Engineering: Conference Contributions
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Item Open Access Direct shear response of gravel-glass-rubber mixtures(2023) Chiaro, Gabriele; Christian, Samuel; Goldingham, Logan; Murali , ArjunThis paper reports on preliminary results of a feasibility study aimed at evaluating the potential use of recycled crushed green glass bottles and recycled granulated tire rubber mixed with gravel. Specifically, dry specimens of selected gravel-glass-rubber mixtures (GGRMs) are tested using a medium-size (100 mm × 100 mm × 53 mm - width × length × height) direct shear apparatus under three normal stress levels: 30, 60 and 100 kPa. The effect of glass and rubber content by volume on the peak shear strength, friction angle and energy absorption of the mixtures is investigated. It is shown that GGRMs having 40% rubber content by volume possess adequate strength (i.e., friction angle > 30o), reduced compressibility and excellent energy absorption properties, making such materials suitable structural fills for typical geotechnical applications.Item Open Access The hydromechanical behaviour of unsaturated loess in slopes, New Zealand(EDP Sciences, 2023) Yates, Katherine; Russell, Adrian; Bardanis MUnsaturated loess and loess-derived soils in the Akaroa harbour area of New Zealand are vulnerable to shallow landsliding during rainfall events. Laboratory testing and long-term field instrumentation has been conducted to characterise the water retention and unsaturated shear strength of these materials, and better understand temporal changings in slope stability. Laboratory test results indicate that the same soil-water characteristic curve can be applied to both recompacted and intact loess when suction is normalised by the air entry value. Conversely the stress-strain behaviours of the recompacted and intact loess were different due to the unique microstructure of the intact loess that contributes to its shear strength. Long-term field instrumentation data showed that, for the duration of the monitoring period, the hydraulic state of the loess remained on a scanning curve. These data, combined with the laboratory testing, confirm that temporal variation in slope stability can be attributed to seasonal variability in suction and its contribution to unsaturated shear strength. These hydromechanical variabilities, resulting from wetting and drying, are affected by rainfall intensity and duration that occurs at the site.Item Open Access Uncertainty estimation of connected vehicle penetration rate(Institute for Operations Research and the Management Sciences (INFORMS), 2022) Jia , Shaocheng; Wong , S. C.; Wong , WaiKnowledge of the connected vehicle (CV) penetration rate is crucial for realizing numerous beneficial applications during the prolonged transition period to full CV deployment. A recent study described a novel single-source data penetration rate estimator (SSDPRE) for estimating the CV penetration rate solely from CV data. However, despite the unbiasedness of the SSDPRE, it is only a point estimator. Consequently, given the typically nonlinear nature of transportation systems, model estimations or system optimizations conducted with the SSDPRE without considering its variability can generate biased models or suboptimal solutions. Thus, this study proposes a probabilistic penetration rate model for estimating the variability of the results generated by the SSDPRE. An essential input for this model is the constrained queue length distribution, which is the distribution of the number of stopping vehicles in a signal cycle. An exact probabilistic dissipation time model and a simplified constant dissipation time model are developed for estimating this distribution. In addition, to improve the estimation accuracy in real-world situations, the braking and start-up motions of vehicles are considered by constructing a constant time loss model for use in calibrating the dissipation time models. VISSIM simulation demonstrates that the calibrated models accurately describe constrained queue length distributions and estimate the variability of the results generated by the SSDPRE. Furthermore, applications of the calibrated models to the next-generation simulation data set and a simple CV-based adaptive signal control scheme demonstrate the readiness of the models for use in real-world situations and the potential of the models to improve system optimizations. Funding: This work was supported by The University of Hong Kong [Francis S Y Bong Professorship in Engineering and Postgraduate Scholarship] and by the Council of the Hong Kong Special Administrative Region, China [Grants 17204919 and 17205822]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2023.1209 .Item Open Access Investigation of mesh sensitivity in coupled thermal-hydrological-mechanical models: examples from Desert Peak, Nevada, USA and Ngatamariki, New Zealand(2013) Kelkar, S.; Dempsey, David; Zyvoloski, G; Pogacnik, JDempsey et al. (this issue) have presented validation of a coupled thermal-hydrological-mechanical model through a comparative study of shear stimulation in geothermal fields at Desert Peak, Nevada, USA and Ngatamariki, New Zealand. Values of model parameters obtained from such