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Gas Hydrate Resource Assessment

U.S. Outer Continental Shelf

Independence Hub photo from Anadarko Petroleum Corp.

Matthew Frye – BOEM, Herndon, VA

Kenneth Piper – BOEM (retired), Camarillo, CA

John Schuenemeyer – SWSC, Cortez, CO

Contributors: John Grace, Gordon Kaufman, Ray Faith, William Shedd, Jesse Hunt, Pulak Ray

•Total OCS = 7.1 million km2

• ~ 15% natural gas, 27% oil

BOEM manages the exploration and development of the nation's offshore resources. It seeks to appropriately balance economic development, energy independence, and environmental protection through oil and gas leases, renewable energy development and environmental reviews and studies.

Bureau of Ocean Energy Management

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Resource Assessments: Conventional O&G v. Unconventional

Conventional Oil and Gas(existing methods)

Discovery MethodSubjective Method

Limited Spatial Resolution

Unconventional Gas Hydrate

(No Existing Methodology)

Mass Balance Method

Significant Spatial Component

What is Gas Hydrate?

What is Gas Hydrate?

Gas hydrates are ice-like crystalline substances occurring in nature where a solid water lattice accommodates gas molecules (primarily methane, the major component of natural gas) in a cage-like structure, known as a clathrate.

•Gas Hydrates are stable only in high pressure - low temperature environments

•P/T conditions are favorable on OCS where water depth > 350 meters

•Hydrate Stability Zone thickness increases as water depth increases (HSZ exceeds 1000 m thick in GOM)

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Why Are We Interested ?

Why are we interested in Gas Hydrate?

Gas hydrate dissociates into methane and water as temperature increases or pressure decreases.

• Potentially recoverable energy resource !!!

Estimated U.S. in-place gas resources – all non-hydrate

reservoirs (25,000 Tcf)

Remaining “Recoverable” (1,400 Tcf)

U.S. Methane Hydrate in-place resource

(200,000 Tcf)

Gas Resources

Produced Methane (900 Tcf)

*1995 USGS

Gas Hydrate Model Description

Model Specifications

•Stochastic - 1,000 Monte Carlo trials (capable of 4,000 trials)

•Mass Balance allows for extreme variable disaggregation / modification

•Inputs – combination of spatial and empirical data

•Outputs are GIS-ready and easily mappable

•Programmed in FORTRAN version 90 (Compiled as v. GOM3.38)•R used for summary statistics and graphics

Example Study Area – Gulf of Mexico

•Multi-channel seismic data (2D and 3D) •Wellbore data (Industry & science wells)•Modeled rates, functions, etc. 2

5°00

'

25°

00'

30°

00'

30°

00'

95°00'

95°00'

90°00'

90°00'

85°00'

85°00'

3-D coverage (~200,000 km2)2-D coverage (~225,000 km2)

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Spatial Inputs to Model

Water Depth Mobile Salt / Basement morphology

Sand Distribution Seafloor Anomalies

Example: Walker Ridge protraction area

•GOM study area ~ 450,000 km2

•202,079 model cells - each cell 2.32 km2 (5000’ x 5000’)

Model Cell Structure – Gulf of Mexico

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Gas Hydrate Model Methodology

Charge Distribution

Rock Volume Distribution

ChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

Charge Distribution

Rock Volume Distribution

ChargeModuleChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

ContainerModule

ContainerModule

ConcentrationModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

IntegrationModule

In-PlaceMethane Hydrate

Distribution

Charge Module

Charge Distribution

Rock Volume Distribution

ChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

Charge Distribution

Rock Volume Distribution

ChargeModuleChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

ContainerModule

ContainerModule

ConcentrationModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

IntegrationModule

Charge Module

Generation Model Migration Model

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Generation Model

Generation Productivity

Function

Asymptotic TOC Conversion Efficiency

Total Organic Carbon Mass

Base Methanogen Productivity

Sediment Temperature

Water Bottom Temperature

GeothermalGradient

Time

Thickness

GeneratedMethane

Mass

SedimentPermeability

Output

Function

Scalars

Input

FunctionArguments

Generation Productivity

Function

Asymptotic TOC Conversion Efficiency

Total Organic Carbon Mass

Base Methanogen Productivity

Sediment Temperature

Water Bottom Temperature

GeothermalGradient

Time

Thickness

GeneratedMethane

Mass

SedimentPermeability

Output

Function

Scalars

Input

FunctionArguments

Pro

babi

lity

Den

sity

Weight percent TOC

0.0 0.5 1.0 1.5 2.0

0.0

0.5

1.0

1.5

Pro

babi

lity

Den

sity

Weight percent TOC

0.0 0.5 1.0 1.5 2.0

0.0

0.5

1.0

1.5

Generation Model Output

Charge:  Generation model Output

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Migration Model

Charge: Migration model two end members100% vertical and 100% dip-driven

At 100% vertical, all gas generated in a model cell remains in that cellGeneration per cell = gas charge per cell

Top of Salt spatial input

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GIS Analysis

Top Salt structure map

Flow Direction

Basin

GISHydrologic

Tools

Top Salt structure withHydrodynamic catchments

Curvature GIS tool

Curvature map w/ catchments

White = negative curvatureBrown = positive curvature

Dip-Driven Gas Migration

100% dip-driven migration continued…….

At 100% dip migration, all gas within a catchment basin is redistributed to cells with + curvature

Curvature Map 100% Dip Migration Map

Sum Generation, by Catchment

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100% dip-driven migration continued…….

