GCEP-funded SCCS Project Report Investigators Anthony R. Kovscek, Professor, Energy Resources Engineering Sally M. Benson, Professor, Energy Resources Engineering Adam R. Brandt, Professor, Energy Resources Engineering Mohammad S. Masnadi, Research Scientist, Energy Resources Engineering D. Chester Upham, Post Doctoral Scholar, Energy Resources Engineering Youssef Elkady, Graduate Student, Energy Resources Engineering Gregory A. Von Wald, Graduate Student, Energy Resources Engineering Gege Wen, Graduate Student, Energy Resources Engineering Gurinder Nagra, Graduate Student, Energy Resources Engineering Meng Tang, Graduate Student, Energy Resources Engineering Introduction The Stanford Center for Carbon Storage (SCCS) investigates questions related to enhanced recovery of oil and gas combined with CO2 storage, the development of monitoring technologies for all classes of geological storage, the characterization of both near-well and distal geochemical processes during CO2 injection, and computational optimization of the design and operation of large projects. SCCS is a multidisciplinary research program within the School of Earth, Energy & Environmental Sciences at Stanford University. SCCS supports research activities across the Departments of Energy Resources Engineering, Geophysics, and Geological Sciences within the School of Earth, Energy & Environmental Sciences. We are a research group comprised of 13 faculty members and about 16 graduate students and researchers involved directly or indirectly with SCCS funds. We are funded by GCEP, as well as other industrial sponsors. In the attached report, we provide a summary of 5 projects directly funded by GCEP. Project 1: CO2 plume migration and dissolution in layered reservoirs, Gege Wen and Sally M. Benson. Project 2: Predicting CO2 Plume Migration using Deep Neural Networks, Gege Wen, Meng Tang, and Sally M. Benson. Project 3: Investigation of CO2 EOR in Carbonate-Rich Shales, Youssef Elkady and Anthony Kovscek. Project 4: 1Mt/yr of CO2 in Basalt Reservoirs - is it viable? Gurinder Nagra and Sally M. Benson. Project 5: Molten-media methane pyrolysis for solid carbon capture, utilization, and sequestration, Gregory A. Von Wald, Mohammad S. Masnadi, D. Chester Upham and Adam R. Brandt.

Project 1: CO2 plume migration and dissolution in layered reservoirs Abstract

In carbon capture and storage (CCS) projects, the presence of layered permeability heterogeneity can strongly affect the migration of the supercritical CO2 plume and CO2 dissolution. By conducting a systematic study of plume migration in layered reservoirs with a wide range of permeability contrast between the layers, we show that the relationship between CO2 plume footprint and permeability contrast has three distinct regimes. Overall, the footprint of the plume can vary by more than 2-fold, with large implications for monitoring, access to sites, and regulatory issues. The mass fraction of CO2 dissolution can vary up to 2-fold depending on the degree of heterogeneity. We also show that the common practice of using permeability anisotropy to simulate multiphase flows in layered reservoirs works quite well in terms of plume footprint for permeability anisotropy ratios of up to 25, but large errors occur at more extreme contrasts.

Introduction Sedimentary formations being used for storage often contain layered permeability

heterogeneity that strongly affects the movement of injected CO2 and the plume footprint. Low permeability intra-reservoir shale layers baffle the vertical migration of CO2 and typically result in larger plume volume and lower gas saturation. At the same time, dissolution trapping and residual trapping are enhanced because a larger volume of brine and rock interacts with free phase CO2. In this project, we systematically investigate the influence of purely layered and continuous intra-reservoir shales on plume footprint and CO2 dissolution, including the effect of grid resolution. We also assess the degree to which and under what circumstances models using anisotropic permeability can be used to predict CO2 plume migration and dissolution reliably.

Background The footprint of a plume, defined as the maximum lateral extent of separate phase CO2,

is an important parameter used throughout the regulatory process of planning, operating, monitoring, and site closure. During site screening, estimation of CO2 plume footprint is essential for identifying pore space ownership issues and potential acquisition of storage leases. In risk assessment, the simulated plume footprint is used to help identify potential well infrastructures, faults, or fractures in the area that may provide leakage pathways. Consequently, the ability to model plume migration accurately is a prerequisite for implementing CO2 storage projects.

For reservoirs with layered continuous heterogeneity, it is a common practice to use the arithmetic average as the effective horizontal permeability and the harmonic average as the effective vertical permeability. However, it can be problematic to plume migration modeling by missing the influence of by thin heterogeneous layers. This phenomenon is known as the thief zone issue in oil and gas production as well as for CO2-EOR reservoirs. In this project, we compared homogeneous anisotropic models with models that explicitly account for heterogeneity.

Results Relationship among plume migration, dissolution, and contrast ratio

The plume radius is highly sensitive to heterogeneity in the reservoir, varying by up to a factor of 2 for a range of realistic scenarios. The sensitivity of plume radius to contrast ratio falls into 3 distinct regimes: for contrast ratios smaller than 5, the plume radius is largest and nearly constant; as contrast ratio increases from 5 to 50, plume radii are highly sensitive to contrast ratio and decrease rapidly; at contrast ratios greater than 50 plume radius becomes nearly constant, but is about 40% smaller than for homogeneous reservoirs. This effect is explained by the role that low permeability (high capillary pressure) layers play in counteracting gravity forces that drive upward migration of the plume.

Dissolution of CO2 during the injection phase also depends strongly on the permeability contrast ratio, reaching a maximum of nearly 25% at a contrast ratio of about 50. For homogeneous reservoirs or those with small permeability contrasts, dissolution is about 50% lower. For high contrast ratios, the amount of dissolution is between these two extremes. We show that dissolution correlates with plume volume, and the largest plume volumes correspond to permeability contrast ratios between 50 and 100.

Figure 1: Plume radius vs. permeability contrast and mass fraction of dissolved CO2 vs. contrast ratio.

