Object‐Based Inversion of Crosswell Radar Tomography Data to Monitor Vegetable Oil Injection Experiments

Abstract

Crosswell radar tomography methods can be used to dynamically image ground-water flow and mass transport associated with tracer tests, hydraulic tests, and natural physical processes. Dynamic imaging can be used to identify preferential flow paths and to help characterize complex aquifer heterogeneity. Unfortunately, because the raypath coverage of the interwell region is limited by the borehole geometry, the tomographic inverse problem is typically underdetermined, and tomograms may contain artifacts such as spurious blurring or streaking that confuse interpretation.We implement object-based inversion (using a constrained, non-linear, least-squares algorithm) as an alternative to pixel-based inversion approaches that utilize regularization (such as damping or smoothing criteria). Our approach requires pre-and post-injection travel-time data. Parameterization of the image plane comprises a small number of objects rather than a large number of pixels, resulting in an overdetermined problem that reduces the need for prior information. The nature and geometry of the objects are based on hydrologic insight into aquifer characteristics, the nature of the experiment, and the planned use of the geophysical results.The object-based inversion approach is demonstrated using synthetic and crosswell radar field data acquired during vegetable-oil injection experiments at a site in Fridley, Minnesota. The region where oil has displaced ground water is discretized as a stack of rectangles of variable horizontal extents. The inversion provides the geometry of the affected region and an estimate of the radar slowness change for each rectangle. Applying petrophysical models to these results and porosity from neutron logs, we estimate that the vegetable-oil emulsion saturation in various layers ranges from 60 to 90%. Further work is needed to assess the accuracy of the emulsion saturation estimates.Using synthetic-and field-data examples, the object-based inversion approach is shown to be an effective strategy for inverting crosswell radar tomography data acquired to monitor the emplacement of vegetable-oil emulsions. A principal advantage of object-based inversion is that it yields images that hydrologists and engineers can easily interpret and use for model calibration.

Geophysical Monitoring of a Field‐Scale Biostimulation Pilot Project

“…The derivation of (Lane et al 2004) combines with a low‐loss simplification of the complex refractive index model (Birchak et al 1974; Wharton et al 1980) to estimate the effective relative dielectric permittivity of a three‐phase mixture of water, VOE, and sediment.…”

“…In the design phase of this study (Lane et al 2004), the first petrophysical model () was used to predict the slowness‐difference anomaly that would result from injection of the VOE into water‐saturated quartz sand for different levels of VOE saturation, assuming that the VOE consists of 65% water and 35% vegetable oil/lecithin emulsifier. Here, we apply the petrophysical models to the ACP field site experimental results to estimate (1) the degree of VOE saturation resulting from injection of the VOE and (2) the change in TDS downgradient of the injections.…”

“…Tomograms provide qualitative information about vertical and horizontal variations in radar properties between the wells; however, resolution depends on measurement error, the survey geometry, and prior information used for inversion (Day‐Lewis and Lane 2004). Tomograms tend to be smoother than reality and to overestimate the size and underestimate the magnitude of target anomalies; thus, the reliability of quantitative estimates of the saturation and extent of VOE from tomograms are questionable (Lane et al 2004). For the data set collected at the ACP, Lane et al (2004) ran a series of synthetic experiments to identify likely artifacts in the tomograms collected at the ACP and improve interpretation of observed anomaly extent and magnitude.…”

“…Tomograms tend to be smoother than reality and to overestimate the size and underestimate the magnitude of target anomalies; thus, the reliability of quantitative estimates of the saturation and extent of VOE from tomograms are questionable (Lane et al 2004). For the data set collected at the ACP, Lane et al (2004) ran a series of synthetic experiments to identify likely artifacts in the tomograms collected at the ACP and improve interpretation of observed anomaly extent and magnitude. Furthermore, as an alternative to conventional pixel‐based tomography, an object‐based inversion (OBI) approach was used, in which the parameters to be estimated are chosen based on a conceptual model of the geology and physics controlling the process being monitored.…”

Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution‐dependent limitations

“…Similar in concept to medical CT scan imaging technology, geotomography yields two‐ or three‐dimensional images, i.e., tomograms, of the spatially variable physical properties of the subsurface. Geotomography has provided high‐resolution information for understanding deep earth structure [e.g., Aki et al , 1977; Zandt , 1981] and near‐surface aquifer heterogeneity [ Hyndman and Gorelick , 1996; Hubbard et al , 2001; McKenna and Poeter , 1995]; improved management of petroleum reservoirs [ Bregman et al , 1989]; monitoring natural hydrologic processes [ Park , 1998; Binley et al , 2001] and engineered remediation [ Lane et al , 2005; Slater and Binley , 2003]; and interpretation of hydrologic field experiments [ Day‐Lewis et al , 2003, 2004; Singha and Gorelick , 2005]. Here, we consider two tomographic modalities: radar travel time tomography (RTT) and electrical‐resistivity tomography (ERT).…”