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GNS Science

Ngawha Reservoir Model

John Burnell

JOGMEC-GNS Workshop, Tokyo

2 June 2016

GNS Science

Outline

• Purpose

• Conceptual Model

• Model Structure

• Model Verification

• Expansion Scenario

• Surface Features Model

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Purpose

• To develop a numerical reservoir model of the Ngawha Geothermal Field for consenting purposes

• Objectives

– Obtain an acceptable match to historical data

– Use a dual porosity model to more accurately model

injection returns in the reservoir

– Consider effects of possible future expansion

– Predict impact on surface features

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Conceptual Model

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Reservoir Characteristics

• Reservoir hosted in Waipapa Greywacke between 500m and 1500m depth

– Low porosity

– Permeability due to fractures and faults

• Low permeability siltstones form a cap

– Some transport through faults and fractures

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Resource Areas

Operations area

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Reservoir Characteristics II

• Geology

– Permeable greywacke

– Cap with small channels connecting to surface

• Temperatures in permeable reservoir are ~230 °C

• Hotter temperatures in the north

• Pre-production testing suggested fractured

reservoir with high permeability

• Hot upflow > 300°C, located in north < 10 kg/s

• CO2 concentrations ~1.5%

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Hydrological Model

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Model Validation Data

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• Pre-production temperature and pressure measurements.

• Measured changes in reservoir pressure due to production.

• Changes in production enthalpies.

• Changes in CO2 concentrations in production wells.

• Measured pressure changes in the 1983

interference tests.

• Travel times from the 2011 tracer test.

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Dual Porosity Numerical Reservoir Model

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Dual Porosity Model

Matrix

Fracture

Used to represent flows in fractures• Fast flow paths• Small volumes

• Model cooling

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Model Grid

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Geology and Resource Boundary

Permeable inner region

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Upflow

Upflow = 10 kg/s

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Model Verification

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Methodology

• Run natural state model

– Compare to measured temperatures and pressures

• Run historical production

– Compare to measured pressure changes, enthalpies and CO2 concentrations

• Add tracer injection.

– Compare to measured tracer

• Run production and injection for 1983

interference test

– Compare to measured pressures

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Natural State Temperatures

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Some Improvements Still Needed

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Natural State Pressures

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Changes Due to Development

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Pressures in Injectors Don't Match as Well

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Production Enthalpies

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Issues with Enthalpies

• Inconsistent with measured tempertures

– NG9 temperatures give enthalpies of 980 kJ/kg

– Initial data – 920 kJ/kg

– Also inconsistency between well enthalpies and station enthalpies

– In other fields it is suggested that measurement uncertainties are ~100 kJ/kg

– If this is the case then the model agrees within

measurement uncertainty.

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CO2 Concentration

• CO2 gives information about long term connection between injectors and producers

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Tracer Test – Injection into NG16

• Arrival times give information about short term transport between injectors and producers

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Co

nc

en

tra

tio

n (

ug

/L)

NG16 Tracer

NG4

NG9

NG12

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Model Results

Arrival time

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Interference Test – October 1983

• Pressure propagation across the reservoir

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Overall Match

• Ngawha Numerical Reservoir Model is well-calibrated

• Matches data from many different aspects of the field

• Based on physical understanding

– Reduces uncertainty

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Expansion Scenarios

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Expansion Scenarios

• Two scenarios

– Scenario A: 25 MWe expansion

– Scenario B: 50 MWe expansion

• 25 MWe stage from 2020

• 50 MWe stage from 2023

• Adjusted injection rates to match observations

– Loss of gases (currently 0.5%)

– Other loses/spillages (0.35%)

• Used supplemental injection to control reservoir pressures

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Scenario Pressures

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Some pressure changes

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Enthalpies Decline

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Will need some plant changes

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Surface Feature Modelling

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Surface Feature Modelling

• Ngawha Springs are valued highly by local community

• Ngawha Springs have low flow rates

• Reservoir model is too coarse to capture changes in flow to surface features

• Developed a separate model of the area around the surface features

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Schematic of Surface Feature Model

Deep Reservoir

Surface Waters

CaprockPermeable

Conduit

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Model Grid

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Vertical Extent

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Natural State Temperatures

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Natural State Pressures

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Surface Feature Model Setup

• Fixed pressures and temperatures in the bottom boundary

– Corresponding to measured reservoir data

• Fixed conditions in atmosphere

• Flow driven by boundary conditions

– Adjust conduit permeability to match flow

– Modelled flow was 1.3 kg/s

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Response to Production

• Used output from numerical reservoir model expansion scenario

– Reduced reservoir pressure by 0.3 bar

– Reduced reservoir temperature by 1 °C

– Reduced reservoir CO2 mass fraction from 1.3% to

0.1%

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Surface Feature Model Results – Flow to

Surface

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Surface Feature Model Results – Steam

Fraction

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Surface Feature Model Results – Temperature

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Surface Feature Model Results – CO2 in

Discharge

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Chemistry Calculation for Surface Features

• Ran a calculation with GeoChemist Workbench to obtain spring chemistry

• Reduced the CO2 content and re-calculated

• The main changes are an increase in pH (6.2 => 6.95) and a reduction in HCO3-.

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Conclusions

• Well-calibrated model for consenting purposes

• Matches many different aspects of flow in the

reservoir

• Pressures can be controlled for 50 MWeexpansion scenario

• Impact on surface features is minor

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