gisera’s water research projects in northern nsw

GISERA’s water research projects in northern NSW

1. Impacts of CSG depressurisation on the Great Artesian Basin (GAB) flux [ Sreekanth et al, CSIRO Land and Water, Jun 18]

2. Data-worth and spatial design of groundwater monitoring network in the Narrabri Gas Project area [Sreekanth et al, CSIRO Land and Water Mar 18]

3. Improving the representation of the impact of CSG in groundwater models [ Connell et al, CSIRO Energy Nov 18]

GISERA water research NSW| 30 Aug 2018 | 1

Impacts of CSG depressurization on Great Artesian Basin flux

Sreekanth Janardhanan, Trevor Pickett, Dennis Gonzalez, Tao Cui, Mat Gilfedder, David Rassam, Matthias Raiber, Axel Suckow, Kate Holland, Damian Barrett, Dan O’Sullivan, Alec Deslandes, Helen Beringen, Nicola Proctor 30 August 2018

Stratigraphy

3

Inter-burden 2

Inter-burden 1

GISERA water research NSW| 30 Aug 2018 |

4GISERA water research NSW| 30 Aug 2018 |

Basin Formation type Model layer

Zone 1 Namoi alluvium alluvium 1 - 2

Zone 3 Surat Basin Inter-burden 3 - 5

Zone 6 Surat Basin Pilliga Sandstone 6

Zone 8

Gunnedah Basin Interburden 7 – 9; 11 - 13

Gunnedah Basin Coal 10, 14

Conceptualisation in the numerical model

5|

Objectives

● Measurement and analysis of new environmental tracers and hydrochemistry data to improve conceptual understanding of recharge

● Integrating the knowledge derived from new data and ongoing work (OWS projects BA, FAM) into the conceptual understanding of the Surat and Gunnedah basins

● Predictive analysis of potential impacts of CSG development on drawdown and GAB fluxes

● Use the predictive uncertainty anlysis to inform data-worth and monitoring strategies


Groundwater model built for the Namoi Bioregional Assessments

6| GISERA water research NSW| 30 Aug 2018 |

Groundwater modelling for the Namoi subregion (Sreekanth et al, 2018)

Probabilistic modelling approach for a generic CSG development scenario

● Water production rates are not hard-wired as a boundary condition in the model

● Instead, the model simulates the water production for a given depressurization target

● Accounts for the uncertainty in CSG water production

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Sensitivity analysis

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Vertical hydraulic conductivity of the inter-burden layers: most sensitive parameter that influences the

propagation of depressurization upwards into the Pilliga Sandstone


Conceptualisation of hydraulic properties


Observed depth-dependency and spatial variability from core, DST, packer and pump test data ( Aryal et al, 2018;

Turnadge et al, 2017, Sreekanth et al, 2018)

Inter-burden hydraulic properties


AQUIFER

Santos GIA

Vertical hydraulic conductivity of the numerical model layer 7 immediately underneath the Pilliga Sandstone (

Purlawaugh formation)

AQUTARD

Spatial variability of vertical hydraulic conductivity in the inter-burden layer 8


Key findings – CSG induced GAB Flux changes

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(a) (b)


Predicted CSG impacts to water volumes in the GAB aquifer

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Volume (GL/y) Source

Estimated Recharge (GAB NSW Total) 295 BRS report (Habermehl, 2009)

Estimated recharge Southern Recharge Source (SRS)

42.4 NSW Water Sharing Plan

Lont-term Annual Average Extraction Limit (LTAAEL)

29.68 NSW Water Sharing Plan

Stock and domestic use 3.0 NSW Water Sharing Plan

Unlikely that the maximum CSG flux impact in any year will exceed

2.3 This study

Likely that the maximum CSG flux impact will be around

0.06 This study

Likely that CSG flux impact will be more than 0.0001 This study


0.27

0.06

0.0001

0 50 100 150 200 250 300 350

Recharge (GAB NSW total)

Estimated recharge (SRS)

LTAAEL

Stock and Domestic right estimate

95% precited maximum CSG flux impact

Median of predicted maximum CSG flux impact

5% predicted maximum CSG flux impact

Water volume (Giga litre/year)

Other estimates Highly parameterized model Parsimoniously parameterized model

3

29.68

42.4

295

Conclusion - 1● Depressurization of coal seams could potentially induce small

changes in groundwater flux from the GAB aquifer to deeper formations

● The median value of the predicted maximum flux losses is 60 ML/year which is about 0.2 % of the Long-term Annual Average Extraction Limit set for the the Southern Recharge Source.