Modeling with anisotropic permeability averages

Results in Figure 2 indicate that anisotropic permeability values can provide relatively accurate plume radius prediction for layered heterogeneity for contrast ratios of less than 100 (corresponding to permeability anisotropy of less than 26), where the errors are up to 11% in our base case. For higher contrast ratios, anisotropic models underestimate the plume radius by large amounts because they do not account of the fact that the capillary entry pressure of the low permeability layers prevents CO2 from entering them.

Figure 2: (a) Comparison of plume radius vs. contrast ratio between heterogeneous and anisotropic systems, numbers on data points represents the anisotropy ratio (b) Comparison of mass fraction of dissolved CO2 vs. contrast ratio between heterogeneous and anisotropic systems, numbers on data points represents the anisotropy ratio

Conclusions

The results in this work has implications for both practical issues such as site selection and approaches for obtaining accurate information about plume migration. With regard to site selection, this work shows that moderate to high degrees of permeability heterogeneity is advantageous insofar as it reduces the plume footprint, keeps the bulk of the plume deeper in the reservoir and away from the seal, and leads to higher dissolution rates. This work also demonstrates the need for high resolution simulations to model plume migration accurately. For modest levels of heterogeneity (< 25), anisotropic simulations can provide reliable estimates of plume radius, but for higher degrees of anisotropy, which are not unusual, alternative approaches are needed that capture the capillary behavior of heterogeneous systems.

Publications and Presentations Publications

1. Wen, Gege, and Sally M. Benson. "CO2 plume migration and dissolution in layered reservoirs." International Journal of Greenhouse Gas Control 87 (2019): 66-79. https://doi.org/10.1016/j.ijggc.2019.05.012

Presentations

1. SCCS Autumn Seminar: CO2 Plume Migration and Dissolution in Layered Reservoirs. Stanford University, Nov 2018

Contacts Gege Wen: gegewen@stanford.ede Sally M. Benson: smbenson@stanford.edu

Project 2: Predicting CO2 Plume Migration using Deep Neural Networks

Abstract

Numerical simulation of CO2 plume migration in the subsurface is a prerequisite to effective CCS projects. However, stochastic high spatial resolution simulations are currently limited by computational resources. In this project, we propose a deep neural network approach to predict the CO2 plume migration in high dimensional systems with complex geology. Upon training, the network is able to give accurate predictions that are 6 orders of magnitude faster than traditional numerical simulators. This approach can be adopted to history-matching and uncertainty analysis problems to support the scale-up of CCS deployment.

Introduction In this project, we demonstrate a neural network which can make fast predictions on

CO2 plume migration given permeability field and injection information. With adequate training, the network achieves high accuracy in a 16,384-dimensional system where viscous, capillary, and gravity forces all play an important role. This network also deals with complex and discontinuous geological heterogeneities.

Background Currently, people use numerical simulation approaches (e.g. Tough2, ECLIPSE) which

solve the relevant mass and energy balances using a set of spatially and temporally discretized nonlinear partial differential equations. However, this process is often computationally intractable due to the heterogeneity of geological formations, large spatial domains, and the long timeframe of CO2 storage projects. The problem is confounded by the inherent uncertainty associated with the subsurface geology. Uncertainty analysis with stochastic simulations can be used to obtain probabilistic estimates of plume migration. However, stochastic simulations are limited by computational resources. Meanwhile, the model calibration process requires history-matching simulation models with monitoring data in an iterative fashion, which also requires huge computational resources. In practice, approximation approaches such as upscaling or reduced physics modeling have been heuristically developed to aid decision making.

Results The results in Figure 1 demonstrate the network's ability to make accurate predictions

in highly stochastic formations (first row), channelized formations (second row), and layered formations (third row). The trained network estimates the saturation of CO2 according to the injection duration and location while capturing the interplay of viscous, capillary, and gravity forces. The mean absolute error on the validation set is around 0.0015, which is considered negligible in the context of plume migration. Each prediction by the neural network takes 0.003 seconds, which is about 6 orders of magnitude faster than traditional simulators.

Figure 1: Validation set result by the neural network which is trained by 40,000 training samples. Conclusions In this project, we provide a demonstration using a neural network approach to conduct fast and accurate prediction of CO2 plume migration given permeability field and injection information. Our network can accurately predict the CO2 plume migration in complex systems with highly heterogeneous subsurface geology. To show the potential of this approach, we plan to conduct case studies to test the ability of this network in real world settings. Publications and Presentations Presentations

1. ICML 2019 workshop “Climate Change: How Can AI Help?” Long beach CA, Jun 2019 (to do)

Contacts Gege Wen: gegewen@stanford.edu Meng Tang: mengtang@stanford.edu Sally M. Benson: smbenson@stanford.edu

