Carbon Sequestration Projects Research Articles

Are Australian carbon prices sufficient to support decarbonisation in gas production?

Recent years have seen a rapid increase in the push for energy transition in Australia. Carbon prices have been introduced through the Safeguard Mechanism and Australian Carbon Credit Units. Consumers of hydrocarbon products are beginning to demand carbon neutral products. Oil and gas operators are pledging net-zero emissions targets. The decarbonisation efforts that ensue are expected to drive a paradigm shift in upstream development approaches. In this work, we investigate how an anonymised high carbon dioxide (CO2) gas field may be developed under prevailing carbon prices. We identify three project archetypes and estimate economically recoverable resources under each project; we also analyse the economic performance of each project. In the first archetype, we consider a project where CO2 is separated from the produced gas and vented into the atmosphere. In the second archetype, we consider a carbon sequestration project in which CO2 is transported via pipeline for storage in an onshore depleted gas reservoir. Lastly, we consider a case in which the gas buyer demands a fully carbon neutral product; as such, we study the feasibility of producing blue hydrogen using the produced gas, and how this impacts project economics and reserves. The case studies quantify by how much decarbonisation efforts negatively impact project economics and how they are the least objectionable when carbon prices are high. The analysis shows that carbon prices in Australia are currently sufficient to enable commercial development in ideal situations, but need to be higher to enable wider decarbonisation.

Deep learning-assisted Bayesian framework for real-time CO2 leakage locating at geologic sequestration sites

Accurate and efficient localization of CO2 leakage if occurred in subsurface formations, is of significant importance in achieving secure geological carbon sequestration (GCS) projects. However, this task is inherently challenging due to the considerable uncertainties in the subsurface. In this work, we develop a novel deep learning-assisted Bayesian framework for identifying potential CO2 leakage sites based on the reservoir pressure transient behavior measured at the wellbores of injection or observation wells. The method consists of two essential steps: 1) Deep learning surrogate: This step aims to effectively replace the intensive high-fidelity simulation with an efficient deep learning surrogate. 2) Bayesian inversion: In this step, the posterior distributions of potential CO2 leakage locations are inverted, in which the surrogate serves as the forward model. The above two processes are automated using Bayesian optimization instead of a labor-intensive trial-and-error approach. The proposed framework is verified using a 3D geological model simulating CO2 sequestration into a brine-filled reservoir. The results demonstrate the Bayesian-optimized surrogate could successfully capture the underlying process of subsurface CO2-brine flow. The Bayesian inversion algorithm enables localizing CO2 leakage with high accuracy. To our knowledge, the proposed Bayesian framework is implemented for the first time to locate multiple leakage sites at the field scale. The proposed workflow provides an accurate and efficient approach to detecting possible CO2 leakage locations in a real-time manner and has promising potential for field-scale GCS applications.

Molecular insights into mass transfer and adsorption behaviors of hydrocarbon and CO2 in quartz multiple-nanopore system

Exploitating liquid hydrocarbons from unconventional reservoirs is playing an ever-increasing role in addressing global energy supply issues. CO2 huff-and-puff is an environmental and effective method to enhance hydrocarbon recovery and achieve CO2 geo-sequestration simultaneously, playing an important role in carbon capture, utilization, and sequestration (CCUS) projects. The optimization of huff-n-puff operations requires clarifying the adsorption state and migration behaviors of hydrocarbons and CO2 in unconventional reservoirs dominated by nanopores. In this paper, we used molecular dynamics (MD) simulation to investigate adsorption behaviors and mass transfer of CO2and n-decane (nC10) molecules in multiple quartz nanopores by carefully considering pore size and structure effects. It shows that the adsorption behaviors and replacement efficiency of oil molecules are closely related to pore aperture. Interestingly, we found that the surface adsorption of nC10 demonstrates a non-monotonic trend of rising after falling as the pore size decreases from 5 nm to 0.7 nm. Specifically, when the pore size is reduced to ∼ 1 nm, nC10 molecules exhibit a pseudo-double layered distribution state. In such a nanopore, the surface adsorption of nC10 is significantly weakened but thesurface adsorption of CO2 is enhanced, leading to the maximum oil recovery efficiency. Although the reduction of pore width adversely affects the extraction speed of oil, it is generally favorable for improving final oil recovery. In a double-nanopore system, the exchange between nC10 and CO2presents a counter-current flow pattern. By contrast, in the triple-nanopore systems, nC10 and CO2form their respective dominant migration paths and the large pores dominates the equilibrium time. These observations provide a more in-depth understanding of CO2-enhanced oil recovery (CO2-EOR) mechanisms from the molecular level, and reveal new insights into CO2and oil adsorption and migration behaviors in complex nanopores, thus aiding in the efficient implementation of CO2-EOR project.

