology Predicts Relative Permeability of Giant Carbonate Reservoirs""; ""Case-Based Reasoning Approach for Well Failure Diagnostics and Planning""; ""Top-Down Intelligent Reservoir Modeling (TDIRM)""; ""New Insight into Integrated Reservoir Management using Top-Down, Intelligent Reservoir Modeling Technique;  Application to a Giant and Complex Oil Field in the Middle East""



2.

Record Nr.

UNINA9910430757003321

Titolo

Allevamento animale e sostenibilità ambientale / a cura di Bruno Stefanon, Marcello Mele, Giuseppe Pulina

Pubbl/distr/stampa

Milano, : FrancoAngeli, 2018

ISBN

9788891761835

Descrizione fisica

2 v. (287 ; 401) : ill. ; 23 cm

Collana

Assalzoo ; 69-70

Disciplina

636.08

Locazione

FMVBC

Collocazione

V B 82.1

V B 82.2

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

1. I principi 2. Le tecnologie