Project 3: Investigation of CO2 EOR in Carbonate-Rich Shales Abstract An experimental workflow is established to test CO2 EOR in carbonate-rich shale. An experimental workflow utilizing Computed Tomography (CT) and image processing was established to quantify CO2 EOR potential in carbonate-rich shale. Single nano-Darcy permeability cores are inadequate for experimental testing as rock matrix does not contribute to flow. The observations made in this work have led us to consider samples with larger carbonate content and higher permeability. Introduction The shale gas and oil boom has been the largest leap in the oil and gas industry since 2009. The world's estimated natural gas from unconventional resources is 22,000 TCF (EIA ,2014). Only 20-30% are deemed recoverable (McgGlade and Sorrell, 2013). The U.S. Energy Information Administration (EIA) estimated that about 4.25 MMBOE had been produced directly from tight reservoirs, accounting for 48% of total U.S. production at ultimate recoveries ranging from 5% to 10%. The knowhow of hydraulic fracturing and horizontal drilling carved tremendous advancements in these resources. Unfortunately, the technology is by no means efficient. The propped portion of the primary hydraulic fracture is limited by the fracture aperture reduction away from the well and the center of the fracture plane, and the suspension ability of the gelling agent. The secondary or micro-fractures that are stimulated in shear through fluid leak off, on the other hand, will not be accessed by proppant as their aperture size is 0.1 microns at best, which would not permeate a 40-mesh sand (Wu and Sharma, 2015). Also, most slippage is caused by the long distance pressure perturbations, that cause the frictional strength of the rock to be exceeded, and not necessarily by direct contact with the fluid. As a result, unpropped fractures are more likely to reduce in aperture with increasing closure stress and production. CO2 enhanced oil recovery (EOR) has been advocated in the literature for unconventional oils due to its low miscibility pressure, eliminating the need of very high entry pressures in nano-pores. Other crucial benefits include: reducing oil viscosity, reservoir re-pressurization, support to carbon storage initiatives, and its reactive nature in the presence of water. U.S. CO2 miscible flooding has produced roughly 300 MBOE in 2014, which is on par with all thermal EOR production in the U.S. that year, emphasizing the tremendous potential of CO2 injection. Although there is extensive use of CO2 in the EOR community due to its effectiveness in conventional reservoirs, there is very limited foundational laboratory work to support it in micro-Darcy formations and even less in nano-Darcy shales. This trend is only natural as shale formations are extremely tight and saturating nano-Darcy cores with light crude oil for testing is non-trivial and very time consuming. Recent numerical and experimental work in the literature has focused on milli-Darcy to micro-Darcy permeability rock with porosity ranging from 4-8% ((Shoaib and Hoffman, 2009), (Mohanty and Balhoff, 2013), and (Alharthy and Kurtoglu, 2015)) with the exception of Vega and Kovscek (2010) using siliceous shale with porosity of

34%. In this paper, we present our findings regarding CO2 recovery in single-digit nano-Darcy permeability carbonate-rich shale. Background In our investigation, we selected a moderately carbonate-rich shale sample shown in Fig. 1. The core sample is 3" in length and 1.5" in diameter with total carbonate composition of approximately 13%. Table 1 summarizes sample W2-2 mineralogical composition. After the sample was vacuumed, we conducted a pulse-decay experiment on the intact core. The permeability of the intact core was computed; however, the porosity value was indeterminable due to its very low permeability. The core was then cut in half with a rock saw to increase surface area and the pulse-decay experiment was repeated to obtain matrix and fracture porosity values. The pulse-decay experiment schematic is shown in Fig. 2.

Figure 1: W2_2 carbonate-rich 3”L x 1.5”D shale sample.

Table 1: W2_2 mineralogical data.

Minerals Percentage

Quartz 23

Plagioclase 5 Calcite 10

Ankerite/Excess Ca. Dolomite 3 Pyrite 2 Clay 56

Organic Matter 1

Figure 2: Pulse-Decay schematic. V1, V2, and Vf refer to the upstream, downstream and final volumes, respectively, used in porosity calculations. The positions of V1 and V2 changes slightly for permeability computations.

Once W2-2 permeability and porosity were measured, the core was vacuumed to remove the in-situ helium gas. The core was then saturated with supercritical CO2 (Sc-CO2) at 1400 psi for 5 days. Oil was then injected with a back-pressure regulator set at 2000 psi for another 5 days. The oil injection pressure was chosen based on a previous miscibility pressure experiment and WinProp simulation results. Figures 3 and 4 summarize that miscibility between our crude and Sc-CO2 at 72 °C is achieved at 1870 psi. Experimental miscibility is obtained by increasing pressure in a confined cell filled initially with 80% crude oil. Pressure is increased by injecting more Sc- CO2 into the cell. The CT number is recorded for every pressure step and plotted as shown in Fig. 3. The data is fitted using a power law model (n=2.2) and then extrapolated to CT number difference of 0, which represents the miscibility pressure. The experimental value was validated by simulating a mixing-cell experiment in CMG© WinProp considering a 10 pseudo-component system to represent our oil as shown in Fig. 4. Figure 4, also includes results for live oil and different methane compositions in injection gas. These additional tests were to corroborate the simulation results with what we expect.

Figure 3: CT number difference between vapor and liquid phases vs pressure. Miscibility estimated using power law extrapolation.

Figure 4: WinProp CMG validation of miscibility experiment. Miscibility pressure increases with increasing methane content in injection gas.

The core was left for 3 months to allow sufficient time for the oil to permeate from the fractures into the matrix. Finally, the core was sequentially injected with Sc-CO2 at 1400 psi, Sc-CO2 above miscibility (1900 psi), water-saturated Sc-CO2 vapor at 1400 psi, and CO2 saturated liquid water at 1400 psi, to assess oil recovery. Figure 5 shows a schematic of the experimental setup. A heated rocking cylinder is used in the case of

water-saturated Sc-CO2 vapor and CO2 saturated liquid water injections as the CO2 and DI water need mixing prior to injection.

Figure 5: EOR experimental schematic. An additional rocking cylinder added in the case of two-component single phase injections for mixing. Rocking cylinder, accumulator and core holder heated to 72 °C. Results The permeability of core W2-2 is estimated to be as low as 10nD. This permeability is in the same order of magnitude as cores from the same depth. As mentioned earlier, due to the very low permeability and the slow permeation of helium into the matrix, a porosity value was hard to obtain from the intact rock. Therefore, the core was cut axially in half and re-tested. Figure 6 depicts the fractured core utilizing Computed Tomography (CT). The decay curves recorded from a fractured core holds information regarding the fracture porosity as well as the matrix permeability and porosity. The helium pulse-decay fracture and matrix porosity are 3.3% and 7.3%, respectively, totaling to 10.6%.

Figure 6: Dry CT image of fractured W2-2 core. Based on QXRD data (13% carbonate content) and the relatively high density of carbonates, one can conclude that green in the figure above captures W2_2 carbonate clusters.