Effects of a Forest Carbon Sequestration Project on Grassroots Democracy in China

Effects of a Forest Carbon Sequestration Project on Grassroots Democracy in China

LOW-CARBON INITIATIVES IN THE PULP AND PAPER INDUSTRY AND THE CONTRIBUTIONS TO THE CARBON MARKET IN BRAZIL

Purpose: This paper analyzes the low-carbon initiatives of Brazilian pulp and paper companies, highlighting their relevance to the national carbon market.Methodology/Approach: The adopted method consists of documentary research, using secondary data from sustainability reports and institutional websites of the pulp and paper companies studied. The study analyzed the five largest companies in the sector in Brazil. Findings: The pulp and paper companies analyzed adopt low-carbon practices, such as emission inventory, eco-efficient operations, replacement of fossil fuel-based products, sustainable products, and biomass utilization. In the carbon market, they operate through certifications, carbon sequestration projects, and credit sales.Research, practical & social implications: The study provides a detailed analysis of the decarbonization strategies adopted by companies in the pulp and paper sector, establishing a robust theoretical basis for understanding low-carbon economy practices.Originality/ Value: By demonstrating paths to sustainability, this work offers guidelines for companies within and outside the pulp and paper sector, driving the adoption of more environmentally friendly practices.Keywords: low-carbon economies; carbon-neutral companies; carbon market; net-zero emissions practices.

A Social Dimension of Adaptation and Mitigation of Climate Change: Empowering Local Rural Communities to Confront Extreme Poverty

Climate change impacts occur at varying spatial scales requiring appropriately scaled responses. In impoverished rural areas, adapting to or mitigating the effects of climate change is challenging, with any short-term impairment to precarious livelihoods likely triggering negative community responses even if people are aware of long-term benefits. The paper will discuss a community-based carbon sequestration project in eastern Iran. It started in 2003 and since then has been expanded widely. It was nominated by UNDP as one of 10 transformative projects in Asia/Pacific in 2016. Over the past 20 years, the project has targeted improving the livelihood of the local communities while addressing local measures to adapt to/mitigate climate change. The paper elaborates on the formation of village development groups as pivotal drivers of success by highlighting local income-generating schemes and project documentation. Key lessons for climate change adaptation can be learnt and are applicable to other developing countries. Extreme poverty in rural areas facing climate change could be tackled through implementing bottom-up approaches in which local communities can be respected and engaged in co-leadership and planning.

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

To address the challenges of climate change, significantly more geologic carbon sequestration projects are beginning. The characterization of the subsurface and the migration of the plume of supercritical carbon dioxide are two elements of carbon sequestration that can be addressed through the use of the available seismic methods in the oil and gas industry. In an enhanced oil recovery site in Farnsworth, TX, we employed three separate seismic techniques. The three-dimensional (3D) surface seismic survey required significant planning, design, and processing, but produces both a better understanding of the subsurface structure and a three-dimensional velocity model, which is essential for the second technique, a timelapse vertical seismic profile, and the third technique, cross-well seismic tomography. The timelapse 3D Vertical Seismic Profile (3D VSP) revealed both significant changes in the reservoir between the second and third surveys and geo-bodies that may represent the extent of the underground carbon dioxide. The asymmetry of the primary geo-body may indicate the preferential migration of the carbon dioxide. The third technique, cross-well seismic tomography, suggested a strong correlation between the well logs and the tomographic velocities, but did not observe changes in the injection interval.