validation studies are often used for extrapolating the model results beyond the domain of available experiments. Thus it is important to consider the sensitivity of these results to the specifics of the model setup as well as uncertainties in input parameters. In this presentation, we consider the sensitivity of history-matched parameter values to the numerical meshes on which computations are performed. During well stimulation, it has been noted that injectivity varies with time according to a power law, i.e., ࡵࡵ ∝ ࢚, with ranging between 0.3 and 0.7. Dempsey et al. propose that depends on the geometry of the stimulated region. However, this result is dependent on permeability enhanced according to a Mohr-Coulomb failure criterion, which is informed by the stress solution. It is well known that that the finite element method, in linear elastostatics, displays optimal rates of convergence in the L2 norm of stress error with mesh refinement (Zienkiewicz and Taylor, 1994). However, the situation is significantly more complicated in fully-coupled THM modelling. Stress-induced permeability changes affect both the fluid mass balance and energy/enthalpy balance equations and the subsequent convergence of the entire coupled system of equations. Relying on solutions found on an un-converged discretization could result in significant errors. We evaluate this dependence for several grid geometries to establish the robustness of the model findings.Item Open Access A Framework for Robust Analysis and Visualization of Geothermal Prospectivity(2016) Harp , Dylan R.; Lin, Youzuo; Glassley, William; Dempsey, David; Karra, Satish; Person, Mark; Middleton, RichardWe describe a framework to synthesize geothermal data streams by joint inversion. Geothermal production robustness, a nonprobabilistic metric of geothermal prospectivity, is defined as the amount that uncertain model parameters can deviate from nominal, best-fit values and still produce simulations that meet geothermal production criteria. Larger parameter deviations indicate greater robustness in geothermal prospectivity. Results are automatically presented as 3D robustness maps using the open-source visualization software ParaView allowing interactive interpretation of the results.Item Open Access Approaches to imaging feedzone diversity with case studied from Sumatra, Indonesia and the Taupō Volcanic Zone, New Zealand(2020) Wallis I; Rowland, J; Dempsey, David; Allan, G; Sidik, R; Martikno, R; McLean, K; Sihotang, M; Azis, H; Baroek, MThere is a fast-growing inventory of studies on borehole image logs acquired in geothermal reservoirs as more operators elect to deploy this technology. Our contribution to this inventory is to illustrate how judicious use of these data may reveal the geologic controls on permeability. We also provide an open source Python library that enables others to replicate the methods described herein. Our study includes a discussion of geometric sample bias, as well as those data integrity and geological factors that influence fracture frequency. We also demonstrate slip tendency modelling as an approach to identifying fractures that may be relevant beyond the borehole wall, which is key for geothermal wells where thermal stresses have enhanced both the number and apparent aperture of fractures at the borehole wall. We illustrate these methods using seven well case studies from a wide range of lithologies, four reservoirs, and two tectonic settings—one dominated by a volcano-tectonic rift and the other a mega-shear zone. The reservoirs are Muara Laboh and Rantau Dedap in Indonesia and Ngatamariki and Wairakei in New Zealand.Item Open Access Heat Extraction Analysis of Multi-Stage Hydraulic Fracturing Doublet Horizontal EGS Wells(2021) Yu, P; Dempsey, David; Archer REnhanced Geothermal System (EGS) are developed using various stimulation technologies to improve the production of heat energy from hot dry rock (HDR) that has ultra-low permeability. In this study, a horizontal EGS well design with partially bridging multistage hydraulic fractures is presented. Based on the proposed design, a semi-analytical model for temperature is derived assuming bi-linear heat transfer in the fractures and stimulated reservoir volume (SRV). The model considers heat conduction and advection in the SRV, and, depending on the number and spacing of fractures, can be used to optimize EGS design. A 3D numerical model is also developed to validate the semi-analytical model and test geometry effects. The numerical model is constructed in the COMSOL finite element solver and compared to a fully bridging hydraulic fracture design. The results show that the partially bridging design can obtain a longer period of high temperature production, delaying thermal breakthrough by forcing water to traverse the SRV.Item Open Access A Users Guide to Leak-off Test Procedures and Interpretation for Geothermal Wells(2021) Wallis I; Pye, DS; Dempsey, David; Rowland, JLeak-off Tests (LOT) and Extended Leak-off Tests (XLOT) are conducted during drilling to verify the competence of the cement around a casing shoe and determine the maximum allowable mud weight for the next hole section. (X)LOT interpretation yields the fracture gradient, which is a key parameter