Fault-seal analysis using a stochastic multifault approach

Reservoir compartmentalization: an introduction

“…see worked 'real field' examples in Jolley et al 2007a, b). Approaches such as the 'stochastic multi-fault' method (James et al 2004;Corona et al), and Reservoir Connectivity Analysis (RCA, Vrolijk et al 2005;Richards et al) emphasize the control of the basic fluid pressure 'plumbing' of the reservoir system on compartmentalization behaviour. Whilst many methodologies have been proposed for estimating the fluid flow properties of faults over geological time-scales (e.g.…”

“…Whilst many methodologies have been proposed for estimating the fluid flow properties of faults over geological time-scales (e.g. Allan 1989; Knipe et al 1997;Yielding et al 1997;James et al 2004), few studies are published that discuss the success of these methodologies. The paper by Corona et al is therefore refreshing in that as well as describing a methodology for assessing the sealing capacity of faults, it also provides statistics as to how successful the methodology has been when applied to a range of 'real field' examples.…”

Structurally complex reservoirs: an introduction

“…In these circumstances, the faults are detrimental to flow, acting as baffles or barriers within a generally more permeable host rock sedimentary sequence (e.g. Knipe 1993;Downey 1994;Knipe et al 1997, Yielding et al 1997Jones et al 1998;Manzocchi et al 1999Manzocchi et al , 2002Hesthammer & Fossen 2000;Brown 2003;James et al 2004). Issues such as the primary connectivity of reservoir units will also impact the behaviour of the flow system.…”

“…These methods are based on explicit modelling of reservoir and non-reservoir juxtapositions and the sealing properties of fault rocks. However, James et al (2004) suggest that static fault seals are controlled exclusively by juxtaposition, and they describe a stochastic approach to fault seal analysis, which models variation of stratigraphic stacking across a fault to assess its hydrocarbon retention capacity. An energetic debate has since developed on the conference circuit between proponents of these two radically differing approaches.…”

“…An energetic debate has since developed on the conference circuit between proponents of these two radically differing approaches. Dee et al use the data presented by James et al (2004), in order to compare and contrast the results that are achieved by these two radically different methods on the same dataset. They compare the stochastic analysis with a standard SGR-based approach and suggest that despite the conceptual differences between the deterministic and stochastic methods, the results are remarkably similar.…”