Field assessment of elastic full-waveform inversion of combined accelerometer and distributed acoustic sensing data in a vertical seismic profile configuration

Seismic data are a significant facilitator for monitoring in carbon capture and sequestration projects, providing high-resolution images of fluid migration, using, for example, full-waveform inversion (FWI). Distributed acoustic sensing (DAS), a relatively novel technology for wavefield sampling, is well suited for this type of monitoring. Using noninvasive optical fibers, DAS allows for dense spatial sampling along the entire length of the wellbore, without disrupting operations. Permanently installed in the wellbore, typically behind casing, DAS offers highly repeatable and dense sampling of the transmitted wave modes crucial to seismic monitoring of injected carbon dioxide ([Formula: see text]). However, the DAS data consist of measurements of strain along the tangent of the fiber and therefore do not transfer directly to conventional FWI algorithms. Incorporation of DAS data in their native strain (or strain-rate) form in standard FWI algorithms, requires changing the definition of the receiver sampling operator to use geometric information about the fiber to supply tangential strain measurements to the FWI residual. The theoretical developments are applied to invert field vertical seismic profile data acquired with DAS fiber and accelerometers at a [Formula: see text] sequestration site in Newell Country, Alberta. Our method incorporates DAS data and accelerometer data in one objective function and allows us to tune the relative importance we wish to place on each data set. This method also transfers to noncollocated sensors, for example, surface-deployed geophones and borehole fiber. The inverted models contain features expected from the geology of the field site, and data modeled in the inverted models compare favorably with the field data for these sensor types. The models are derived from data acquired prior to [Formula: see text] injection, representing baseline models for future time-lapse studies planned at the field research station.

Valuing the functionality of tropical ecosystems beyond carbon

Land-based carbon sequestration projects, such as tree planting, are a prominent strategy to offset carbon emissions. However, we risk reducing natural ecosystems to one metric – carbon. Emphasis on restoring ecosystems to balance ecosystem services, biodiversity conservation, and carbon sequestration is a more appropriate strategy to protect their functioning.

Time-Lapse Pulsed-Neutron Logs for Carbon Capture and Sequestration: Practical Learnings and Key Insights

Pulsed-neutron logs are a staple of time-lapse monitoring programs for saline aquifer carbon capture and sequestration (CCS) projects and are unsurprisingly the most frequently run wireline logs in both injection and monitoring wells. While the emphasis imposed by government regulators and the focus of operators to date has been on the verification of CO2 containment, it is envisioned that a savvy interpretation of the multiple independent measurements should be able to unlock much greater value for the project than merely detecting the location of stored CO2. Recently introduced capabilities for novel measurements and improved environmental compensation should further increase the repeatability, interpretability, and value of these logs. We reviewed more than 30 time-lapse runs of pulsed-neutron logs acquired over a period of 15 years on three mature CCS projects using both previous- and new-generation pulsed-neutron tools, including measurements of formation sigma, hydrogen index, and fast neutron cross section. Special attention in processing is required when changes occur to the wellbore environment between runs, although this is mitigated by the improved environmental compensation scheme of the newer tool. We performed both standalone estimates of CO2 saturation from single-physics time-lapse measurements and simultaneous interpretation of multiple independent time-lapse measurements and studied the results side-by-side with openhole log interpretation, core analysis, and well test results from the evaluation phase. The apparent changes in saturation were framed within the context of the injection history and important events in the life of the wells. A first finding is that differences in apparent CO2 saturation between the various independent measurement physics of the pulsed-neutron tool are often reconcilable and may carry additional information about the state of the well or reservoir. With respect to verification of containment, depending on the well configuration, it may be possible to differentiate between CO2 in the formation and CO2 in the annulus. The interpreted CO2 saturation itself can have different significance depending on the timing of acquisition and the type of well. Measured at the right time, it is a direct in-situ measurement of formation CO2 storage efficiency. In other cases, the interpretation reveals formation dryout in the near-wellbore region of injection wells, a condition that may presage loss of injectivity. We now understand that it is important for operators to plan the timing and frequency of pulsed-neutron runs according to what they want to measure and not based solely on regulatory obligations. In a CCS project, time-lapse pulsed-neutron logs should be thought of as much more than simple indicators of the presence and migration of CO2. They give important information about migration pathways. They can also help to quantify essential uncertainties on reservoir performance that are difficult to ascertain during evaluation. For example, storage efficiency is difficult to quantify with openhole logs since the formation is initially at zero CO2 saturation. Yet it is one of the keys to determining the ultimate storage capacity of any reservoir. Time-lapse pulsed-neutron logs provide an abundance of information that, when properly history matched, can greatly improve our models of CCS reservoirs to better navigate both the economic and operational risks associated with these projects.

