This is only a subset of my research over the years. I don’t have the patience to create a fully comprehensive overview of my research with text and images, and I doubt anyone would care to see it all. For a compact list of my projects, you can find that in my (likely out-of-date) VITAE page.
multiphysics integration for carbon capture, utilization & storage (CCUS) monitoring
Integrated development of 3D electrical conductivity site models for CCUS monitoring with charged wellbore casing controlled-source electromagnetics (CWC-CSEM). Here, the model is constructed through the multiphysics integration of reservoir simulation, seismic, borehole resistivity, and transient EM (TEM) data. The process is performed in two stages. First, a large background conductivity model is constructed from the combination of seismic, borehole, and TEM data. Second, a more detailed and dynamic component of the model is created within the production interval by converting the reservoir simulation parameters to conductivity through Archie’s equation. The developed site models can be used to simulate and interpret the CWC-CSEM data as one step in the larger problem of reservoir imaging and monitoring of injected CO2. Images from Krahenbuhl et al, 2019
Deep investigation into the self-demagnetization effects on magnetic data and means for quantitative interpretation of such data in highly magnetic environments. Conventional inversion can perform well for interpretation of self-demagnetization problems with simple source geometries. However, as geometry becomes more complex for real targets such as banded iron formations, this approach tends to produce poor results. Directly inverting amplitude data, which can be derived from total-field magnetic anomaly data and are weakly-dependent on magnetization direction, produces superior results when interpreting data from areas with complex geology and high magnetic susceptibilities. The image demonstrates the strength of this approach on a large magnetic data set from the Hawsons iron deposit that exhibits strong self-demagnetization, multiple source bodies and complex structures. Images from Krahenbuhl & Li, 2017
guiding next generation sensors: time-lapse borehole vector gravity for reliable subsurface monitoring
We have thoroughly simulated and strongly supported development of borehole vector gravity sensors over traditional vertical gravity for improved time-lapse monitoring problems such as EOR and CCS. It is well understood that for monitoring with the vertical-only component of the gravity field, the lack of horizontal information and the potential for data saturation after a flood front passes a monitoring well, limits gravity method from achieving its full potential. To overcome these boundaries, the time-lapse borehole vector gravity data demonstrate the possibility of detecting a continuously changing field in magnitude, and more significantly in direction consistent with lateral water or CO2 movement, thus providing more complete long term monitoring information about the fluid front. Images from Krahenbuhl et al., 2019
sensing during rapid drilling in urban settings
A significant challenge to rapid drilling in urban environments is the ability to reliably detect and interpret approaching targets of possible concern for collision avoidance. Such features may include storm water systems, gas distribution lines, and basement with pile foundations. We perform detailed magnetic simulations beneath urban environments, particularly around such targets of interest and along simulated drill-paths to understand: 1) their geophysical signatures; 2) their detection distances from varying directions and inducing fields; and 3) the possibility of avoiding such features.
agriculturally induced landslides in hyper arid settings
Near-surface geophysical survey performed in and around the agricultural fields in Majes, Peru to understand the relationship between geology, agricultural irrigation, and increased landslide activity. Surveys include seismic, ground penetrating radar, transient EM, and DC resistivity methods. Geophysics results are used to update finite-element landslide modeling to understand the role of water percolation from the agricultural fields. Images from Flamme et al, 2020 and Krahehenbuhl et al, 2020.
