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Evaluating a 2-D Structural Restoration: Validating Section Balance

Abstract

Dahlstrom (1969) introduced the power of 2D balanced section construction for making more accurate predictions of subsurface trap geometry in the Foothills of the Canadian Rocky Mountains. Early efforts relied on hand-drafted bed-length conservation between the folded and faulted sedimentary layers of a cross-section interpretation (deformed state) and the flat-lying layer-cake geometry of its restoration (restored state). Today, computer-assisted section construction and restoration software allows the assessment of more complicated structural interpretations by applying a number of methods for forward and inverse strain transformation. While software greatly increases the speed and precision with which the unfolding of folds and the juxtapositioning of fault cut-offs can be made, the validity of material balance requires quantitative analysis beyond a visual inspection between deformed and restored state. In this work, we will review the common methods of inverse strain transformations (i.e. restoration) and common pitfalls found in some published restorations: 1) depending upon the geological setting being analyzed, some transformation methods are more appropriate than others; 2) for some settings, the extant software-based transformations (mostly simple-shear methods) may be poor approximations for the observed deformation; 3) restorations showing restored arrays of multiple fault blocks are rarely seamless, as fault trace mismatches (gaps & overlaps) between hanging-wall (HW) and footwall (FW) are present in nearly every restoration of a structural profile derived from real data. Most authors of restorations “cosmetically” remove the small gaps and overlaps between juxtaposed fault blocks. We emphasize that tables listing the line-lengths of key horizons and the areas of key units should be shown in order to describe the quality of balance. Three published restorations (contractional, extensional, salt diaper) are analyzed to illustrate the utility of quantitative validation.