Hydrocarbon E&P challenges opportunitie Information Systems

Reliance Industries Ltd. Exploration & Production Business. India. 17-September-2008

Hydrocarbon

Exploration & Production

Opportunities & Challenges in IS

Scope of Document : Insight into the Possibilities of IS.

Nature : Presentation

Security : Public

Author : G Srikanth

Date and Version : 30 October 2010 v1.0


Fall-back

1. Principles and Overview

2. Domain Information Systems

3. Challenges and Opportunities in IS


1. Principles & Overview of E&P

1. Hydrocarbons are Formation, Discovery and Production

2. Uncertainties & Risks

3. Gamut of Sciences and Technologies involved

4. Business Process Categories and Process

– Acquisition Capture the opportunity

– Explore Convert the opportunity to Discovery

– Appraise Evaluate the Discovery

– Develop Prepare to Exploit the Discovery profitably

– Deplete(Produce) Nomination to Cash on Production asset

– Abandon Exit

Spectacular Opportunity Extensive Diversity Strategic

Contribution

The Charm of Successful E&P


2. Domain Information Systems of E&P

1. Business Processes and Functions/Tasks in each Process node

2. Complexity of data and analysis

3. Features of E&P IS

a. High Compute Capability

b. Diverse Application Portfolio for every function

c. High Data & Information Costs

d. Large data volumes

e. Complex Integration of wide range of data classes

f. Information Uncertainty needing multiple analysis and processes

4. Compute System Characteristics

a. Teraflop processing power needed in many areas of work

b. Very high memory capacity > 64GB needed in many applications

c. Imaging Systems – very high end graphics

5. Application Characteristics

a. Specialized with proprietary algorithms and data structures

b. Long cycle times in development of expertise {Programs & Usage}


The Charm of Successful E&P

• Extensive Diversity for Thought

• Opportunity to be thinking beyond ordinary

Challenges and Opportunity to Excel in the Charming world of E&P IS


In Pursuit of the Charm - Outline

I. Compute Intense Applications and Opportunities

II. Graphic Intensive Applications and Opportunities

III. Data Structures and Semantic exploitation

IV. Communication Technologies and their avenues

V. Extent and Scope of opportunities


I. Compute Intense Applications

1. Programs that execute trillions of operations

– Seismic Data Processing & Interpretation

– Reservoir Simulation

– Numerical Basin Modeling

2. Opportunities in System Administration & Optimization

3. Opportunities for innovation and development


I.1 Seismic Data


I.1 Seismic Data Processing


I.1 Seismic Data Processing Opportunity

1. New Processing methods. Example

• Stochastic Processing

• Full wave-form deconvolution

• Complex geometric corrections

• Quantum Resonance Interferometry

2. Requirements

• HPC facilities

• Numerical analysis CoE

3. Value

• Niche technology {large IP}

• Improved resolution of RIL E&P data discovery

Appropriate development Efficient depletion


I.2 Reservoir Flow

http://www.stanford.edu/dept/ICME/docs/seminars/Aziz-2006-10-16.pdf

1. Flow by

fluid

movement

2. Flow by

expansion

(pressure

reduction)


I.2 Reservoir Simulation


I.2 Reservoir Simulated

10/2/2012

Seismic AI

History

Match Sw

Original

History

Match Sw

Oct 2000


I.2 Reservoir Simulation Opportunity

1. Improved algorithms and mathematics

2. Grid design

3. Scaling methods

4. Cloud computing algorithms

5. Data structure for storing model results

6. Analytical methods to compare multiple models

a. Strong mathematics in CFD

b. Use of CFD tool-kits

c. Understanding of Single and Multiphase fluid flow through

porous media

d. Multi speciality team as CoE


II. Graphic Intensive Applications

5 k

m


II. Graphic Intensive Applications Opportunity

1. E&P is heavily Graphic intensive

– Yet, cannot see through the objects in 3D

– Resolution, Color depth

?


III. Information Value Proposition in E&P

E&P

Others

Dr. Alan Nunns


III. Data Structures and Semantics Space


III. E-R of Earth Model in E&P database-Finder


III. Seismic and Well Data Models


III. Opportunities and Requirements in DM

1. Defined and Develop the Data Models There are international Standards (www.energistics.org)

2. Implementations with GIS (E.g. PPDM)

3. Intelligent Semantics

4. Knowledge Management

ONTOLOGY


Well Plan and Real Time Data:

Updating The 3D Volume“Earth

Model”

Integrated

Interpretation

Update

Well Plan Update

Interpretation

Well Plan/Construction

Update

Reservoir Model

/Simulation

Real Time Data

Transmission

Direct to

Database

III. Information Flow across E&P Workflows


III. Data integration, assimilation and interpretation Applications Portfolio from major vendors address specific

functional space

– Geophysics

– Geology Models & Reservoir Models

– Production

– Drilling

Data interfaces across disciplines are mediocre

– Largely visual integration

– Import-Export data structures

Advanced aspects like :

– Data Mining

– Pattern recognition

– Intelligent search are yet to develop


IV. Communications & Technologies in E&P

1. Large band-with LAN (1gpbs/ws is minimal need for 3D)

Can this be achieved on WAN/ Internet?

2. Remote & Hazardous locations VSATs, Microwave, Radio++

3. Extreme Temperatures & Pressure

• Sensors inside oil & gas wells

• Well head (2000m below sea-level @ -30C)

4. Non-serviceable and Non-replaceable sensors High reliability

Cable free sensors for planting at sea-bottom

Ultra-high-resolution measurement of Natural EM


V. Automated Detection of Thin Intra-Reservoir Denses


Lithofacies From Logs

Sta

nd

ard

Log A

naly

sis

– A

nalo

g L

itholo

gy C

lasses

Spe

cia

l Im

ag

e L

og

s a

nd

Derive

d L

ith

o I

nd

ica

tors

Sta

nd

ard

Log S

uite (

To D

o S

pectr

al +

Segm

)

Lithfacies from Conventional Logs using Brigg’s Triangles. Calibrated

with Core and used. Requires Field level tuning

Very

hig

h v

ert

ical re

solu

tion a

nd c

lassific

ation a

chie

ved

S

eq

ue

nce

str

atig

rap

hy c

on

fin

ed M

ark

ovia

n S

trin

gs?


Classification & Categorization

Such Patterns Exist in Real data

The Various Structured Parameters Can be :

– On each Trace Separately

– Based on adjacent traces either side on 3D (1 look up= 4 traces)

– Based on Multiple adjacent traces (2-5 lookup – How to do?)


Simple Syntactic Pattern Recognition – Are you ready?

Can any of you

Develop a small

Program to

Extract these

Syntactic Variables?


V. Attitude, Aptitude and Abilities

Attitude

– Learn

– Analyze

– Collaborate

Aptitude

– Numbers and Analytical methods

– Graphics

– Development

Abilities

– Numerical Analysis and Graphics

– Handle large data sets


E&P – Pursuit of Passion

1. Radically new methods are finding way

2. Individuals are changing the paradigm

3. If there is Excellence in You, there is a problem in E&P for You

Documents

Hydrocarbon E&P challenges opportunitie Information Systems