pledger ccs: evaluating resolution of time-lapse gravity co2 sequestration monitoring
Robust evaluation of time-lapse gravity to monitor CO2 sequestration. The project is a component of a larger geotechnical suitability study to evaluate a specific field’s potential for CO2 storage and to evaluate viable techniques for effective monitoring there. The reservoir model for this study is constructed from detailed reservoir data available through separate reservoir characterization studies of the field. The gravity inversion used is a highly constrained binary approach that incorporates reservoir geometry from seismic data and the internal 3D distributions of density change predicted from the reservoir engineering database. Images from Krahenbuhl et al, 2015
Monitoring Steam Assisted Gravity Drainage with gravity and gravity gradiometry
Even though time-lapse seismic has historically shown great success for monitoring steam assisted gravity drainage, or SAGD, the gravimetry and gravity gradiometry methods offer a low-cost interseismic alternative that can complement the seismic method, increase the survey frequency, and decrease the cost of monitoring. In addition, both gravity-based methods are directly sensitive to the density changes that occur as a result of the replacement of heavy oil by steam. Advances in technologies have made both methods viable candidates for consideration in time-lapse reservoir monitoring. Images from Reitz, Krahenbuhl, & Li, 2015
Unexploded Ordnance Detection and discrimination using magnetic data
SERDP Project-MM-1638 advance detection and discrimination technologies of buried UXO through development of new processing methods for identifying potential UXO targets in the presence of anomalies of geologic origin, and interpretation algorithms utilizing higher-order moments of associated magnetic targets. Rather than following the traditional approach of identifying only hazardous UXO, we develop a comprehensive method to first identify all UXO-like targets in the presence of geologic noise, and then recognize both UXO and non-UXO through indirect shape reconstruction from higher-order moments. Poster from Krahenbuhl et al, 2009 (Symposium)
Artifical aquifer storage and recovery monitoring
Hybrid optimization for the binary inversion of time-lapse gravity data to monitor a local aquifer storage and recovery (ASR) system. The Leyden mine, located in Arvada, Colorado, was an active dual-seam underground coal mine until its closure in 1958. The city began use of the abandoned mine site for underground water storage by injecting purified water into the artificial aquifer in 2003. The goal of the project was to store excess water runoff during the wet winter months in Colorado, and recover the water as necessary during the water-strained summer months. Time-lapse gravity data collected over the ASR site are successfully interpreted to water movement and storage at the site. Images from Krahenbuhl & Li, 2009; Davis et al, 2009; Capriotti & Li, 2013. Time-lapse field data were collected by Davis and Capriotti.
enhanced oil recovery (eor) monitoring
In this study based on the Jotun Field in the Norwegian North Sea, we show through complex model construction and robust inversion that time-lapse gravity surveys may contribute to improved production efficiency and reservoir management in-between the more traditional, and expensive 4D seismic surveys. Results hint that the true value of time-lapse gravity as an additional tool for production efficiency and reservoir management may be greatly undervalued. We show that data simulated within current and ongoing sensor technologies, combined with advances in computing power and robust inversion, can extract much more meaningful information about fluid movement in reservoirs that are geometrically complex and relatively thin and deep. Images from Krahenbuhl et al, 2011.
adaptive data sampling of geophysical data for fast large-scale inversion
We have developed a direct and practical approach to the adaptive downsampling of potential-field data for large inversion problems. The approach is formulated to significantly reduce the quantity of data in relatively smooth or quiet regions of the data set, while preserving the signal anomalies that contain the relevant target information. As the approach compresses the problem in the data domain, it can be applied immediately without the addition of, or modification to, existing inversion software. Additionally, as most industry software use some form of model or sensitivity compression, the addition of this adaptive data sampling creates a complete compressive inversion methodology whereby the reduction of computational cost is achieved simultaneously in the model and data domains. Applications of the method have demonstrated that the relevant model information is maintained after inversions, sometimes using as little as 1%–5% of the data. Method and images from Foks et al, 2014; and Krahenbuhl & Li, 2017.
robust parametric inversion via adaptive quenched simulated annealing
There is a class of inverse problems in applied geophysics that is well described by a parameter estimation approach. Such problems are often characterized by strong nonlinearity, multimodal objective functions, and parameter bounds that can be well-defined in some cases and unknown in others. We developed a robust parametric inversion algorithm designed for such problems based on an adaptive quenched simulated annealing (AQSA). The method combines successive refinement of the parameter search space and adaptive bound constraints to address some the difficulties associated with multi-modality in the objective function and to improve the numerical efficiency. Results are illustrated here for the problem of ensemble fitting in potential field method for UXO detection and discrimination. Images from Krahenbuhl & Li, 2015.
joint parametric inversion of gravity and magnetic data with strong remanent magnetization
Adaptive QSA provides a powerful tool for the independent and joint parametric inversion of gravity and magnetic data. For example, in the case here of gravity and magnetic data over a hidden dipping geologic dyke with remanent magnetization, random candidate solutions are initialized by QSA for the geologic feature, and the parameter bounds are adaptively updated throughout the process. The results from adaptive QSA for the joint inversion is a better representation of the dyke over gravity and magnetics alone in this case. The joint solution better recovers: 1) the width over both gravity and magnetics along; 2) dip, depth extent and magnetization inclination over magnetics alone; and 3) both physical properties over the individual data inversions. Images from Krahenbuhl & Li, 2015.
