Geochemistry monitoring of CO2 storage at the CO2CRC Otway Project, Victoria: operational mode

2009 ◽  
Vol 49 (2) ◽  
pp. 602
Author(s):  
Chris Boreham ◽  
Jim Underschultz ◽  
Linda Stalker ◽  
Barry Freifeld ◽  
Dirk Kirste ◽  
...  
Keyword(s):  
Supercritical Co2 ◽  
Co2 Storage ◽  
Co2 Injection ◽  
Operational Mode ◽  
Water Contact ◽  
Tracer Injection ◽  
Flow Models ◽  
Chemical Tracers ◽  
Tube Assembly ◽  
Operational Issues

The CO2CRC Otway Project is an Australian-first, demonstration-scale CO2 geosequestration experiment. It incorporates a wide-ranging monitoring and verification operation, including the injection of chemical tracers and the geochemical characterisation of the subsurface fluids sampled from the Naylor—1 monitoring well multi-zone U-tube system. Following the successful collection of baseline gas and fluid samples, injection began in April 2008 and by September 2008 over 20,000 tonnes of the projected total of ∼100,000 tonnes of supercritical CO2 has been injected into the depleted Waarre C unit of the Naylor gas reservoir in the Otway Basin. Critical operational issues revolved around the timing of the chemical tracer injection at the CRC—1 injection well and the on-going maintenance and modifications to the U-tube sampling assembly. The latter resulted from two things:a hazard and operability study (HAZOP), which specifically addressed the continued integrity of the U-tube assembly and the safe collection and disposal of pressurised gases and formation waters, and the need for an innovative solution to mitigate against hydrocarbon wax precipitaton inside the U-tubes that would have jeopardise retrieval of sub-surface samples. A solvent delivery and retrieval system involving Solvesso—100TM was deployed following a mini-HAZOP. Breakthrough was initially confirmed by tracer detection at Naylor—1 approximately four months after injection began, whereas changes in the inorganic geochemical signatures were observed a few weeks later. This has validated the sub-surface monitoring strategy and resulted in refinements to fluid flow models and expanded our understanding of geochemical processes. Furthermore, supercritical CO2 injection has resulted in the lowering of the gas-water contact at Naylor—1 and the progressive gassing out of the deeper U-tubes. Weekly to fortnightly U-tube sampling will continue until supercritical CO2 is established at Naylor—1 following which the frequency of sampling will be reviewed for the rest of the injection period.

The role of supercritical CO2 in gas well health issue – liquid loading

2020 ◽  
Vol 60 (1) ◽  
pp. 143
Author(s):  
Bashirul Haq ◽  
Fahad Shehiwin ◽  
Dhafer Al Shehri ◽  
Jishan Liu ◽  
Nasiru Muhammed ◽  
...  
Keyword(s):  
Surface Tension ◽  
Supercritical Co2 ◽  
Co2 Storage ◽  
Health Issue ◽  
Co2 Injection ◽  
Liquid Loading ◽  
Well Productivity ◽  
Liquid Load ◽  
The Impact

Liquid load or condensate banking is a common well health issue in gas/gas-condensate reservoirs that decreases well productivity by a factor of two to four. Due to the depletion of bottom-hole pressure, the produced liquid accumulates around the wellbore and creates a static column of liquid that reduces gas production until well production ceases. Enhancing gas recovery by CO2 injection is a promising technology because it reduces greenhouse gas emissions and improves CO2 storage. More investigation needs to be conducted to understand the role of supercritical CO2 (SCCO2) in minimising liquid loading. The aim of this research is to examine the impact of SCCO2 in surface tension, condensate viscosity and well productivity. This study consists of simulation and laboratory experiments. Eclipse 300 was used to develop a model that examines the effect of SCCO2 injection on reducing liquid loading issues by varying the well parameters. We found that injecting SCCO2 improved the microscopic displacement efficiency and minimised liquid loading by decreasing the condensate viscosity and the surface tension. The model shows that (1) condensate recovery increases when the injection rate increases up to a limit after which there is no change of production and (2) condensate recovery improves with decreasing production rate.

