IDENTIFYING THE AMOUNT AND TIMING OF LAYER PARALLEL SHORTENING IN COMPRESSIVE REGIONS USING THIN-SECTIONS AND ANALOG MODEL

Layer parallel shortening (LPS) is known to be a process occurring during deformation of a region under an applied compressive stress. LPS is thought to occur before the development of major structures such as folds or faults and is generally taken up by volume change within the beds, resulting in structures such as pressure-solution cleavage, reduction of porosity and potential stylolite development on the bed scale, or pressure solution and deformation of grain boundaries on the grain scale. Since much of the deformation related to LPS is taken up on the grain scale, the actual amount of LPS is difficult to quantify in the field or from map data. Thus, in constructing a balanced and restored cross-section, an element of the deformation is unaccounted for. As a result, any restored cross-section and the deformation amounts, timing and hydrocarbon-in-place estimates calculated from this section may be fundamentally flawed.

Various authors have placed the amount of LPS within the range of 5-20% initial shortening, indicating that the cross-sections created may have up to 20% error within them. This study presents a methodology using samples collected from the Teton Anticline, Sawtooth Range, Montana, indicating that the timing of LPS can be reliably inferred from dip-parallel thin-sections and polished slabs. Initial analog modeling results by the PI indicate that LPS also varies with depth in the deforming system, such that LPS is greatest near the base of a deforming sediment system, and that although most LPS occurs in early deformation stages, LPS continues to occur throughout the deformation sequence.

These flaws and the flawed interpretations based on inaccurate cross-sections are likely to propagate through an entire research or exploration sequence. Given an interpretation based on a flawed model (lacking quantified LPS) the errors may propagate through the entire exploration sequence, resulting in poor drilling decisions and lower than optimum recovery rates for a given field. If these flaws can be removed, then improved interpretations of sub-surface structures are expected, leading to scientifically sound drilling decisions and improved recovery rates.