Burke J. Minsley

Spatial orientation and distribution of reservoir fractures from scattered seismic energy

Wepresentthedetailsofanewmethodfordeterminingthereflection and scattering characteristics of seismic energy from subsurface fractured formations. The method is based upon observations we have made from 3D finite-difference modeling of the reflected and scattered seismic energy over discrete systems of vertical fractures. Regularly spaced, discrete vertical fracture corridors impart a coda signature, which is a ringing tail of scatteredenergy,toanyseismicwaveswhicharetransmittedthrough or reflected off of them. This signature varies in amplitude and coherence as a function of several parameters including: 1 the difference in angle between the orientation of the fractures and the acquisition direction, 2 the fracture spacing, 3 the wavelength of the illuminating seismic energy, and 4 the compliance, or stiffness, of the fractures. This coda energy is most coherent when the acquisition direction is parallel to the strike of thefractures.Ithasthelargestamplitudewhentheseismicwavelengths are tuned to the fracture spacing, and when the fractures have low stiffness. Our method uses surface seismic reflection tracestoderiveatransferfunctionthatquantifiesthechangeinan apparent source wavelet before and after propagating through a fracturedinterval.Thetransferfunctionforanintervalwithnoor low amounts of scattering will be more spikelike and temporally compact. The transfer function for an interval with high scattering will ring and be less temporally compact. When a 3D survey is acquired with a full range of azimuths, the variation in the derived transfer functions allows us to identify subsurface areas with high fracturing and to determine the strike of those fractures.Wecalibratedthemethodwithmodeldataandthenapplied ittotheEmiliofieldwithafracturedreservoir.Themethodyielded results which agree with known field measurements and previously published fracture orientations derived from PS anisotropy.

Critical steps for the continuing advancement of hydrogeophysics

Special hydrogeophysics issues published by hydrology and geophysics journals, special sessions and workshops at conferences, and an increasing number of short courses demonstrate the growing interest in the use of geophysics for hydrologic investigations. The formation of the hydrogeophysics technical subcommittee of AGUs Hydrology section adds further evidence of the recognized significance of this growing interdisciplinary field. Given the clear value of nondestructive and nonintrusive imaging for subsurface investigations, we believe the advances in the adoption of existing geophysical methods, the development of novel methods, and the merging of geophysical and other data made in hydrogeophysics could be applied to a wide range of geological, environmental, and engineering applications.

Multiscale geophysical imaging of the critical zone

Details of Earths shallow subsurface—a key component of the critical zone (CZ)—are largely obscured because making direct observations with sufficient density to capture natural characteristic spatial variability in physical properties is difficult. Yet this inaccessible region of the CZ is fundamental to processes that support ecosystems, society, and the environment. Geophysical methods provide a means for remotely examining CZ form and function over length scales that span centimeters to kilometers. Here we present a review highlighting the application of geophysical methods to CZ science research questions. In particular, we consider the application of geophysical methods to map the geometry of structural features such as regolith thickness, lithological boundaries, permafrost extent, snow thickness, or shallow root zones. Combined with knowledge of structure, we discuss how geophysical observations are used to understand CZ processes. Fluxes between snow, surface water, and groundwater affect weathering, groundwater resources, and chemical and nutrient exports to rivers. The exchange of gas between soil and the atmosphere have been studied using geophysical methods in wetland areas. Indirect geophysical methods are a natural and necessary complement to direct observations obtained by drilling or field mapping. Direct measurements should be used to calibrate geophysical estimates, which can then be used to extrapolate interpretations over larger areas or to monitor changing processes over time. Advances in geophysical instrumentation and computational approaches for integrating different types of data have great potential to fill gaps in our understanding of the shallow subsurface portion of the CZ and should be integrated where possible in future CZ research.

Applying compactness constraints to differential traveltime tomography

Tomographic imaging problems are typically ill-posed and often require the use of regularization techniques to guarantee a stable solution. Minimization of a weighted norm of model length is one commonly used secondary constraint. Tikhonov methods exploit low-order differential operators to select for solutions that are small, flat, or smooth in one or more dimensions. This class of regularizing functionals may not always be appropriate, particularly in cases where the anomaly being imaged is generated by a nonsmooth spatial process. Time-lapse imaging of flow-induced velocity anomalies is one such case; flow features are often characterized by spatial compactness or connectivity. By performing inversions on differenced arrival time data, the properties of the time-lapse feature can be directly constrained. We develop a differential traveltime tomography algorithm whichselects for compact solutions, i.e., models with a minimum area of support, through application of model-space iteratively reweighted leas...

