Techniques of Hydrocarbon Exploration in Basement with Special Emphasis on Log Analysis

- Arnab Ghosh (Senior Petrophysicist, Schlumberger)

Agenda

Introduction

Basement Overview

Methodology for Basement Characterization

Well-Log Responses in Basement

Summary

Introduction

Basement reservoirs for hydrocarbon

‘of no economic potential’ ??15000 bpd production from basement rocks of California fields Edison, Santa Maria Valley and Wilmington; - reported by Eggleston (AAPG Bulletin, 1948)

Many oil discoveries had been missed because of inadequate exploration of the barely scratched basement - Landes (1959)

Introduction

Kennedy (1996) – Oilfields that produce from crystalline basements were discovered by accident in most of the cases

Aguilera (1996) – Suggested drilling at least 300 m into basement especially if the cover rocks contain oil– Fractured reservoirs contain significant volumes of undiscovered

hydrocarbons may have been missed by a failure to intersect the mainly vertical to sub-vertical fracture system

Fractured Basement Reservoir Around the World

Ref: www.slb.com/dcs

Hydrocarbon Potential in Basement Worldwide

IGNEOUS ROCK METAMORPHIC ROCK

Basement rock usually refers to the thick foundation of ancient, and oldest metamorphic and igneous rock that forms the crust of continents.

What is Basement Rock?

Igneous rock (derived from the Latin word "Igneus" meaning of fire, from "Ignis" meaning fire) is one of the three main rock typesIgneous rock is formed by magma or lava (molten rock) cooling and becoming solid. Igneous rock may form with or without crystallization, either below the surface as intrusive (plutonic) rocks or on the surface as extrusive (volcanic) rocks. This magma can be derived from partial melts of pre-existing rocks in either a planet's mantle or crust.

What is an Igneous Rock

Metamorphic rock isthe result of thetransformation of anexisting rock type, theprotolith, in a processcalled metamorphism,which means "change inform".The protolith may besedimentary rock,igneous rock or anotherolder metamorphic rock.Some examples ofmetamorphic rocks aregneiss, schist, slate,marble, and quartzite

What is a Metamorphic Rock

SchistGranite Granite-Gneiss

Most basement rocks are hard and brittle with very low matrix porosity and permeability, consequently reservoir quality depends on the development of secondary porosity.

Secondary porosity may be divided into two main kinds by origin;

– tectonic porosity (joints, faults, fractures, etc at a range of scales from micro-fractures to seismic scale faults and their damage zones)

– dissolution porosity (ranging from solution effects in weathering zones or fault zones to effects associated with hydrothermal circulation

There are many possible sources for the oil accumulations in basement reservoirs, however, three sources are referenced most commonly:

– Overlying organic rock from which the oil was expelled downward during compaction.– Lateral, off-the-basement but topographically lower, organic rock from which oil was squeezed into

an underlying carrier bed through which it migrated updip into the basement rock.– Lower, lateral reservoirs from which earlier trapped oil was spilled due to tilting or overfilling.

Basement Reservoirs

Seismic Section of a Basement Reservoir

Ref: SPE 57324

Integrated Fractured Basement Workflow

Ref: www.slb.com/dcs

Well-log Responses in Basement

Well-X: 40 bopd Well-Y: 800 bopd

0 150 0.2 20001.95 2.950.45 -0.15m3/m3

g/cm3ohm.mgAPI 0 150 0.2 20001.95 2.950.45 -0.15m3/m3

gAPI

Mineralofacies with Porosities

Methodology for Basement Evaluation using Well-Logs

Data Acquisition

OH Logs

Gamma Ray Density Neutron Resistivity

AcousticBorehole

Resistivity Images

Rock-Strength

Basement Characterization using Integrated Formation Evaluation

Spectroscopy

Dry Weights Stoneley Fracture Analysis Anisotropy

ANN ValidationMineral Volumetrics

NMR Litho Independent PorosityN

Permeability

Oil Saturation

Best ReservoirFacies with HC Straddle Packer

Y

Confirmation

Open Fracture

Spectroscopy

Relative yields are determoned from the spectrum

Dry weight elemental concentrations are determined as a continuous well-logs of Si, Ca, Al, Fe, Su, Ti, Na, K, Mg etc.

TAS Diagram using Elemental Analysis Results

Ref: SPWLA 2007

Elemental Analysis and TAS Diagram

Ref: PetroTech 2009

Si-Al Cross Plot

0

0.05

0.1

0.15

0.2

0.25

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5

Si (wt%)

Al (W

t%)

Lower Rock-Group

Upper Rock-Group

Si-Al

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.1 0.2 0.3 0.4 0.5

Si (wt%)

Ca(w

t%)