Integrated Formation Evaluation for Site-Specific Evaluation, Optimization, and Permitting of Carbon Storage Projects

Participation in over 80 carbon capture and sequestration (CCS) projects spanning 25 years has led to the evolution of a recommended well-based appraisal workflow for CO2 sequestration in saline aquifers. Interpretation methods are expressly adapted for CCS applications to resolve key reservoir parameters, constrain field-scale modeling, provide answers required for the permitting process, and de-risk unique CCS evaluation challenges, such as Storage capacity Injectivity Containment. A challenge complicating all of the above is the eventual impact of three-way interaction among rock matrix, brine, and (impure) CO2 streams. Most logging, sampling, and laboratory techniques are adapted from established domains such as enhanced oil recovery, underground gas storage, and unconventional reservoir evaluation, though some CCS-specific innovation is also needed. Storage evaluation begins with established methods for lithology, porosity, permeability, and pressure, while special core analysis (SCAL) determines CO2 storage efficiency and relative permeability. Containment evaluation spans multiple disciplines and methods: the petrophysicist’s task to quantify seal capacity relies heavily on laboratory analysis, while geologists leverage downhole imaging tools to verify caprock structural/tectonic integrity. Geomechanics engineers define safe injection pressure via mechanical earth models (MEMs) built on advanced acoustic logs calibrated by core geomechanics, wellbore failure observations, and in-situ stress tests. The impact of rock-brine-CO2 interactions is studied via custom SCAL experiments and/or pore-scale digital rock simulations that rigorously represent chemical and thermal processes. Wireline formation tester samples provide representative formation brine as feedstock for SCAL. Water samples also enable operators to prove injection within regulatory limits while establishing baselines for future monitoring programs. Examples applied to recent CCS projects in North America are presented. All of the above data need to be integrated into a CCS model predicting the CO2 plume behavior across the area of interest and within multiple horizons.

Accessible satellite data decision support systems for Yurok Tribe forest management

Local decisionmakers managing forests for sequestering carbon and mitigating disturbance face increasing pressures from climate change, while needing to derive revenue from forests resources and balance diverse stakeholder concerns. Decision support systems (DSS) that use freely available satellite data are effective tools for forest management decision-making, due to the broad spatial coverage and temporal consistency of this data. However, the literature demonstrates that many DSS developed by researchers incorporating satellite data are often not utilized by decision makers. This is in part due to a lack of stakeholder engagement in DSS development. Here, we employ an intentional stakeholder engagement process to develop an accessible DSS incorporating satellite data. This process is applied with the Yurok Tribe – an Indigenous community in California – towards the goal of managing forests for carbon sequestration. We use system architecture framework (SAF) to translate stakeholder objectives into targeted analyses and the environment-vulnerability-decision-technology (EVDT) integrated modeling framework to incorporate contextual local infrastructure and land ownership information alongside satellite data analyses. Satellite data analyses classify tree cover and track Normalized Difference Vegetation Index (NDVI) over time. We compare and show that trends in our analysis agree with independent global tree cover and biomass datasets. These analyses meet the Tribe's objective for tracking forest trends in Yurok carbon sequestration projects, while also detecting undesirable conifer encroachment on culturally-important prairies traditionally managed as open landscapes. Additionally, integration of community infrastructure data alongside satellite-derived drought, forest fire, and smoke density information via EVDT meets another Yurok Tribe objective of identifying negatively impacted Tribal areas for aid allocation. User feedback sessions with participating Yurok Tribe employees assess the prototype DSS and show 80% of users providing high ratings (≥75%) for information accuracy, relevancy, and sufficiency, demonstrating that our DSS development process overcomes previous gaps to DSS use and satellite data accessibility to augment Yurok Tribe forest management decision making.