After saturating W2-2 with oil, only the fracture was filled with crude oil. Figure 7 shows a 3D CT image reconstruction of the oil saturated core using an exponential color scale. After aging the core for 3 months at reservoir temperature and 2000psi dry CO2 was injected at 1400psi and incremental recovery was computed after subtracting dead volume. The 3D CT images before and after CO2 injection showed that almost all fluid flow is occurring in the fracture with negligible movement in the matrix (Fig. 8). After 21.8 pore volume injected (PVI) the oil recovery was 0.78. Subsequently, we injected CO2 at 1900psi a pressure above the miscibility pressure, for another 6 PVI followed by 9.6 PVI of wet CO2 injection. Finally, 7.3 PVI of CO2 saturated water was injected.

Figure 7: 3D CT image of oil residing in the main fracture of W2-2 core with exponential color scale increments.

Figure 8: Subtracted 3D CT image of dry CO2

injected core and initially oil saturated image. Figure 9 highlights the observed fracture differences at the end of each injection step. It is apparent that all the flow, regardless of the injection fluid, was occurring through the fractures. Figures 9a and 9d show the smallest fracture apertures whereas, Figures 9b and 9c show identical and larger fracture apertures. The increase in aperture from a to b was attributed to the experimental sequential change of pore pressure and confinement pressure. In other words, the pore pressure was increased by 500psi followed by an increase of 500psi in confinement to maintain the same effective stress. As the fracture is non-homogenous, the fracture width is likely to change. Although pore pressure was reduced back to 1400psi in injection c, there was no observable change in fracture aperture from b to c as well as no additional oil recovery. Finally, at the end of injection d, the fracture aperture decreased due to injection of liquid instead of gas, in other words,

there were a few millimeters of penetration with gas injection that depicted a large fracture aperture that was no longer observed when CO2 rich water was injected.

Figure 9: Fracture subtracted images after four injection scenarios. Initial oil saturated core image is used as reference image.

The recovery of all four scenarios is summarized in Fig. 10. Only 0.02 additional oil recovery was obtained after the first injection of dry Sc- CO2 at 1400psi. This result indicates that the matrix did not contribute to the overall oil recovery and that the permeability of the chosen rock was too low to test our hypothesis. Also, the carbonate content of this specific core was relatively low compared to other previously tested cores from the same region.

Figure 10: Oil recovery versus pore volume injected for all four injection scenarios.

Conclusions We established an experimental workflow to test and quantify CO2 EOR potential in carbonate-rich shale. The core had permeability, porosity, and carbonate content that

were too low to obtain conclusive results; however, the observations helped set the selection criteria for the next set of cores to be tested. For future work, we plan to replicate these experiments on Eagleford samples that have more than 70% carbonate content and that are in the micro-Darcy permeability range. References

1. Teklu T. Kazemi H. Graves R. Hawthorne S. Braunberger J. Alharthy, N. and B. Kurtoglu. Enhanced oil recovery in liquid-rich shale reservoirs: Laboratory to field. SPE, 2015.

2. U.S. Energy Information Administration EIA. Technically recoverable shale oil and shale gas resources: an assessment of 137 shale formations in 41 countries outside the United States. 2014.

3. Speirs J. McGlade, C. and S. Sorrell. Methods of estimating shale gas resources-comparison, evaluation, and implications. Energy, 59:116–125, 2013.

4. Chen C. Mohanty, K. and M. Balhoff. Effect of reservoir heterogeneity on improved shale oil recovery by CO2 huff-n-puff. SPE, 2013.

5. S. Shoaib and B. Hoffman. Co2 flooding the elm coulee field. SPE, 2009. 6. O’Brien W. Vega, B. and A. Kovscek. Experimental investigation of oil recovery from siliceous shale by

miscible CO2 injection. SPE, 2010. 7. W. Wu and M. Sharma. Acid fracturing in shales: Effect of dilute acid on properties and pore structure of shale.

SPE, 2015.

Contacts Youssef Elkady: yelkady@stanford.edu Anthony Kovscek: kovscek@stanford.edu

Project 4: 1Mt/yr of CO2 in Basalt Reservoirs - is it viable? Abstract If we are to reach the UNFCC’s goal to limit warming to below 1.5C, it is vital we deploy geologic storage of CO2 (International Energy Agency 2007; IPCC 5th Assesment 2013; Rubin, Davison, and Herzog 2015). Geologic storage of CO2 in Basalt formations presents a unique opportunity to lock CO2 in geologic reservoirs in a stable mineral phase as carbonates in the subsurface (Lackner et al. 1995; Van Pham, Aagaard, and Hellevang 2012). Despite the success of small-scale pilot projects (McGrail et al. 2017; Snæbjörnsdóttir et al. 2018), the scalability of CCS in basaltic reservoirs still remains in question due to their impermeable and heterogenous nature. We use a hydrogeologic perspective to assess the injectivity of major Basalt formations around the world, and their viability for large scale geologic storage. Introduction Recently there has been a rise in interest in the geologic storage of CO2 storage in Basalt formations, primarily because Basalt formations present the opportunity to lock CO2 as thermodynamically stable minerals in the subsurface through mineral trapping (Van Pham, Aagaard, and Hellevang 2012). This challenge to store CO2 in the subsurface has inspired pilot projects across the world to inject CO2 into Basalt reservoirs; two of the most notable include 1) the CarbFix project in Iceland and 2) The Wallula pilot project in Washington, USA. The CarbFix project in Iceland was designed to promote and verify in-situ CO2 mineralization in basaltic rocks for the permanent disposal of anthropogenic CO2 emissions. Two injection tests were performed at the CarbFix injection site near the Hellisheidi geothermal power plant. The target CO2 storage formation is between 400 and 800 m depth and consists of basaltic lavas and hyaloclastites. Injection rates of CO2 were on the order of 70g/s for Test 1 and 50g/s for Test 2 (Gislason et al. 2016). In contrast the Wallula pilot project, in Washington, USA was the world’s first project to inject supercritical CO2 into a Basalt formation. Over three weeks they injected 1000Mt of CO2 into the Columbia River Basalt, equivalent to an injection rate of 0.46kg/s (McGrail et al. 2014, 2017). For a standard coal fired power plant that emits 1Mt of CO2/year, we need to inject at rate of 32kg/s. Such high rates require sufficient permeability to maintain safe injection pressure, as insufficient reservoir permeability can lead to high reservoir pressures that induce fractures in the host reservoir and caprock compromising reservoir integrity. Our research effort involves conducting an assessment on the injectivity of Basalt formations. Background When we inject CO2 into a reservoir, maintaining safe injection pressures exerts a fundamental limit on the CO2 injection rate and subsequently the CO2 storage potential of that reservoir. The pressure buildup equation for multiphase fluids at the injection well is given by the following equation:

