Most difficult issues regarding the upstream oil industry are data management, quantifying uncertainty in the subsurface, and risk assessment of strategies for field engineering and development. Oil and Gas industry is now in the sea of data, where the Big data is collected from virtually every sensor imaginable, and this data can provide us with the ways and means to go above and beyond old school of traditional deterministic and interpretive studies.
In the Big Data era, the clustering techniques, neural networks, fuzzy-logics, genetic algorithms and other heuristics are becoming the new norm for data driven modeling of all the elements of the upstream oil and gas industry.
This training course will highlight:
- Data Management and Data Mining with the focus on reservoir modeling and drilling operations
- Data analysis techniques that provide descriptive and predictive models
- How to complement conventional petroleum engineering analysis with the Big Data Analytics
- How can Big Data, IoT and Blockchain influence the Oil and Gas Industry?
- Business cases to illustrate the applications of the concepts presented in the course
By the end of this training course, you will learn to:
- Perform the data mining and the fusion of data
- Understand how to implement the Big Data Analytics to improve drilling processes
- Appreciate Artificial neural network and its geoscience applications
- Implement data management and data analytics for intelligent reservoir characterization
- Effectively perform data analysis for production forecasting
- Implement Blockchain models for Risk Management and production optimization
DAY 1
MINING AND FUSION OF DATA
- Instrumented oil fields
- Current situation in the upstream data analysis
- The SEMMA process- Sampling, Exploring, Modifying, Modeling, and Assessing
- Oilfield Data Management
- Oilfield Exploration Analysis
- Oilfield Appraisal Management
DAY 2
BIG DATA ANALYTICS
- Pattern recognition
- Clustering
- Quantification of data uncertainty and prediction error and confidence interval
- Data repositories in upstream oil and gas
- Exercise: Production Data Quality Control Framework
DAY 3
INTRODUCTION TO IOT AND BLOCKCHAIN
- loT revolution
- IoT application in oil and gas fields
- Smart sensors for smart oilfields
- Blockchain basics
- Blockchain and Byzantine general problem in Risk Management
DAY 4
PRODUCTION FORECASTING
- Aggregate, analyze, and forecast production from wells and reservoirs
- Analytical workflows for a decline curve analysis
- Reserves values estimation at P90, P50, P10
- Well clustering and appraisal of wells representation
- Exercise: Oil well reserves forecasting
DAY 5
PRODUCTION OPTIMIZATION
- Intelligent Reservoir Modeling Workflow
- Travel time (DT) prediction
- Gamma ray (GR) prediction
- Density (RHOB) prediction
- Hierarchical Clustering
- Exercise: Big Data Workflows definition for drilling optimization
This training course is designed for all professionals working in the field of data analysis, oil and gas exploration, geology and reservoir modelling.
It is also quite beneficial for other people involved in the upstream oil production as it shows the interdependence of the data between the departments.
This training course is suitable to a wide range of professionals but will greatly benefit:
- Reservoir Engineers
- Petroleum Engineers
- Risk Managers
- Drilling Managers
- Field Service and Related Operations
- Business Unit Heads
- Data and Business Analysts
- Data Mining/Data Managers/Data Scientists