4D surface seismic tracks small supercritical CO2 injection into the subsurface: CO2CRC Otway Project

2017 ◽  
Vol 63 ◽  
pp. 150-157 ◽  
Author(s):  
Roman Pevzner ◽  
Milovan Urosevic ◽  
Dmitry Popik ◽  
Valeriya Shulakova ◽  
Konstantin Tertyshnikov ◽  
...  
Keyword(s):  
Supercritical Co2 ◽  
Co2 Injection ◽  
Supercritical Co2 Injection

Experimental and Modeling Study of Salt Precipitation During Injection of CO2 Contaminated With H2S Into Depleted Gas Fields in the Northeast of the Netherlands

SPE Journal ◽  
2014 ◽  
Vol 19 (06) ◽  
pp. 1058-1068 ◽  
Author(s):  
P.. Bolourinejad ◽  
R.. Herber
Keyword(s):  
The Netherlands ◽  
Carbonic Acid ◽  
Co2 Storage ◽  
Mineral Dissolution ◽  
Co2 Injection ◽  
Salt Precipitation ◽  
Geological Time ◽  
Core Samples ◽  
Carbon Dioxide Co2 ◽  
Gas Fields

Summary Depleted gas fields are among the most probable candidates for subsurface storage of carbon dioxide (CO2). With proven reservoir and qualified seal, these fields have retained gas over geological time scales. However, unlike methane, injection of CO2 changes the pH of the brine because of the formation of carbonic acid. Subsequent dissolution/precipitation of minerals changes the porosity/permeability of reservoir and caprock. Thus, for adequate, safe, and effective CO2 storage, the subsurface system needs to be fully understood. An important aspect for subsurface storage of CO2 is purity of this gas, which influences risk and cost of the process. To investigate the effects of CO2 plus impurities in a real case example, we have carried out medium-term (30-day) laboratory experiments (300 bar, 100°C) on reservoir and caprock core samples from gas fields in the northeast of the Netherlands. In addition, we attempted to determine the maximum allowable concentration of one of the possible impurities in the CO2 stream [hydrogen sulfide (H2S)] in these fields. The injected gases—CO2, CO2+100 ppm H2S, and CO2+5,000 ppm H2S—were reacting with core samples and brine (81 g/L Na+, 173 g/L Cl−, 22 g/L Ca2+, 23 g/L Mg2+, 1.5 g/L K+, and 0.2 g/L SO42−). Before and after the experiments, the core samples were analyzed by scanning electron microscope (SEM) and X-ray diffraction (XRD) for mineralogical variations. The permeability of the samples was also measured. After the experiments, dissolution of feldspars, carbonates, and kaolinite was observed as expected. In addition, we observed fresh precipitation of kaolinite. However, two significant results were obtained when adding H2S to the CO2 stream. First, we observed precipitation of sulfate minerals (anhydrite and pyrite). This differs from results after pure CO2 injection, where dissolution of anhydrite was dominant in the samples. Second, severe salt precipitation took place in the presence of H2S. This is mainly caused by the nucleation of anhydrite and pyrite, which enabled halite precipitation, and to a lesser degree by the higher solubility of H2S in water and higher water content of the gas phase in the presence of H2S. This was confirmed by the use of CMG-GEM (CMG 2011) modeling software. The precipitation of halite, anhydrite, and pyrite affects the permeability of the samples in different ways. After pure CO2 and CO2+100 ppm H2S injection, permeability of the reservoir samples increased by 10–30% and ≤3%, respectively. In caprock samples, permeability increased by a factor of 3–10 and 1.3, respectively. However, after addition of 5,000 ppm H2S, the permeability of all samples decreased significantly. In the case of CO2+100 ppm H2S, halite, anhydrite, and pyrite precipitation did balance mineral dissolution, causing minimal variation in the permeability of samples.

scholarly journals Numerical Simulation and Optimization of CO2 Sequestration in Saline Aquifers

2012 ◽  
Author(s):  
Zheming Zhang ◽  
Ramesh Agarwal
Keyword(s):  
Numerical Simulation ◽  
Co2 Sequestration ◽  
Storage Capacity ◽  
Co2 Storage ◽  
Injection Well ◽  
Co2 Injection ◽  
Great Promise ◽  
Saline Aquifer ◽  
Simulation And Optimization ◽  
Co2 Plume