Here Q is volumetric flow rate (m3/s), t is time, Uw is the viscosity of water, UCO2 is the viscosity of CO2, k is permeability of the reservoir, b is thickness of the reservoir, rw is the radius of the well, rf is the radius of the front, krCO2 is the relative permeability of CO2, and fCO2 is the factional flow of CO2. A safe rule of thumb limits safe injection pressure buildup to ~170% of initial reservoir pressure. Initial reservoir pressure can be calculated using the following equation:

Pdepth = Ptop + pgz

Where P is pressure at the surface, p is density of formation water (which we assume to be 1000g/m3), g is the gravity (9.8m/s) and z is depth (m). Basalt aquifers are generally low in permeability thus injection rates to maintain safe reservoir pressure per well are low. These low rates ultimately limit the CO2 storage potential of the reservoir. Key parameters that influence pressure buildup are permeability and the thickness of the injection interval. We take a hydrogeologic perspective on CO2 injection into basalt formations to assess the viability of large-scale CO2 injection into basalt reservoirs for geologic storage of CO2. Results We use average hydraulic conductivity measurements from the Basalt Waste Isolation Project (BWIP) in the Columbia River Basalt to calculate permeability for basalt flow tops, basalt interior and interbedded sedimentary reservoirs and construct a conceptual geological model. Initial conditions are set at 80Bar and 41C simulating a depth of ~800m. The thickness of the geological units are as follows; flow interior (40m), flow top (30m), and intercalated sedimentary bed (9m). We consider two CO2 injection cases to monitor pressure buildup at the well and assess the large-scale feasibility of CO2 injection in Columbia River Basalt. In Case 1 we simulate injection into a thick flowtop (30m), in Case 2 we simulate injection into at thin interbedded sedimentary reservoir (9m). CASE 1: Injection into flowtop

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CASE 2: Injection into intercalated sediment. In both cases our results show injection at the commercial scale required (1Mt/yr) would lead to pressures in the reservoir 2875x the initial reservoir pressure in Case 1 despite the reservoir being 30m thick, and 29.7x initial reservoir pressure in Case 2 (Figure 1), both are well above the safe rule of thumb pressure limit of 1.7x initial reservoir pressure. Case 1 Case 2

Figure 1: Pressure build up with time for Case 1 (injection into flow top) and Case 2 (injection into interbed). Assuming there is only 1 interval for injection, we use vertical wells and there is a constant supply of CO2 at 1Mt/year, to maintain safe pressure levels we must decrease Q (volumetric flow rate) at the well by increasing the number of wells. Case 1 requires 4000

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wells while Case 2 requires 50 wells to bring injection rate (Q) low enough so that reservoir pressure does not exceed the safe limit. Assuming a drilling cost of ~$300/ft and an injection period of 20 years this equates to a drilling cost of $157/t of CO2 for Case 1 and $1.97/ton for Case 2. Case 1 Case 2

Figure 2: Pressure build up with time for Case 1 (injection into flow top) and Case 2 (injection into interbed) with multiple wells to maintain safe pressure (<1.7x initial reservoir pressure). Conclusions These findings have implications for the large-scale adaption of CCS in Basalt reservoirs. Injection into interbedded sedimentary formations within Basalt reservoirs may provide enough permeability and thickness for cost effective CO2 storage. However, a thorough analysis of the petrophysical properties of basalt reservoirs and their depositional environments is required to fully assess the injectivity of large-scale injection into Basalt formations. This is focus of ongoing research. We are gathering petrophysical data from key Basalt formations around the world (Figure 3, below) and are conducting an assessment on the injectivity of Basalt formations.

Figure 3: A) Map of Basalt formations around the world; yellow star indicates major formations data (adapted from Oelkers, Gislason, & Matter, 2008). B) Profile of permeability with depth for the major formations around the world. Red lines show thresholds for storage characteristics, 800m depth is required for CO2 to be in a super critical phase. While the 1mD boundary marks the threshold for potential reservoirs (> 1mD) and impermeable rocks or potential seals (<1 mD). C) Profile of porosity with depth. Shows a trend toward less porosity and variability in porosity with increasing depth. This is ongoing research and involves addressing the following overarching questions:

1. Given existing hydraulic conductivity and permeability measurements, under what conditions is injection of CO2 into basalt formations technically and economically scalable?

2. To what extent does the application of horizontal wells influence the viability of CO2 injection in Basalt?

A

B C

3. To what extent does CO2 storage potential and injectivity differ between basalts of Marine

vs. Terrestrial origin? References

1. Franzson, Hjalti et al. 2000. “Database on Igneous Rock Properties in Icelandic Geothermal Systems. Status and Unexpected Results.” World Geothermal Congress 2000 (November 2015): 2881–86.