in well control procedures, mud program design and cement operations. These data are also one of the minimum requirements for any geomechanical study that seeks to understand the role fractures play in reservoir permeability. Despite its utility for successful well completion and studies investigating reservoir permeability, (X)LOT procedures are often poorly implemented and the interpretation methods used are not always appropriate for geothermal conditions. Using a case study, we describe the test procedures and interpretation process for typical geothermal conditions. We address key issues that set geothermal apart from oil and gas, such as the impact of high temperatures on test results, the high frequency of naturally occurring fractures, and the variable physical properties of hydrothermally altered volcanic rocks. We illustrate the impact of quality checking an existing (X)LOT dataset and review methods for estimating the fracture gradient prior to drilling in extensional environments. While our paper addresses a number of detailed technical issues related to interpretation, it aims to be a pragmatic and geothermally-relevant guide for those who aspire to improve the quality of these tests.Item Open Access Reservoir Microearthquake Modeling Analysis: a Proof-of-concept Study and Its Application to Injection Fluid-Induced Seismicity(2021) Rivera, J; Dempsey, DavidMicroearthquakes (MEQs) occur when fluid is reinjected into the reservoir, raising the pressure in the vicinity of the injection well. The pressure build-up in the reservoir due to fluid injection decreases the rock yield strength, which causes shear failure, thus triggering a seismic event. This mechanism presents a further opportunity to use microseismicity as a means to calibrate reservoir parameters, particularly the active faults which tend to be the most conductive fluid flow pathways. The study aims to integrate MEQ modelling to the reservoir development workflow and to the calibration workflow to estimate the permeability of the formations and the faults. The proof-of-concept study considers a synthetic induced seismicity model which represents an area where the fluid is being injected. Reservoir simulation is conducted to evaluate pressure migration through the reservoir for a given reservoir and fault parameters. The earthquake model uses the pressure change from the simulation to compute the average seismicity rate of the fault as well as the spatiotemporal evolution of the seismic events. Synthetic MEQ data is then generated from the earthquake simulation using the Poisson model, which serves as the data for calibration and inverse modelling. Synthetic inversion is then performed to estimate the permeability of both the reservoir and the fault using Markov Chain Monte Carlo (MCMC) sampling method. The study also includes the effects of variation in MEQ data and other uncertainties in the model in parameter estimation. The method developed in this study is then applied to an injection fluid-induced seismicity from a wastewater injection site.Item Open Access Measuring heat flux dynamics through the clay cap in the Wairakei-Tauhara geothermal field(2021) Ardid, A; Archer R; Sepulveda, F; Dempsey, DavidThis paper develops a multidisciplinary analysis of the extent, stratigraphic context, and thermal structure of the hydrothermally altered clay cap in the Wairakei-Tauhara geothermal field of New Zealand. We recovered unprecedented information on the clay cap geometry and heat transfer dynamics that helps in the understanding of these complex hydrothermal systems. First, using a joint inversion of magnetotelluric (MT) and methylene-blue (MeB) data, we imaged a ~300 m thick conductive clay cap that tracks the primary aquiclude overlying a distinct reservoir unit. Then, by mapping wells temperature and lithology into this structure, we differentiated contemporary hydrothermal clays from relict clays as well as those formed under diagenetic alteration. Also, we confirmed a broad temperature formation range of between 59±15 °C and 199±20 °C for the electrically conductive smectite clay. Finally, by applying a simple heat transfer model that captures vertical conductive and advective heat flow through the inferred clay cap, we estimated a lower bound of 380±21 MW for the system heat output. Additionally, we tested the incorporation of the clay cap inferred from MT inversions into geothermal reservoir simulations. The inferred clay cap was mapped to a reservoir permeability model to simulate temperatures with the reservoir simulator AUTOUGH2. Modelled temperatures were then compared to observed temperature logs as well as prior models using standard techniques (i.e., without MT information). We applied this scheme to a calibrated permeability model for the Wairakei-Tauhara geothermal field. Results indicated that our inclusion of the low permeability structure led to reductions in the model misfit to temperature logs. The developed methods allow studying uncertainties when inferring clay cap properties in high-temperature geothermal fields. Imaging the clay cap serves as a guide for developing conceptual models and for defining drilling targets, so the uncertainty inferred for these estimations is of great