With recent concerns on CO2 emissions from coal fired electricity generation plants; there has been major emphasis on the development of safe and economical Carbon Dioxide Capture and Sequestration (CCS) technology worldwide. Saline reservoirs are attractive geological sites for CO2 sequestration because of their huge capacity for sequestration. Over the last decade, numerical simulation codes have been developed in U.S, Europe and Japan to determine a priori the CO2 storage capacity of a saline aquifer and provide risk assessment with reasonable confidence before the actual deployment of CO2 sequestration can proceed with enormous investment. In U.S, TOUGH2 numerical simulator has been widely used for this purpose. However at present it does not have the capability to determine optimal parameters such as injection rate, injection pressure, injection depth for vertical and horizontal wells etc. for optimization of the CO2 storage capacity and for minimizing the leakage potential by confining the plume migration. This paper describes the development of a “Genetic Algorithm (GA)” based optimizer for TOUGH2 that can be used by the industry with good confidence to optimize the CO2 storage capacity in a saline aquifer of interest. This new code including the TOUGH2 and the GA optimizer is designated as “GATOUGH2”. It has been validated by conducting simulations of three widely used benchmark problems by the CCS researchers worldwide: (a) Study of CO2 plume evolution and leakage through an abandoned well, (b) Study of enhanced CH4 recovery in combination with CO2 storage in depleted gas reservoirs, and (c) Study of CO2 injection into a heterogeneous geological formation. Our results of these simulations are in excellent agreement with those of other researchers obtained with different codes. The validated code has been employed to optimize the proposed water-alternating-gas (WAG) injection scheme for (a) a vertical CO2 injection well and (b) a horizontal CO2 injection well, for optimizing the CO2 sequestration capacity of an aquifer. These optimized calculations are compared with the brute force nearly optimized results obtained by performing a large number of calculations. These comparisons demonstrate the significant efficiency and accuracy of GATOUGH2 as an optimizer for TOUGH2. This capability holds a great promise in studying a host of other problems in CO2 sequestration such as how to optimally accelerate the capillary trapping, accelerate the dissolution of CO2 in water or brine, and immobilize the CO2 plume.

scholarly journals Managing Uncertainty in Geological CO2 Storage Using Bayesian Evidential Learning

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1557
Author(s):  
Amine Tadjer ◽  
Reidar B. Bratvold
Keyword(s):  
Uncertainty Quantification ◽  
History Matching ◽  
Co2 Storage ◽  
Carbon Capture And Storage ◽  
Monitoring Program ◽  
Co2 Injection ◽  
Drinking Water Contamination ◽  
Model Inversion ◽  
Geological Co2 Storage ◽  
And Storage

Carbon capture and storage (CCS) has been increasingly looking like a promising strategy to reduce CO2 emissions and meet the Paris agreement’s climate target. To ensure that CCS is safe and successful, an efficient monitoring program that will prevent storage reservoir leakage and drinking water contamination in groundwater aquifers must be implemented. However, geologic CO2 sequestration (GCS) sites are not completely certain about the geological properties, which makes it difficult to predict the behavior of the injected gases, CO2 brine leakage rates through wellbores, and CO2 plume migration. Significant effort is required to observe how CO2 behaves in reservoirs. A key question is: Will the CO2 injection and storage behave as expected, and can we anticipate leakages? History matching of reservoir models can mitigate uncertainty towards a predictive strategy. It could prove challenging to develop a set of history matching models that preserve geological realism. A new Bayesian evidential learning (BEL) protocol for uncertainty quantification was released through literature, as an alternative to the model-space inversion in the history-matching approach. Consequently, an ensemble of previous geological models was developed using a prior distribution’s Monte Carlo simulation, followed by direct forecasting (DF) for joint uncertainty quantification. The goal of this work is to use prior models to identify a statistical relationship between data prediction, ensemble models, and data variables, without any explicit model inversion. The paper also introduces a new DF implementation using an ensemble smoother and shows that the new implementation can make the computation more robust than the standard method. The Utsira saline aquifer west of Norway is used to exemplify BEL’s ability to predict the CO2 mass and leakages and improve decision support regarding CO2 storage projects.