SegForest: A Segmentation Model for Remote Sensing Images

The accurate estimation of forest area is of paramount importance for carbon sequestration projects, ecotourism and ecological safety. Forest segmentation using remote sensing images is a crucial technique for estimating forest area. However, due to the complex features, such as the size, shape and color of forest plots, traditional segmentation algorithms struggle to achieve accurate segmentation. Therefore, this study proposes a remote sensing image forest segmentation model named SegForest. To enhance the model, we introduce three new modules: multi-feature fusion (MFF), multi-scale multi-decoder (MSMD) and weight-based cross entropy loss function (WBCE) in the decoder. In addition, we propose two new forest remote sensing image segmentation binary datasets: DeepGlobe-Forest and Loveda-Forest. SegForest is compared with multiple advanced segmentation algorithms on these two datasets. On the DeepGlobe-Forest dataset, SegForest achieves a mean intersection over union (mIoU) of 83.39% and a mean accuracy (mAcc) of 91.00%. On the Loveda-Forest dataset, SegForest achieves a mIoU of 73.71% and a mAcc of 85.06%. These metrics outperform other algorithms in the comparative experiments. The experimental results of this paper demonstrate that by incorporating the three proposed modules, the SegForest model has strong performance and generalization ability in forest remote sensing image segmentation tasks.

Decoupling Analysis of Carbon Emissions and Forest Area in China from 2004 to 2020

As the largest ecological carbon sequestration systems on the Earth, forests play a significant role in reducing carbon dioxide, and countries around the world are actively expanding their forest areas. However, China’s carbon emissions and forest area have shown an upward trend, which has seriously hindered the implementation of forestry carbon sequestration projects. This paper analyzed the temporal variation, spatial distribution, and deviation degree of the forest area and carbon emissions in China from 2004 to 2020 by using a decoupling model and a coordination model. Firstly, according to the decoupling model, the national carbon emissions and forest area are negatively decoupled. At the provincial level, Beijing, Shanghai, Jiangsu, Guizhou, Yunnan, and Gansu have weak decoupling. Expansive link areas include Shanxi, Henan, Hubei, Ningxia, and Xinjiang. The other 19 provinces show expansive negative decoupling. Secondly, according to the coordination model, national carbon emissions are coordinated to the forest area. Zhejiang, Fujian, Jiangxi, and Guangdong are basically coordinated provinces. More coordinated provinces include Ningxia. The other 25 provinces are coordinated provinces. Finally, according to the comprehensive measurement model, Inner Mongolia, Qinghai, Shaanxi, Hainan, Jilin, Anhui, Liaoning, and Heilongjiang are high-quality expansive negative decoupling provinces. Chongqing, Hunan, Tianjin, Shandong, Hebei, and Guangxi are moderate to strong expansive negative decoupling provinces. This study not only provides a new perspective for analyzing forest carbon sinks, but also provides theoretical guidance for enhancing the natural carbon sink capacity, helping to achieve global carbon peak and carbon neutrality goals.

Towards a co‐crediting system for carbon and biodiversity

Societal Impact StatementHumankind is facing both climate and biodiversity crises. This article proposes the foundations of a scheme that offers tradable credits for combined aboveground and soil carbon and biodiversity. Multidiversity—as estimated based on high‐throughput molecular identification of soil meiofauna, fungi, bacteria, protists, plants and other organisms shedding DNA into soil, complemented by acoustic and video analyses of aboveground macrobiota—offers a cost‐effective method that captures much of the terrestrial biodiversity. Such a voluntary crediting system would increase the quality of carbon projects and contribute funding for delivering the Kunming‐Montreal Global Biodiversity Framework.SummaryCarbon crediting and land offsets for biodiversity protection have been developed to tackle the challenges of increasing greenhouse gas emissions and the loss of global biodiversity. Unfortunately, these two mechanisms are not optimal when considered separately. Focusing solely on carbon capture—the primary goal of most carbon‐focused crediting and offsetting commitments—often results in the establishment of non‐native, fast‐growing monocultures that negatively affect biodiversity and soil‐related ecosystem services. Soil contributes a vast proportion of global biodiversity and contains traces of aboveground organisms. Here, we outline a carbon and biodiversity co‐crediting scheme based on the multi‐kingdom molecular and carbon analyses of soil samples, along with remote sensing estimation of aboveground carbon as well as video and acoustic analyses‐based monitoring of aboveground macroorganisms. Combined, such a co‐crediting scheme could help halt biodiversity loss by incentivising industry and governments to account for biodiversity in carbon sequestration projects more rigorously, explicitly and equitably than they currently do. In most cases, this would help prioritise protection before restoration and help promote more socially and environmentally sustainable land stewardship towards a ‘nature positive’ future.