Hydrogeophysical methods for analyzing aquifer storage and recovery systems

Hydrogeophysical methods are presented that support the siting and monitoring of aquifer storage and recovery (ASR) systems. These methods are presented as numerical simulations in the context of a proposed ASR experiment in Kuwait, although the techniques are applicable to numerous ASR projects. Bulk geophysical properties are calculated directly from ASR flow and solute transport simulations using standard petrophysical relationships and are used to simulate the dynamic geophysical response to ASR. This strategy provides a quantitative framework for determining site-specific geophysical methods and data acquisition geometries that can provide the most useful information about the ASR implementation. An axisymmetric, coupled fluid flow and solute transport model simulates injection, storage, and withdrawal of fresh water (salinity ∼500 ppm) into the Dammam aquifer, a tertiary carbonate formation with native salinity approximately 6000 ppm. Sensitivity of the flow simulations to the correlation length of aquifer heterogeneity, aquifer dispersivity, and hydraulic permeability of the confining layer are investigated. The geophysical response using electrical resistivity, time-domain electromagnetic (TEM), and seismic methods is computed at regular intervals during the ASR simulation to investigate the sensitivity of these different techniques to changes in subsurface properties. For the electrical and electromagnetic methods, fluid electric conductivity is derived from the modeled salinity and is combined with an assumed porosity model to compute a bulk electrical resistivity structure. The seismic response is computed from the porosity model and changes in effective stress due to fluid pressure variations during injection/recovery, while changes in fluid properties are introduced through Gassmann fluid substitution.

Hydrogeophysical Investigations at Hidden Dam, Raymond, California

Self-potential and direct current resistivity surveys are carried out at the Hidden Dam site in Raymond, California to assess present-day seepage patterns and better understand the hydrogeologic mechanisms that likely influence seepage. Numerical modeling is utilized in conjunction with the geophysical measurements to predict variably-saturated flow through typical two-dimensional dam cross-sections as a function of reservoir elevation. Several different flow scenarios are investigated based on the known hydrogeology, as well as information about typical subsurface structures gained from the resistivity survey. The flow models are also used to simulate the bulk electrical resistivity in the subsurface under varying saturation conditions, as well as the self-potential response using petrophysical relationships and electrokinetic coupling equations. The self-potential survey consists of 512 measurements on the downstream area of the dam, and corroborates known seepage areas on the northwest side of the dam. Two directcurrent resistivity profiles, each approximately 2,500 ft (762 m) long, indicate a broad sediment channel under the northwest side of the dam, which may be a significant seepage pathway through the foundation. A focusing of seepage in low-topography areas downstream of the dam is confirmed from the numerical flow simulations, which is also consistent with past observations. Little evidence of seepage is identified from the self-potential data on the southeast side of the dam, also consistent with historical records, though one possible area of focused seepage is identified near the outlet works. Integration of the geophysical surveys, numerical modeling, and observation well data provides a framework for better understanding seepage at the site through a combined hydrogeophysical approach.

Evidence for nonuniform permafrost degradation after fire in boreal landscapes

Fire can be a significant driver of permafrost change in boreal landscapes, altering the availability of soil carbon and nutrients that have important implications for future climate and ecological succession. However, not all landscapes are equally susceptible to fire-induced change. As fire frequency is expected to increase in the high latitudes, methods to understand the vulnerability and resilience of different landscapes to permafrost degradation are needed. We present a combination of multiscale remote sensing, geophysical, and field observations that reveal details of both near-surface ( 1 m) impacts of fire on permafrost. Along 11 transects that span burned-unburned boundaries in different landscape settings within interior Alaska, subsurface electrical resistivity and nuclear magnetic resonance data indicate locations where permafrost appears to be resilient to disturbance from fire, areas where warm permafrost conditions exist that may be most vulnerable to future change, and also areas where permafrost has thawed. High-resolution geophysical data corroborate remote sensing interpretations of near-surface permafrost and also add new high-fidelity details of spatial heterogeneity that extend from the shallow subsurface to depths of about 10 m. Results show that postfire impacts on permafrost can be variable and depend on multiple factors such as fire severity, soil texture, soil moisture, and time since fire.

Generation of 3‐D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the models predictive capability.

Minimization of self-potential survey mis-ties acquired with multiple reference locations

Self-potential (SP) surveys often involve many interconnected lines of data along available roads or trails, with the ultimate goal of producing a unique map of electric potentials at each station relative to a single reference point. Multiple survey lines can be tied together by collecting data along intersecting transects and enforcing Kirchhoff’s voltage law, which requires that the total potential drop around any closed loop equals zero. In practice, however, there is often a nonzero loop-closure error caused by noisy data; traditional SP processing methods redistribute this error evenly over the measurements that form each loop. The task of distributing errors and tying lines together becomes nontrivial when many lines of data form multiple interconnected loops because the loop-closure errors are not independent, and a unique potential field cannot be determined by processing lines sequentially. We present a survey-consistent processing method that produces a unique potential field by minimizing the ...

A matlab-based frequency-domain electromagnetic inversion code (FEMIC) with graphical user interface

We present a new Matlab-based11Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. frequency-domain electromagnetic (EM) inversion code (FEMIC) for analysis of datasets collected using multi-frequency EM-induction instruments. The code includes routines for data filtering and calibration, forward modeling, inverse modeling, image appraisal (i.e., calculation of the depth of investigation), and visualization. A one-dimensional forward model is assumed, but two or three dimensional lateral regularization constraints can be applied during the inversion. The code can take advantage of the parallel-processing capabilities of multi-processor computers, thus facilitating efficient inversion of large datasets. Synthetic and field examples demonstrate the operation of the FEMIC code and showcase its capabilities. Source code is provided as material supplementary to this paper to allow modifications and extensions by others.