Estimation of CO2 Diffusivity in Brine by Use of the Genetic Algorithm and Mixed Kernels-Based Support Vector Machine Model

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Qihong Feng ◽  
Ronghao Cui ◽  
Sen Wang ◽  
Jin Zhang ◽  
Zhe Jiang
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Diffusion Coefficient ◽  
Co2 Storage ◽  
Co2 Injection ◽  
Support Vector ◽  
Hybrid Technique ◽  
Machine Model ◽  
Proposed Model ◽  
Wide Range

Diffusion coefficient of carbon dioxide (CO2), a significant parameter describing the mass transfer process, exerts a profound influence on the safety of CO2 storage in depleted reservoirs, saline aquifers, and marine ecosystems. However, experimental determination of diffusion coefficient in CO2-brine system is time-consuming and complex because the procedure requires sophisticated laboratory equipment and reasonable interpretation methods. To facilitate the acquisition of more accurate values, an intelligent model, termed MKSVM-GA, is developed using a hybrid technique of support vector machine (SVM), mixed kernels (MK), and genetic algorithm (GA). Confirmed by the statistical evaluation indicators, our proposed model exhibits excellent performance with high accuracy and strong robustness in a wide range of temperatures (273–473.15 K), pressures (0.1–49.3 MPa), and viscosities (0.139–1.950 mPa·s). Our results show that the proposed model is more applicable than the artificial neural network (ANN) model at this sample size, which is superior to four commonly used traditional empirical correlations. The technique presented in this study can provide a fast and precise prediction of CO2 diffusivity in brine at reservoir conditions for the engineering design and the technical risk assessment during the process of CO2 injection.

A method for incorporating equilibrium chemical reactions into multiphase flow models for CO2 storage

2013 ◽  
Vol 62 ◽  
pp. 431-441 ◽  
Author(s):  
Maarten W. Saaltink ◽  
Victor Vilarrasa ◽  
Francesca De Gaspari ◽  
Orlando Silva ◽  
Jesús Carrera ◽  
...  
Keyword(s):  
Multiphase Flow ◽  
Chemical Reactions ◽  
Co2 Storage ◽  
Flow Models ◽  
Equilibrium Chemical

scholarly journals Changes in Permeability of Kimachi Sandstone and Iidate Granite with Supercritical CO2 Injection

2013 ◽  
Vol 129 (12) ◽  
pp. 701-706
Author(s):  
Takashi FUJII ◽  
Yuichi SUGAI ◽  
Kyuro SASAKI ◽  
Toshiyuki HASHIDA ◽  
Toshiyuki TOSHA ◽  
...  
Keyword(s):  
Supercritical Co2 ◽  
Co2 Injection ◽  
Supercritical Co2 Injection

Modelling and Upscaling Unstable Miscible Displacement Processes: Characterisation of Physical Instabilities

2021 ◽  
Author(s):  
Precious Ogbeiwi ◽  
Karl Stephen
Keyword(s):  
Relative Permeability ◽  
Transport Coefficients ◽  
Miscible Displacement ◽  
Co2 Injection ◽  
Co2 Flooding ◽  
Fine Grid ◽  
Flow Models ◽  
Reservoir Models ◽  
Flood Simulations ◽  
Physical Instabilities

Abstract The compositional simulations are required to model CO2 flooding are computationally expensive particularly for fine-gridded models that have high resolutions, and many components. Upscaling procedures can be used in the subsurface flow models to reduce the high computation requirements of the fine grid simulations and accurately model miscible CO2 flooding. However, the effects of physical instabilities are often not well represented and captured by the upscaling procedures. This paper presents an approach for upscaling of miscible displacements is presented which adequately represents physical instabilities such as viscous and heterogeneity induced fingering on coarser grids using pseudoisation techniques. The approach was applied to compositional numerical simulations of two-dimensional reservoir models with a focus on CO2 injection. Our approach is based on the pseudoisation of relative permeability and the application of transport coefficients to upscale viscous fingering and heterogeneity-induced channelling in a multi-contact miscible CO2 injection. Pseudo-relative permeability curves were computed using a pseudoisation technique and applied in combination with transport coefficients to upscale the behaviour of fine-scale miscible CO2 flood simulations to coarser scales. The accuracy of the results of the pseudoisation procedures were assessed by applying statistical analysis to compare them to the results of the fine grid simulations. It is observed from the results that the coarse models provide accurate predictions of the miscible displacement process and that the fingering regimes are adequately captured in the coarse models. The study presents a framework that can be employed to represent the dynamics of physical instabilities associated with miscible CO2 displacements in upscaled coarser grid reservoir models.

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