exploration: imaging base of salt
Salt beds, including domes, ridges and pillows, are relatively incompressible and therefore remain fairly constant in density throughout. This incompressibility likewise allows for abundant traps throughout regions such as the Gulf of Mexico. As a result, they have become major targets in oil and gas exploration. Gravity and gradiometry are two cost-effective tools available for imaging these exploration targets. The interpretation problem then one of recovering density distribution of the salt body as a function of spatial position. Challenges arise when the salt body straddles a nil-zone, i.e. a regions of zero density contrast to the surrounding sediments. This task is not trivial and requires additional prior information to help improve the solution. One approach to overcome this difficulty is to separate the problem into its two fundamental components, i.e., density and location. By supplying density information appropriate to the salt feature as a constraint, a binary inversion approach may then focus on the single task of defining the location and extent of the target. This form of highly constrained inversion has demonstrated significant improvement in gravity inversion for cases where such prior information is available, in particular for imaging base of salt in exploration. Images from Hatch et al., 2015
gas cap water injection (GCWI) monitoring at prudhoe bay with time-lapse micro-gravity data
We have revisited the time-lapse gravity data collected to monitor gas-cap water injection at Prudhoe Bay to understand how we can best integrate a field’s detailed reservoir simulation data into the gravity inversion for an integrated interpretation. We test two methodologies that can directly incorporate into the inversions a set of time-lapse density models constructed from the reservoir simulation parameters. The first is a generalized density inversion where the reservoir information can be converted into an appropriate reference model to guide both the shape and amplitude of the recovered density change from the water flood. The second is a binary inversion where the reservoir data are included as an expected density model to pre-define the amplitudes of the time-lapse densities, allowing the algorithm to focus on recovering the location and shape of the water plume. Results for the two methods show that the reservoir data does guide the gravity inversions to distributions comparable to known water movement within the simulation models, and thus provide valuable means for integrated monitoring with time-lapse gravity. The results additionally demonstrate deviations from the reservoir simulation models, indicating that either the surface gravity is not sensitive to the subtle changes in saturation in those regions, or that the reservoir models predict saturation changes that may be too high or too low in different areas. Images from Krahenbuhl & Li, 2017; and Yin et al., 2016
understanding the applications and limitations of time-lapse gravity: delhi c02-eor feasibility
A natural alternative to seismic only monitoring is the addition of time-lapse gravity in-between seismic surveys. We develop a cost-effective and systematic approach for CO2-EOR reservoir monitoring – throughout the lifecycle of a project site and potentially for long-term monitoring of CO2 storage. To demonstrate, we simulate density change from CO2 injection over time at a recently active sequestration-EOR site, the Delhi Field in Louisiana. This multi-faceted feasibility study illustrates a reliable workflow to understanding the potential benefits, and limitations, of 4D gravity at a site, for both pre-acquisition monitoring decisions and as a guide for post-acquisition interpretation. Images from Krahenbuhl et al., 2011.
secarb cranfield carbon capture storage (ccs): integrated interpretation of borehole and reservoir simulation data
The Southeast Partnership (SECARB) test at Cranfield, Mississippi, was the first of the commercial scale projects comprising a staged array of field deployments testing key issues of capacity and best methods for assuring storage permanence. The project was unique in deploying a range of geophysical measurements including cross-well seismic and electrical resistivity tomography, from two monitoring wells positioned in line from the injector and several 100 ft down-dip. The CO2 Capture Project (CCP) took advantage of the multiple field acquisitions of borehole data during the injection phase of this project to acquire time-lapse borehole gravity in the two monitoring wells. The objectives were to understand the operational aspects and design of the acquisition, and to assess the ability of the surveys to detect the injected CO2. Images from Dodds et al., 2013
guiding next generation monitoring technology: time-lapse gravity sensors for highly deviated and horizontal monitoring wells
We identify the added benefit of jointly inverting surface and borehole gravity data for reservoir monitoring. In particular, we show that time-lapse measurements in horizontal monitoring wells can provide significant additional information about fluid movement over surface data alone. The primary advantage of such monitoring wells lies in the option to preferentially orient them with the geometry of a production or sequestration field. Additionally, well heights can be chosen to maximize the signal strength in consideration of instrument accuracy, while balancing data sensitivity to the lateral extent of the reservoir to be monitored. Images from Krahenbuhl et al., 2012