2. Gislason, Sigurdur R et al. 2016. “Carbon Dioxide Emissions.” Science 352(6291): 10–13. 3. International Energy Agency. 2007. World Energy Outlook 2007 - China and India Insight. 4. IPCC 5th Assesment. 2013. 5. Lackner, Klaus S. et al. 1995. “Carbon Dioxide Disposal in Carbonate Minerals.” Energy 20(11): 1153–70. 6. McGrail, B. P. et al. 2014. “Injection and Monitoring at the Wallula Basalt Pilot Project.” Energy Procedia 63:

2939–48. http://dx.doi.org/10.1016/j.egypro.2014.11.316. 7. ———. 2017. “Wallula Basalt Pilot Demonstration Project: Post-Injection Results and Conclusions.” Energy

Procedia 114(November 2016): 5783–90. http://dx.doi.org/10.1016/j.egypro.2017.03.1716. 8. Moore, James G. 2001. “Density of Basalt Core from Hilo Drill Hole, Hawaii.” Journal of Volcanology and

Geothermal Research 112(1–4): 221–30. 9. Oelkers, Eric H., Sigurdur R. Gislason, and Juerg Matter. 2008. “Mineral Carbonation of CO2.” Elements 4(5):

333–37. 10. Van Pham, Thi, Per Aagaard, and Helge Hellevang. 2012. “On the Potential for CO2 Mineral Storage in

Continental Flood Basalts – PHREEQC Batch- and 1D Diffusion–Reaction Simulations.” Geochemical Transactions 13(1): 5. http://www.geochemicaltransactions.com/content/13/1/5.

11. Rossetti, Lucas M. et al. 2019. “Evaluating Petrophysical Properties of Volcano-Sedimentary Sequences: A Case Study in the Paraná-Etendeka Large Igneous Province.” Marine and Petroleum Geology 102(April 2018): 638–56. https://doi.org/10.1016/j.marpetgeo.2019.01.028.

12. Rubin, Edward S., John E. Davison, and Howard J. Herzog. 2015. “The Cost of CO2capture and Storage.” International Journal of Greenhouse Gas Control 40: 378–400. http://dx.doi.org/10.1016/j.ijggc.2015.05.018.

13. Snæbjörnsdóttir, Sandra et al. 2018. “The Geology and Hydrology of the CarbFix2 Site, SW-Iceland.” Energy Procedia 146: 146–57. https://doi.org/10.1016/j.egypro.2018.07.019.

14. Zakharova, Natalia V. et al. 2012. “Petrophysical and Geochemical Properties of Columbia River Flood Basalt: Implications for Carbon Sequestration.” Geochemistry, Geophysics, Geosystems 13(11): 1–22.

Contacts Gurinder Nagra: gnagra@stanford.edu Sally M. Benson: smbenson@stanford.edu

Project 5: Molten-media methane pyrolysis for solid carbon capture, utilization, and sequestration Abstract A quarter of global greenhouse gas emissions can be attributed to industrial combustion and processes. Reductions in industrial sector emissions are essential to achieve climate change mitigation goals. Methane pyrolysis has the potential to decarbonize parts of the industrial sector. This technology could be retrofitted to produce low-carbon hydrogen (H2) for distributed combustion equipment or for industrial processes while generating a solid carbon that can be sold into secondary markets or permanently sequestered. This research effort implements an energy systems design optimization to assess the technoeconomics of methane pyrolysis using a molten media to catalyze the reaction and continuously separate the carbon. A 50 MW boiler is used as a base case for combustion applications in this work. Existing boilers can be expensive to retrofit and operate with CO2 capture and sequestration (CCS) at small-scale. Under base case assumptions, we find the levelized cost of low-carbon energy is $11.10/MMBTU, corresponding to a marginal abatement cost of $115/tonne CO2 avoided. In addition, we look at one potential application: use of low-carbon H2 at refineries covered by the Low Carbon Fuels Standard (LCFS) in California. In the absence of credits, the levelized cost of hydrogen is $1.75/kg H2. When LCFS credits are awarded and sold at recent prices of $190/tonne CO2e, we find the levelized cost of hydrogen drops to $0.34/kg H2. The space of economic sensitivities was explored, finding that, while design challenges remain out-standing, the estimated abatement costs are competitive with CCS or other low-carbon H2 production pathways. Introduction Representing nearly a quarter of global GHG emissions, substantial reductions in industrial sector CO2 emissions are required in order to mitigate climate change. Carbon-capture technologies separate and sequester carbon oxides produced from combustion carbon-based fuel. However, the economics of operating these technologies at small scale and without significant retrofits is challenging. The Global CCS Institute estimates the GHG abatement costs for a variety of CCS applications. For large-scale, post-combustion capture at a natural gas-fired generator, costs are estimated at $89/tonne CO2 avoided [1]. Another emissions-reduction pathway is fuel-switching to a zero-carbon fuel such as hydrogen (H2) or leveraging low-carbon H2 for industrial processes. H2 can be produced from steam methane reforming (SMR) combined with CCS (SMR-CCS) or from water electrolysis. Recent academic work estimates abatement costs to be $100/tCO2 for SMR-CCS and over $500/tCO2 for electrolysis fueled by renewable electricity [2]. One technology at the intersection of these emissions-reduction paradigms is methane pyrolysis. Methane pyrolysis produces solid carbon that can be sequestered or used prior to combustion and an H2-rich gas that could be used in combustion applications as well as hydrotreating in oil refineries. Methane pyrolysis requires a solid catalyst to operate the endothermic reaction at industrially feasible rates, however deposition of solid carbon can quickly deactivate a solid catalyst. One solution to the separation challenge is to use a bubble column as the reaction environment, with a molten media providing an efficient heat transfer medium and acting as a catalyst [3]. The carbon floats to the surface as a