importance.Item Open Access Analysing induced seismicity in geothermal reservoirs: a modification of the Hall Plot(2016) Mattie , Taylor; Dempsey, DavidThe Habanero-1 well in the Cooper Basin, Australia and RRG-9 well in the Raft River geothermal field in the United State are two examples of an enhanced geothermal system. Both underwent hydraulic stimulations and experienced notable amounts of injection induced seismicity. Hall’s method plots the time integrated wellhead pressure versus the cumulative injection volume, with changes in the slope of the plot indicating changes in injectivity. In this paper, we analyse the induced seismicity using a modified version that plots cumulative earthquake count versus cumulative injection volume. This test provides a simple graphical interpretation of spatiotemporal features of the seismicity and any changes that occur during injection. The modified method is applied to datasets from the Cooper Basin and Raft River to analyse the seismicity and correlate this with changes in reservoir properties. In the case of Habanero-1, a linear trend is obtained indicating that the number of induced seismic events is directly proportional to the cumulative volume of water injected, however the high level of induced seismicity appears to be decoupled from any change in permeability. In contrast, at RRG-9, a piecewise linear slope was obtained indicating that, unlike Habanero-1, the productivity of seismic events with injected volume changed during the stimulation.Item Open Access Numerically Stable Computation of the Thermodynamics Properties of Water Using Splines(2021) Letourneur, M; Dempsey, David; O'Sullivan, J; O'Sullivan, M; Croucher, AIn geothermal modelling, a stable method for computing the thermodynamic properties of water – density, temperature and viscosity – is essential. Instability can lead to convergence issues within the flow simulator. For water, the most common way of computing those properties is through using either Gibbs or Helmholtz equations depending on the pressure (𝑝) and enthalpy (ℎ) region the fluid is in. However, the boundaries between the different regions present some discontinuities in the values of fluid properties, which can cause slow convergence of the flow simulator. In the past, these discontinuities have been addressed through the introduction of blending zones between regions to ensure a smooth transition. Our work aims to implement an efficient method of computing fluid properties that builds in property and derivative continuity across the entire 𝑝-ℎ domain. We do this by using bivariate splines with optimised, non-uniform knot locations. In addition to increased stability of the computation, this grants easy access to the derivatives of fluid properties with respect to pressure and enthalpy. This is important for some methods of reservoir simulation and optimization. The methodology presented in this paper is as follows. First, we assemble data related to the water properties we are interested in. Second, we introduce an algorithm capable of building a bivariate spline approximation that captures the complexity of our datasets while remaining sufficiently smooth. Third, we perform a quality check on the relative errors, partial derivatives and continuity of our surfaces. Finally, we implement our thermodynamic formulation into a flow simulator in order to assess its performance and precision.Item Open Access Optimising a One Million Block Grid for a TVZ Flow Model(2018) Letourneur, M; Dempsey, David; O'Sullivan, J; Croucher, A; O'Sullivan, MThe recently developed multiphase geothermal flow simulator, Waiwera, is now able to handle unstructured grids. However, to reduce errors related to the grid, certain quality factors should be optimised. In applying the finite volume method, Waiwera assumes that for each pair of neighbouring tetrahedral cells the line connecting their centroids is perfectly orthogonal to their shared interface. Any deviation from orthogonality will introduce an error in the flow simulation. Our work aims to optimize a given grid so as to minimise departures from orthogonality as much as possible. Our algorithm is written in Python. It uses the MeshIO library to read and write various formats of mesh files, and the SciPy library for optimisation algorithms. Our approach is to minimise the sum of all deviations from orthogonality within the mesh. The inputs are the node coordinates and connectivity and any surface constraints (e.g., model boundaries, faults). Then, our algorithm moves the nodes around in space in an attempt to minimise deviations from orthogonality. Several challenges were addressed in developing the optimisation algorithm. First, we require that some nodes should be constrained to move only along boundaries (model edges, topography, faults) so that geometric features honoured by the original mesh are not altered. This reduces a node’s degrees of freedom from 3 – the number of coordinate directions - to (3 – n), where n is the number of boundaries the node lies on. As a result, the algorithm can handle plane and complex boundaries (including faults and topography), intersections between planes and between a plane and a complex surface. Second, we aimed to minimise the running