Data-worth and spatial design of groundwater monitoring network in the Narrabri Gas Project area

Sreekanth Janardhanan, Dan Gladish, Trevor Pickett, Dennis Gonzalez, Dan Pagendam, Tao Cui, Mat Gilfedder, David Rassam, Damian Barrett, Dan O’Sullivan, Helen Beringen, Nicola Proctor 30 August 2018

Method overview

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START

Flow model (MODFLOW USG)

Particle trackingMod-PATH3DU

Drawdown in model layers

Travel times, distances, velocities

Geostatistical spatial models

Baseline WQ variance

Optimal monitoring design(s)Data worth analysis

STOP

MODELS

MONTE-CARLOSIMULATIONS

LINEAR ANALYSIS

GLOBAL OPTIMIZATION



Maximum drawdown impacts

Travel distances within a modelling period of 100 years


Ensemble predictions to inform potential future monitoring locations to observe CSG-induced drawdown

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Layer 6 Layer 7 Layer 12

Dmax – Maximum CSG-induced drawdown

Tmax – Time at which maximum CG-induced drawdown occurs


Monitoring network design

● Monitoring within predicted drawdown area to verify and refine the predictions


Monitoring network used in data-worth analysis

Potential monitoring bore sites

Current GAB monitoring bores within the predicted drawdown area● Current density of

montoring bores ~4.2 bores/100 km2


Receptor locations for data-worth analysis

GISERA water research NSW| 30 Aug 2018 | 22GISERA water research NSW| 30 Aug 2018 |

Data worth of observations

23

a


Conclusion – 2

● Probabilistic predictive analysis resulted in a median predicted drawdown to be less than 0.2m for most of the areas within and beyond the gas project area

● Probabilistic particle tracking analysis indicated that velocity of groundwater flow in the Pilliga Sandstone aquifer is slow and particles may travel on the order of 100s of metres within a simulation period of 100 years.

● The current density of GAB monitoring bores is approximately 4.2 bores/100 km2

● Data-worth analysis indicated that nested monitoring bores within the 95th percentile drawdown area and especially monitoring formations underneath the Pilliga Sandstone returns maximum data-worth

● A design for a network of 10 bores and the data-worth emerging from that is demonstrated in this study


IESC advice to decision maker on Narrabri Gas Project –gaps addressed by GISERA study

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IESC comment number GISERA research

Q1.2, Q1.13, Q2.15 Improve confidence in modelled heads in target seams instead of specified flux boundary condition for coal seasm gas

Used target heads in coal seams/formations (projects 1). Project 3 will help to refine this further

Q1.3, Q1.6f Groundwater model parameterisation, calibration, uncertainty and sensitivity analysis. Monitoring points for data collection could be identified based on uncertainty analysis

Investigated two different parameterisationschemes, undertook calibration, sensitivity and uncertainty analysis (projects 1 and 2)

Q1.6b, 2.17 “measuring heads directly above and below tightest aquitards would allow constrain aquitard properties”

Our monitoring design study (project 2) establishes this using quantitative analysis that multi-level piezometers would be most useful in refining predictions


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IESC advice to decision maker on Narrabri Gas Project –gaps addressed by GISERA study

IESC comment GISERA study

Q1.6d Consideration should be given to use methods like Turnadge et al (2017) in assessing effects of changing permeability and storativity particularly in areas with overlying sensitive receptors

We have used the data/knowledge from Turnadge et al and have assessed the drawdown effects from varying permeability and storativity in the uncertainty analysis

Q1.6e “range of different hydrogeological conceptualisations and methods to address uncertainties in recharge”

In this study we used environmental tracers to understand recharge. We also evaluated wide range of variabilities in recharge in the model while predicting the impacts

Q1.6h “robust estimates of evapotranspiration in the model”

We have spatially varying evapotranspiration considering vegetation height


Thank you

Sreekanth JanardhananSenior Research Scientist

t +61 7 3833 5565e [email protected] gisera.org.au

Acknowledgements● Jizelle Khoury● Henning Prommer● Catherine Moore● Ryan Morris● Andrew Moser● Saeed Torkzaban● Raman Pandurangan● Luke Connell● Melita Keywood● Andrea Walton● Helen Beringen● Dan O’Sullivan● Nicola Proctor● Russell Crosbie● Luk Peeters● Glenn Toogood● John Doherty● Liz Tearall● David Rassam

● Neale House● Sue Hamilton● Jim Underschultz● Tim Ransley● Steven Flook● Cate Barrett● Andrew McCallum● Andrew Druzynski● Fabienne d’Hautefeuille● Phil Davies● Tim Ransley● Emily Slatter● Jessica Northey● Keith Phillipson● Researchers of the Bioregional Assessment Programme● David Post


gisera’s water research projects in northern nsw

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