fine solid, avoiding deactivation of the catalyst. This solid carbon can be transported to sites for permanent sequestration or sold as a manufacturing feedstock [2]. The objective of this work is to evaluate the technoeconomic performance of a catalytic molten-media methane pyrolysis system through optimization of the energy system design. Leveraging these results, we provide insight regarding how this technology may compete economically with other options for reducing industrial emissions in two specific use cases: fuel-switching at distributed combustion applications and substitution for conventional sources of hydrogen in oil refining. Background Methane pyrolysis is a chemical process where the carbon is stripped from CH4, yielding gaseous H2 and solid carbon. This reaction is endothermic, requiring 75 kJ/mol CH4. However, this process usually involves a solid catalyst which can become deactivated over time and must be regenerated, typically by oxidizing the carbon [4]. Using a molten media, such as a metal or salt, as the heat transfer medium and reaction catalyst may solve separation challenges associated with conventional methane cracking. Molten media methane pyrolysis In 1930, Daniel Tyrer patented a continuous process for producing hydrogen via decomposition in a molten iron bath, introducing air into a separate, but connected, chamber to oxidize the carbon and fuel the endothermic pyrolysis reaction [5]. More recently, Steinberg (1999) proposes the use of a liquid metal bubble column to facilitate the thermal decomposition of methane into hydrogen and solid carbon [6]. Serban et al. (2003) conducted several early experiments of methane cracking in molten tin and lead baths [7]. Paxman et al. (2014) investigate the use of solar thermal energy to fuel a molten media methane pyrolysis reactor [8]. Researchers at the Karlsruhe Institute of Technology have conducted a variety of experiments and analyses of this technology as well [4, 9, 10, 11]. Geißler et al. (2015, 2016) conducted additional experiments on a liquid tin bubble column reactor with a packed bed and find maximum hydrogen yields of 78% [12,13]. However, these non-catalytic processes require longer residence times, requiring either a larger reactor volume or lower CH4 conversion rates. Upham et al. (2017) conducted the first experiments using liquid metal catalysts alloyed with low melting temperature metals in order to convert methane into hydrogen and solid carbon [3]. Utilizing an alloy of nickel (Ni) and bismuth (Bi), the authors observed methane conversion exceeding 95% at temperatures near 1050 ˚C [3]. Parkinson et al (2018) present a technoeconomic analysis of a system such as this for comparison with steam methane reforming and electrolysis for industrial hydrogen production [14]. Recent experimental work has demonstrated that molten salts (such as MnCl2-KCl) can similarly act as catalysts for CH4 pyrolysis [15]. This study found high H2 selectivity and CH4 molar conversion fractions exceeding 40% with small residence times [15]. Other efforts to model molten media methane pyrolysis reactors have employed a membrane bubble column reactor model, identifying ultra-high conversion of CH4 [16].

Some industrial processes may not be well-suited for traditional gaseous CO2 capture techniques and barriers may exist to pipeline transmission of captured CO2 to productive end-uses. Methane pyrolysis can produce H2-rich gas to be used in industrial burners or as a direct substitute for more carbon-intensive H2 feedstocks. Results Energy systems design optimization The design optimization yielded several insights regarding process optimization for bubble column pyrolysis reactors. The optimal bubble column has a ~1.6 m radius and is ~3.2 m tall. Reactor temperature was fixed at 1100 ˚C. The optimal reactor height is dictated by the residence time required to achieve the desired minimum CH4 conversion fraction of 90%. However, the radius of the reactor was governed by the terminal velocity of the bubbles in the column and the constraint that gas holdup not exceed 10% at the column entrance.

Figure 1: Process block diagram depicting all components of the methane pyrolysis energy system for carbon-capture of industrial energy uses. The system incorporates a heat exchanger to recover all sensible heat from the H2-rich gas, preheating the inlet CH4 to ~1050 ˚C and producing the H2-rich fuel gas at a temperature of ~40 ˚C after the pre-heat exchanger. This heat exchanger recovers ~7.4 MW of thermal energy. The reactor requires heat input of 8.2 MW and 110 kW are needed for ancillary electrical loads. The electric resistive heating elements reach 1131 ˚C in order to maintain isothermal conditions inside of the reactor. A 0.29 m thick layer of carbon insulation reduces thermal losses to 290 kW. Distributed combustion applications The principal result of this analysis as applied to the case of combustion applications is the levelized cost of energy (LCOE) at which the project achieves zero NPV for the desired internal rate of return (IRR = 15%) (Figure 2, left). The energy premium (above the assumed natural gas price) can also be expressed as an effective abatement cost, in terms of $/tonne CO2 (Figure 2, right). For base case assumptions, the estimated LCOE is

$11.10/MMBTU of decarbonized gaseous fuel, which is equivalent to $1.76/kg H2. At a $5.10/MMBTU premium over the base case price of natural gas ($6/MMBTU), there would need to be a carbon emissions tax of $115/tCO2 imposed on the industrial consumer in order for this additional cost to make economic sense.

Figure 2: Levelized cost of energy, or H2 sale price (Left) and equivalent abatement cost (Right) under range of sensitivities for fuel-switching in combustion applications. Refinery applications In the case of displacing H2 produced by a conventional small-scale SMR for oil refining, the relevant metric for comparison is the levelized cost of hydrogen (LCOH). This cost would need to compete with the marginal cost of H2 from existing steam methane reforming in order to provide economic incentive to pursue development. Based on efficiency factors from CA-GREET 3.0, we estimate an all-in efficiency of 1.38 MJ CH4/MJ H2. In the base case, with natural gas prices of $6/MMBTU, this corresponds to $1.11/kg H2 from conventional SMR. This provides a benchmark from which to assess the marginal abatement cost. In the base case, we find a pyrolysis-based LCOH of $1.75/kg H2 which would correspond to an equivalent abatement cost of $52.60/tonne CO2 avoided.