time of the algorithm so that the approach is practical for full-sized meshes (up to one million blocks). This included implementing and passing analytical Jacobians to the optimiser, and the use of multiprocessing to subdivide and parallelise optimisation of mesh subsections. The mesh is divided into m sets of disjoint (non-overlapping, non- adjacent) node clusters, where 𝒎𝒎 is the number of parallel processors, and each cluster contains 𝒌𝒌 nodes. The coordinates of the 𝒌𝒌 nodes are optimised and updated before a new set of 𝒎𝒎 disjoint clusters are chosen. Calibrating tolerance parameters carefully, we are able to achieve convergence of an optimal mesh in less than 10 iterations (for a 10 4 node mesh we have achieved optimisation in just over 90 seconds). In this paper, we present the algorithm details, several test cases, and a challenge mesh: a one million block grid of the TVZ, with realistic topography, and approximate faults and basement contactItem Open Access Machine learning investigation of injection-seismicity in Rotokawa geothermal field(2021) Yu, Pengliang; Dempsey, David; Calibugan A; Archer RUnderstanding the injection-seismicity relationship in geothermal reservoirs can provide insight into reservoir connectedness. One challenge is that, in real fields, fault and reservoir complexity make it difficult to apply simple analytical models to understand the data. Here, we use a machine learning technique called time-series feature engineering to study relationships between aspects of fluid injection and microearthquakes in Rotokawa geothermal field, New Zealand. We took four years of injection data between 2012 and 2016 and sliced it into smaller sub-windows. For each window, the average seismicity in a look-back period was computed, and then binary label of 1 was assigned if it exceeded a threshold. Automatic time series feature extraction from the raw and transformed injection data in each window was performed using Python package tsfresh. Significant features of the data were identified on the basis of distribution discrepancy between the two labels. The results show that the injection rate at some wells is a predictor of long term (fortnightly) earthquake rates. At other wells, there is a poor correlation between injection rate and seismicity. We have been unable to find any link between rapid changes in injection rate and seismicity spikes, as suggested by some theoretical models.Item Open Access Pitching to the `Big Fish': Elevating Presentation and Communication Skills in a Software Quality Course(2023) Morales Trujillo, Miguel Ehécatl; Caballero, IsmaelIn this work, we present a Software Quality teaching experience based on gamification. In this experience, “A Meeting with the Big Fish”, the lecturer and students play different roles in a Shark Tank-like situation. The lecturer (Big Fish) and their sharks maintain a planned meeting with students where harsh and unexpected situations happen to students while presenting a Software Process Improvement proposal. Initial results have shown the effectiveness of the activity in terms of engagement, fun, and authenticity.Item Open Access Estimation of pressure and permeability enhancement distribution using induced earthquake hypocenter density for the 2011 Paralana EGS stimulation(2016) Riffault , Jeremy; Dempsey, David; Karra , Satish; Archer, RosalindTo create an Enhanced Geothermal System (EGS), cold water is injected at high pressure, along with acid, with the goal of reactivating pre-existing fractures and enhancing their permeability. Through increases in pore pressure and associated stress changes, shear failure occurs, which is part of the permeability enhancement process, but also results in induced seismicity. In spite of being the primary goal of stimulation, details about the spatiotemporal evolution of permeability are difficult to determine. One measure of its improvement is the increase in well injectivity, which is defined as the injected flow rate divided by the wellhead pressure. However, this measure is sensitive to both the volume of stimulated rock as well as the permeability increase, and so it does not uniquely constrain the stimulation state. To augment this analysis, we present an inverse modelling approach that incorporates both the injection records and the spatiotemporal distribution of induced seismicity. We present an application of the method to the Paralana-2 EGS stimulation undertaken in 2011 in South Australia. High pressure injection is modelled by solving coupled flow and heat transport equations in the reservoir simulator FEHM. In the model, the magnitude of permeability increase is a prescribed function of space and time. The injectivity profile observed at Paralana limits the possible set of permeability evolution scenarios, however, additional constraint is necessary to choose amongst these. As induced seismicity is a consequence of elevated pore pressure, we assume that the density of earthquake hypocenters is proportional to pore pressure rise. By comparing the pressure profiles modelled in the different scenarios to the high-resolution microearthquake data collected during the stimulation, we can pick the permeability enhancement distribution scheme most consistent with the