Economic and operational investigation of CO2 sequestration through enhanced oil recovery in unconventional reservoirs in Colorado, USA

The ongoing CCUS commercial projects are highly relied on the support of government incentives due to massive capital investment. This study analyzes the economics of carbon capture utilization and sequestration (CCUS) projects, shows a state-wide CCUS deployment exercise, followed by simulation results of enhanced oil recovery (EOR) based CO2 storage in unconventional reservoirs. The comprehensive economic analysis of capture, transportation, sequestration costs, enhanced 45Q tax credits, and EOR revenue implies the practicality of CO2-EOR to offset the high CCUS costs. With the economics understanding, we study the top CO2 sources, existing CO2 pipelines, and sequestration sinks in the state of Colorado, USA. This paper next presents results from EOR simulation in one section of the unconventional Denver-Julesburg (DJ) Basin Niobrara and Codell reservoirs. The simulation model is based on a geological static model, incorporated with hydraulic fracture stimulation, history matched to production, and calibrated to the microseismic and time-lapse surface seismic data. The CO2-EOR simulation results show that oil production can be increased and more CO2 stored with: a longer primary production period; the presence of a shut-in period; higher injection rates; and multi-well injectors. The modeling results show that about 7–10 Mscf of CO2 will be stored when recovering 1 stb of EOR oil. By adding the enhanced oil revenue and the carbon credits together, it is estimated that the most economic case can generate $13 MM when oil price is assumed to be $80/stb, and the EOR oil revenue is 3.4 times greater than that generated from 45Q incentives. It corresponds to the scenario that a five-year primary production is followed by CO2 injection into four wells with the sequence of injection (4 MMscf/day for 6 months), shut-in (6 months) and production (12 months). The best practices in this study will provide valuable insights for similar CCUS projects in other unconventional fields. Furthermore, this study defines a term named “Carbon Neutrality Index (CNI)” by comparing the amount of CO2 stored with that burned by EOR oil. The CNI value of 0 indicates the enhanced oil is carbon neutral; a negative CNI value implies there is a net reduction in carbon emission. The 4-year huff-n-puff (HnP) simulation leads to a positive CNI value, indicating that the EOR oil generated in this process is not carbon neutral yet.

Optimal harvest decisions for the management of carbon sequestration forests under price uncertainty and risk preferences

Forestry carbon sequestration represents a critical way to achieve the goal of mitigating climate change and carbon neutrality in China. However, fluctuations in timber and carbon prices pose greater risks for forest farmers in their management decisions. Thus, risk preferences play an important role in forestry production decisions. This study develops a dynamic Faustmann model to evaluate the impact of market uncertainty and risk preferences for the harvesting decisions on Chinese fir plantations in southeastern China. The model is solved by employing a dynamic programming algorithm with the Monte Carlo simulation method. Specifically, we use a linearization function to describe the land expectation value of the future rotation period, simplifying the model's solution. The regression results of the linearized function are significant and can fully represent the future land expectation value of different optimal risk tolerance levels with different discount rates and timber and carbon prices. The results indicate that risk-seeking forest farmers generate more revenue than risk-aversers to maximize the land expectation value. The results of the dynamic Faustmann model generally show a shorter optimal rotation period and a higher land expectation value when compared with the static Faustmann model. Sensitivity analysis shows that timber price is a key parameter affecting the management decisions on the carbon sequestration forests, and forest farmers can obtain additional revenue from the increased timber price volatility. In contrast, the impact of carbon price fluctuations is relatively small, but higher carbon price can help forest farmers generate more revenue from the projects. Our results demonstrate that the Chinese government should improve the long-term equilibrium level of the carbon price, which fully reflects the carbon sequestration benefits of forest stands, and motivates forest farmers to participate in carbon sequestration projects. In addition, advising forest farmers to select the appropriate rotation period for forest carbon projects based on their risk preferences enables them to maximize the benefits of carbon sequestration and timber harvesting.