Figure 3: Levelized cost of hydrogen (Left) and equivalent abatement cost (Right) under range of sensitivities for oil refinery application of methane pyrolysis.

We also consider the specific case of a refinery in California using pyrolysis to generate supplemental H2 to produce credits in the Low Carbon Fuels Standard (LCFS) program. In this scenario, the refinery must pay $10/tonne carbon to permanently sequester the solid carbon and receives LCFS credits worth $190/tonne CO2e avoided on a lifecycle basis. In this case, the levelized cost of H2 produced is $0.34/kg H2. This lies below any reasonable estimate for costs of H2 from SMR and could provide substantial returns. Therefore, as incentivized by the LCFS framework, there is a notable opportunity for oil and gas industry to invest in clean H2 for the refinery processes [17]. However, there would need to be rigorous verification that the solid carbon was permanently sequestered and did not return to the atmosphere as a carbon oxide. Conclusions We find levelized costs of energy in the range of $9 to $15/MMBTU ($1.50 to $2.20/kg H2) and equivalent abatement costs between $100 and $150/tonne CO2 avoided. At these estimates, methane pyrolysis is competitive with other emissions reduction measures, including carbon capture and other pathways for low-carbon H2 production. However, the superior option will largely depend on site-specific factors. The proposed methane pyrolysis energy system may be one option for reducing greenhouse gas emissions in the near term while minimizing stranded assets and continuing to leverage existing infrastructure. Unique engineering and design challenges remain, and the technology is unproven at any commercial scale, but a molten media-based methane pyrolysis process may offer advantages with respect to carbon supply chain or preferential economic characteristics and sensitivities. References

1. Irlam, L. (2017). Global Costs of Carbon Capture and Storage: 2017 Update. Global CCS Institute. 2. Parkinson, B., Balcombe, P., Speirs, J. F., Hawkes, A. D., & Hellgardt, K. (2019). Levelized cost of CO 2

mitigation from hydrogen production routes. Energy & Environmental Science, 12(1), 19-40. 3. Upham, D. C., Agarwal, V., Khechfe, A., Snodgrass, Z. R., Gordon, M. J., Metiu, H., & McFarland, E. W.

(2017). Catalytic molten metals for the direct conversion of methane to hydrogen and separable carbon. Science, 358(6365), 917-921.

4. Abanades, A., Rubbia, C., & Salmieri, D. (2012). Technological challenges for industrial development of hydrogen production based on methane cracking. Energy, 46(1), 359-363.

5. D. Tyrer, Production of hydrogen. USA Patent US1803221 A, 28 April 1931. 6. Steinberg, M. (1999). Fossil fuel decarbonization technology for mitigating global warming. International

Journal of Hydrogen Energy, 24(8), 771-777. 7. Serban, M., Lewis, M. A., Marshall, C. L., & Doctor, R. D. (2003). Hydrogen production by direct contact

pyrolysis of natural gas. Energy & fuels, 17(3), 705-713. 8. Paxman, D., Trottier, S., Nikoo, M., Secanell, M., & Ordorica-Garcia, G. (2014). Initial experimental and

theoretical investigation of solar molten media methane cracking for hydrogen production. Energy Procedia, 49, 2027-2036.

9. Abanades, A., Rubbia, C., & Salmieri, D. (2013). Thermal cracking of methane into hydrogen for a CO2-free utilization of natural gas. International Journal of Hydrogen Energy, 38(20), 8491-8496.

10. Plevan, M., Geißler, T., Abánades, A., Mehravaran, K., Rathnam, R. K., Rubbia, C., ... & Wetzel, T. (2015). Thermal cracking of methane in a liquid metal bubble column reactor: Experiments and kinetic analysis. International Journal of Hydrogen Energy, 40(25), 8020-8033.

11. Postels, S., Abánades, A., von der Assen, N., Rathnam, R. K., Stückrad, S., & Bardow, A. (2016). Life cycle assessment of hydrogen production by thermal cracking of methane based on liquid-metal technology. International Journal of Hydrogen Energy, 41(48), 23204-23212.

12. Geißler, T., Abánades, A., Heinzel, A., Mehravaran, K., Müller, G., Rathnam, R. K., ... & Weisenburger, A. (2016). Hydrogen production via methane pyrolysis in a liquid metal bubble column reactor with a packed bed. Chemical Engineering Journal, 299, 192-200.

13. Geißler, T., Plevan, M., Abánades, A., Heinzel, A., Mehravaran, K., Rathnam, R. K., ... & Weisenburger, A. (2015). Experimental investigation and thermo-chemical modeling of methane pyrolysis in a liquid metal bubble column reactor with a packed bed. International Journal of Hydrogen Energy, 40(41), 14134-14146.

14. Parkinson, B., Matthews, J. W., McConnaughy, T. B., Upham, D. C., & McFarland, E. W. (2017). Techno-Economic Analysis of Methane Pyrolysis in Molten Metals: Decarbonizing Natural Gas. Chemical Engineering & Technology, 40(6), 1022-1030.

15. Kang, D., Rahimi, N., Gordon, M. J., Metiu, H., & McFarland, E. W. (2019). Catalytic Methane Pyrolysis In Molten MnCl2-KCl. Applied Catalysis B: Environmental.

16. Farmer, T. C., McFarland, E. W., & Doherty, M. F. (2019). Membrane bubble column reactor model for the production of hydrogen by methane pyrolysis. International Journal of Hydrogen Energy.

17. California Air Resources Board (CARB). (2018). Staff Report: Initial Statement of Reasons. Retrieved from https://www.arb.ca.gov/regact/2018/lcfs18/isor.pdf

Contacts Gregory A. Von Wald: gvonwald@stanford.edu Mohammad S. Masnadi: masnadi@stanford.edu D. Chester Upham: dcupham@stanford.edu Adam R. Brandt: abrandt@stanford.edu