injectivity and seismicity data.Item Open Access Forward and inverse modelling of geothermal microseismicity using TOUGH2 coupled with an earthquake simulator(2017) Rivera , Julius Marvin; Dempsey, DavidReservoir modelling is undertaken to represent the physical state of the reservoir in order to estimate its current condition and to predict future responses. Prior to use of the reservoir model for forecasting, it is common to calibrate natural state and production models using temperature and pressure data gathered from downhole surveys. In addition to these data, microseismicity presents a further opportunity to calibrate reservoir parameters, in particular the permeability of active faults that serve as major fluid pathways. Microearthquakes (MEQs) occur in areas where brine produced from the production wells is reinjected. The injection causes fluid pressure to build-up in the area, which decreases the rock yield strength and promotes failure: a small earthquake. These events may occur on active faults that are also major fluid pathways in the field. The location, migration, and number of MEQs provide information about pressure change and the nature of fluid flow through the reservoir. Many fields these days are equipped with instruments to detect and locate MEQs. The objective of this project is to integrate MEQ data into the reservoir model development workflow so as to assist model calibration and reservoir characterization. In this project, a simple reservoir model is created to represent an area into which fluid is injected. A forward run using the TOUGH2 reservoir simulator is conducted to estimate pressure changes due to injection into a single well for specified reservoir and fault parameters. Pressure change on the fault is used to compute an average seismicity rate as well as individual MEQ locations and times. Sensitivity analysis has been conducted to understand how model parameters affect the amount of seismicity generated, and the manner in which it travels along the fault. The coupling between reservoir pressure evolution and synthetic microseismicity provides the physical link necessary to use field MEQ data for calibration. In particular, we will use the seismicity migration rate to estimate permeability of the reservoir and faults. The synthetic study presented here is a proof-of concept before application of the approach to an actual geothermal MEQ dataset.Item Open Access Quantifying the influential factors affecting performance variation of stormwater treatment systems: an example from a stormwater membrane treatment system(2023) Bilek , F; Charters, Frances; Cochrane , TItem Open Access Comparing Measures of Linguistic Diversity Across Social Media Language Data and Census Data at Subnational Geographic Areas(2022) Wong S; Dunn J; Adams, BenjaminThis paper describes a preliminary study on the comparative linguistic ecology of online spaces (i.e., social media language data) and real-world spaces in Aotearoa New Zealand (i.e., subnational administrative areas). We compare measures of linguistic diversity between these different spaces and discuss how social media users align with real-world populations. The results from the current study suggests that there is potential to use online social media language data to observe spatial and temporal changes in linguistic diversity at subnational geographic areas; however, further work is required to understand how well social media represents real-world behaviour.Item Open Access Carbon Negative Geothermal: Financial Analysis for Combined Geothermal, Bioenergy and Carbon Dioxide Removal(2022) Titus, K; Archer, R; Peer, R; Dempsey, DavidCoupling bioenergy with carbon capture and storage (BECCS) is a net carbon negative process that has been highlighted by the Intergovernmental Panel on Climate Change as an important technology for offsetting greenhouse gas emissions. Despite their proposed efficacy as both a power production and negative emissions tool, BECCS technologies currently lack widespread use due to their high costs. Coupling geothermal fields with BECCS operations by dissolving biogenic CO2 in geothermal brine could reduce the transportation and injection costs by leveraging geothermal reinjection apparatus for sequestration. Dissolved biogenic CO2 could be stored more safely in a geothermal reservoir through pressure maintenance, sidestepping leakage concerns from storing buoyant supercritical CO2. Additionally, geothermal and bioenergy synergize as electricity generation technologies, leading to higher utilization efficiencies. Our analysis shows that geothermal-BECCS plants could have operational emissions intensities of -137 gCO2/kWh to -928 gCO2/kWh, offsetting 30% to 206% of the emissions from a standard natural gas plant. For the CO2 price of NZD 80/tonne in 2022, geothermal-BECCS could have a levelized cost of electricity (LCOE) of NZD 163 to 203/MWh, cheaper than overseas standalone BECCS estimates NZD 267 to 426/tonne. For a projected CO2 price increase of NZD 160/tonne by 2035 suggested by the Climate Change Commission, geothermal-BECCS plants could have LCOEs as low as NZD 29 to 54/MWh. This would be more competitive than geothermal plants while also removing up to 110,000 tonnes of CO2 a year.