The impact of carbon market on city greening: Quasi-experimental evidence from China

This paper investigates the regional spillover effects of the project-based voluntary market under the carbon emissions trading scheme (ETS). By exploiting one local offset mechanism (China's PHCER) as a quasi-experiment, we detect the unintended causal effect of the carbon market on greening the city. Using the difference-in-differences (DiD) estimator, we find that the voluntary carbon market resulted in a 14.45% (14.34%) increase in city-year-level NDVI summary value (per capita). The primary mechanism is the expansion of forest carbon sequestration projects. Cities with lower carbon emissions and fewer carbon market participants experience a greater causal effect. More importantly, we find no evidence to support the crowding out of arable land by forest carbon sequestration projects. Finally, several policy implications for a more functional carbon market are discussed.

Estimating Sustainable Long-Term Fluid Disposal Rates in the Alberta Basin

Reliable regional-scale permeability data and minimum sustained injectivity rate estimates are key parameters required to mitigate economic risk in the site selection, design, and development of commercial-scale carbon sequestration projects, but are seldom available. We used extensive publicly available disposal well data from over 4000 disposal wells to assess and history-match regional permeability estimates and provide the frequency distribution for disposal well injection rates in each of 66 disposal formations in the Alberta Basin. We then used core data and laboratory analyses from over 3000 cores to construct 3D geological, geomechanical and petrophysical models for 22 of these disposal formations. We subsequently used these models and the history-matched regional permeability estimates to conduct coupled geomechanical and reservoir simulation modeling (using the ResFrac™, Palo Alto, CA, USA, numerical simulator) to assess: (i) well performance in each formation when injecting carbon dioxide for a 20-year period; (ii) carbon dioxide saturation and reservoir response at the end of the 20-year injection period; (iii) reliability of our simulated rates compared to an actual commercial sequestration project. We found that: (i) the injection rate from our simulations closely matched actual performance of the commercial case; (ii) only 7 of the 22 disposal formations analyzed appeared capable of supporting carbon dioxide injectors operating at greater than 200,000 tons per year/well; (iii) three of these formations could support injectors operating at rates comparable to the successful commercial-scale case; (iv) carbon dioxide presence and a formation pressure increase of at least 25% above pre-injection pressure can be expected at the boundaries of the (12 km × 12 km) model domain at the end of 20 years of injection.

Integration of Clustering System and Joint Venture Business Model for CCUS Deployment:

Carbon Capture, Utilization, and Storage (CCUS) have been a 'buzzword' for the past two years, especially in Indonesia, a developing country committed to achieving net-zero emissions. However, 43% of global CCUS projects were still terminated or put on hold, mainly driven by economic inability and public acceptance. Therefore, a suitable business model and clustering system must be proposed to make carbon sequestration projects economically attractive in Indonesia. Under the Analytical Hierarchy Process (AHP) assessment collaborating with the previous study conducted by Center of Excellence ITB and Lemigas, clustering systems can be deployed in three regions: South Sumatra, West Java, and East Kalimantan. The selected CO2 sources consist of various industrial sectors surrounding the fields, aiming to facilitate the source's matching process to the possible sink. Thus, it is obtained that the Talang Jimar field (South Sumatra) becomes the highest priority and the most probable sink point with 0.584 GtCO2 storage and an annual sink capacity of 0.0292 GtCO2 for 20 years storage period. Integrating CCUS deployment in Talang Jimar with a clustering system and advanced capturing technology seriously adds commercial value to the project. A carbonate fuel cell is the proposed capturing technology for coal power plants, with expected CO2 capture efficiency by 90% and reduced electricity cost by 33%. These developing technologies and clustering systems are forcing companies to find more efficient business models to compete in the carbon market. In this study, a joint venture scheme is applied to specify the CO2 value chain in this project and to cover the capturing and transportation cost through the joint-stock cooperative system, under sharing percentage assumptions of 40% for the capturing company, 30% for storage, and 30% for transport.