At 100% dip migration, all gas within a catchment basin is redistributed to cells with + curvature

Dip-Driven Gas Migration

Migration Model

Which migration method is correct?

100% Dip Driven

Gas migrates to margin of basins

100% Vertical

Gas remains in cell of origin

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Migration model

Based on sensitivity analysis using known seafloor seeps…….

Mixing Ratio 60:40 dip v. vertical

Mean Charge

Container module

Charge Distribution

Rock Volume Distribution

ChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

Charge Distribution

Rock Volume Distribution

ChargeModuleChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

ContainerModule

ContainerModule

ConcentrationModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

IntegrationModule

Container Module

Gross HSZ  ‐ UZ = Net HSZ

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where, B = water depth in meters C = thickness of the hydrate stability zone in meters

geothermal gradient water bottom phase stabilitytemperature expression

f(B) = -(-9.6 x ln(B) + 88.4) x C/1000 – 295.1 x B-0.6 + 8.9 x ln(C + B) – 50.1

Stability Equation (from Milkov and Sassen, 2001)

sediment temperature expression

Container Module

GrossHSZ

Salt

Undersaturated Zone (UZ)

Net HSZ

High Charge = Thin UZ Low Charge = Thick UZ

thickness inversely related to Charge:

Container Module

UZ

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Net HSZ (= Gross HSZ – UZ)

Container Module

Charge Distribution

Rock Volume Distribution

ChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

Charge Distribution

Rock Volume Distribution

ChargeModuleChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

ContainerModule

ContainerModule

ConcentrationModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

IntegrationModule

Concentration Module

HSZ porosity, by lithologic facies

Pore space saturated by gas hydrate

Concentration Module

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Concentration Module

5000’

zT

Shale Void = (Volume)(Porosity)Volume Shale = (x)(y)[(T)(1-sand%)]Porosity Shale = f(d)

Sand Void = (Volume)(Porosity)Volume Sand = (x)(y)[(T)(sand%)]Porosity Sand = f(d)

From Container Module:(T) Net HSZ thickness(d) Midpoint depth net HSZ

From input file:sand %

Sand %

x

Concentration Module

Mean = .095

Concentration

*decimal % of the bulk rock volume

*

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Integration Module

Integration Module

For each model cell, we:

•Compare charge to available container retain smaller of two

•Except at surficial anomalies manually fill if undercharged

•Convert from RTP to STP: P

roba

bilit

y D

ensi

ty

Conversion Factor

140 145 150 155 160 165 170

0.0

0.5

1.0

1.5

2.0

2.5

Beta(5,1.6) mean=164,mode=168

Pro

babi

lity

Den

sity

Conversion Factor

140 145 150 155 160 165 170

0.0

0.5

1.0

1.5

2.0

2.5

Beta(5,1.6) mean=164,mode=168

Charge Distribution

Rock Volume Distribution

ChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

Charge Distribution

Rock Volume Distribution

ChargeModuleChargeModule

Hydrate Saturation Distribution

ContainerModule

ConcentrationModule

ContainerModule

ContainerModule

ConcentrationModule

ConcentrationModule

In-Place Methane Hydrate

Distribution

IntegrationModule

IntegrationModule

Assessment Results - Graphical

0

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750

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950

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1150

1250

1350

Mor

e

In-Place gas Hydrate (TCM)

Fre

qu

ency

0%

20%

40%

60%

80%

100%

Cu

mu

lati

ve P

rob

abil

ity

Frequency Cumulative %100%

80%

60%

40%

20%

0%0

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450

550

650

750

850

950

1050

1150

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Mor

e

In-Place gas Hydrate (TCM)

Fre

qu

ency

0%

20%

40%

60%

80%

100%

Cu

mu

lati

ve P

rob

abil

ity

Frequency Cumulative %100%

80%

60%

40%

20%

0%

Mean Total = 607 TCM (21,444 TCF)

U.S. GOM In-Place Results (1,000 trials)

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Assessment Results - Spatial

New Orleans

o In Place resource estimate – not necessarily technically/economically recoverable

o No introduction of geologic risk – petroleum system success on all trials

Summary

Conclusions - GOM:

•Resource assessment methodology different than typical O&G assessmentsSpatial rather than strictly empirical

•Advanced GIS tools used to model gas generation and migrationFlow Direction, Basin, Curvature

•Approach applicable to other O&G basins around the world with proper modifications to account for local subsurface geometries and data availability

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Pacific OCS

Pacific Outer Continental Shelf

• Complex tectonics (subduction, spreading, wrench)• Several point source sediment systems• Near-shore basins• Relatively thin sediment cover in places• Paucity of seismic data

Model Changes

• 100% vertical gas migration• Crust age & BSR incorporated• Mixed spatial/empirical inputs• HSZ constrained by sediment thickness

*Official results release expected 3Q 2012

Pacific OCS – Spatial Inputs

2D Seismic Data DSDP/ODP wells

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Pacific OCS – Spatial Inputs

Water Depth Sediment Thickness

Crust Age

Pacific OCS – Spatial Inputs

Bottom Simulating Reflectors (BSR)

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Pacific OCS – (partial) Spatial Inputs

Sand DistributionTotal Organic Carbon

Pacific OCS - Outputs

Gas ChargeHydrate Stability Zone (HSZ)

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In Place Gas Hydrate Volume