Lower Rock-GroupUpper Rock-Group

Silica Vs Calcium

Silica Vs Aluminum

Silica Vs Magnesium

Elemental Analysis: Well-A

Na2O+K2O

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

SiO2

Na2O

+K2O

Upper Rock-Group

Lower Rock-Group

Na2O+K2O

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

SiO2

Na2O

+K2O

Upper Rock-Group

Lower Rock-Group

Total Alkali Vs Silica

Ref: SPWLA India 2011

Si vs Ca

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Si

SiO2 Vs Na2O+K2O

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.3 0.4 0.5 0.6 0.7 0.8 0.9

SiO2

Na2

O+K

2O

Si vs Al

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Si

Al

Si-Mg

0

0.01

0.02

0.03

0.04

0.05

0.06

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Si

Mg

Silica Vs Calcium

Silica Vs Aluminum

Silica Vs Magnesium

Total Alkali Vs Silica

Elemental Analysis: Well-C

Ref: SPWLA India 2011

Si-Ca

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5

Si

Ca

SiO2 Vs (Na2O+K2O)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.3 0.4 0.5 0.6 0.7 0.8 0.9

SiO2

Na2O

+K2O

Si Vs Al

0

0.02

0.04

0.06

0.08

0.1

0.12

0.1 0.15 0.2 0.25 0.3 0.35 0.4

Si

Al

Si Vs Mg

0

0.01

0.02

0.03

0.04

0.05

0.06

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Si

Mg

Silica Vs Aluminum

Total Alkali Vs Silica

Silica Vs Calcium

Silica Vs Magnesium

Lower Rock-Group

Upper Rock-Group

Elemental Analysis: Well-B

Ref: SPWLA India 2011

Elemental Cross Plots Assists in Possible Rock type Determination and Mineral Assemblages

Stoneley Waves and Fracture Analysis

Low frequency fluid pressure pulse

Piston-like propagation along borehole wall

Energy decays exponentially away from borehole wall

Sensitive to fractures and permeable zones

Slowness is a function of frequency: dispersive mode

Open Fracture Analysis from Stoneley

Ref: SPE 138965

Stoneley Fracture Analysis and Hydrocarbon Production from Basement

Ref: SPE 57324

Dipole Anisotropy

Receivers with energy

Receivers with no energy

Dipole firing direction

Max horiz stress

Isotropic rock

Anisotropic rock

X Y

Z

Slow shear

Fast shear

Microfractures

Stress direction

Dipole Dispersion Analysis

Dipole Anisotropy and Dispersion Analysis

Ref: SPE 138965

Natural Fracture Detection using Dispersion Analysis

Ref: SPE 138965

Acoustic Profiling for Rock Strength and Alteration

B-G Inversion

Inhomogeneous isotropic

FrequencyS

low

nes

s

Damaged,near failure, Or alteration

VS(r)

W = c.A.Rmb.Rxo1-b

W = Fracture widthA = Additional current flow, caused by the presence of fracture.Rm= Mud ResistivityRxo=Fluxed Zone Resistivity

Co-efficient c and exponent b are obtained numerically from forward modeling.

k = w3 L / 12

L = Fracture lengthK = PermeabilityFor a single phase flow through a set of fractures, honoring Darcy’s law and Snow’s Cubic law.

Borehole Resistivity Imaging and Fracture Analysis

Scale 1: 250

Proved Zone of Interest

Possible Zone of Interest

Scale 1:60

Fracture Analysis in Basement

Ref: PetroTech 2012

Fracture Analysis: Well-A

Stoneley Fracture Analysis

Ref: PetroTech 2009

Fracture Analysis: Well-B

Stoneley Fracture Analysis

Ref: PetroTech 2009

Paleo-stress Vs. Permeable Fracture Pattern

Regional Stress Direction

Good Flow Region Low Flow/ Tight Region

Ref: PetroTech 2012

Forward modeling of Fracture & Stress Effects

Image loginterpretation

Fracture-driven

Stress-driven

Mixed effect

Zoning

+

New Generation Acoustic

Data versusprediction

Ref: SPE-138965

Different Sets of Fractures with Variable Potentials

Ref: IPTC 14802

Artificial Neural Network: mathematical models that emulate some of theobserved properties of biological nervous systems: parallel information processing,adaptive learning...

Artificial Neural Network (ANN)

Lithology Model: Well-A (Using ANN)

Artificial neural networking models using all the available logs in combination shows consistent result.

Revealed two major rock group based on the restricted occurrence of calcium rich layers.

This information was utilized as a framework for the current study.

T2

D

gas

water

oil

T2

D

T1

D-T2-T1

D-T1 map

T2-T1 map

D-T2 map

3D-Map

D = Diffusion CoefficientT1 = Longitudinal Relaxation TimeT2 = Transversed Relaxation Time

Viewing The Reservoir in a New Way using NMR

Wireline Formation Testing with Straddle Packer

Summary

Advanced well-log data integration with conventional open-hole logs is the key for basement characterizationElemental analysis provides elemental concentration as continuous logs, which can be used for mineral identification and volumetric analysisBorehole acoustic and resistivity imaging data is useful for fracture characterization Fluid identification can be possible by NMR as resistivity independent measurementsStraddle packer technique is the solution for collecting the reservoir fluid sample and reservoir property analysis

THANKS