Fault seal mapping – incorporating geometric and property uncertainty

Abstract

In this paper, we present workflows, key relationships and results of multiple stochastic fault seal analyses conducted on geocellular geological or (static) reservoir grids. Ranges of uncertainties are computed from new and published datasets for the different input relationships (e.g. throw, VShale to VClay, fault clay prediction, fault rock clay content to permeability); these are used as input into stochastic modelling processes and the impact of each is assessed. The power of stochastic modelling to focus interpretation and risking effort is reviewed. Reducing the uncertainty distributions from the published data ranges has a massive impact on the range of predicted fault seal properties. Halving the uncertainties associated with the computation of the transmissibility multiplier, for instance, reduces this range from 7 to 1-1.5 orders of magnitude of the base-case value (no uncertainty). Importantly, when combined together, the median predictions from each individual parameter do not lead to the median value for the final prediction; average relationships combined together will not therefore produce the average final prediction. This is a powerful result for two reasons: first, current geological modelling packages use global trends to define fault properties and so are likely to predict spurious results; and secondly, reducing the uncertainty on specific relationships by around 50% is an achievable goal. Locally calibrated datasets and relationships (field-specific) based on carefully characterized samples should allow for this improvement in prediction accuracy. This paper presents a review of fault seal techniques, published data and the potential pitfalls associated with the analyses.Incorporating uncertainty during fault seal analysis via stochastic 3D modelling has the potential to rapidly identify critical high-risk seal or flow zones. The result should be more accurately risked prospects or field geological models. Simple uncertainty incorporation techniques, such as varying throw and clay smear, combined with the computation of the distribution of probable reservoirreservoir cross-fault juxtaposition windows, are very powerful, but are currently unavailable in most commercial reservoir geological modelling packages. Utilizing these techniques has the potential to improve the accuracy of predictions. In this contribution, we outline workflows to allow uncertainty to be incorporated into fault seal analyses conducted directly on geocellular geological or reservoir models (e.g. pillar-based grids).Stochastic multiple realization techniques are widely implemented in reservoir geological and property modelling processes (Handyside et al. 1992) but are currently under-utilized in fault seal predictions (e.g. James et al. 2004). The strength of stochastic approaches is in the analysis and prediction of results where the key relationships have significant natural variability. Fault morphology and fault rock properties certainly fall within this category (e.g.In systems which are known to vary significantly...

Cross-fault sealing, baffling and fluid flow in 3D geological models: tools for analysis, visualization and interpretation

“…The data also indicate that a range of other factors can influence those relationships; these include burial history (e.g. Sperrevik et al 2002;Freeman et al 2008) and the timing of hydrocarbon migration. With this array of valid but potentially different relationships, it is important to be able to differentiate the most appropriate ones to apply in a given situation, or alternatively to assess what effect selecting different relationships will have on the predicted flow behaviour.…”

“…Yielding 2002) or more commonly as a step toward defining the likely cross-fault permeability, and ultimately the fault TMs for input to flow simulation (e.g. Manzocchi et al 1999Manzocchi et al , 2008Sperrevik et al 2002;Jolley et al 2007;Freeman et al 2008). Fault permeabilities and TMs along the fault surface can then be viewed as values for each cross-fault grid connection (e.g.…”

“…Currently only a limited suite of these algorithms are available in most commercial geological modelling packages, but the varying impact that they can have on the resulting flow simulation is significant (e.g. Freeman et al 2008). Furthermore, it is not sufficient to only implement the algorithms, as the associated visualization capabilities are also required if the geoscientist or reservoir engineer is to be able to understand or make informed choices on the influence of modifying the spatial variability of these properties.…”

“…Manzocchi et al 1999Manzocchi et al , 2008Sperrevik et al 2002;Jolley et al 2007). The majority of published datasets suggest a significant scatter in the nature of the critical parameters (Hull 1988;Childs et al 1997;Knipe et al 1997Knipe et al , 1998Sperrevik et al 2002;Jolley et al 2007;Freeman et al 2008;Manzocchi et al 2008). The data also indicate that a range of other factors can influence those relationships; these include burial history (e.g.…”

Improved Implementation of Fault Seal Analysis in Reservoir Simulation

“…The effective crossfault transmissibility (ECFT) is one potential solution (see Figure 1). This property is the total transmissibility of the host rock on one side of the fault, the fault rock and the host rock on the other side of the fault, all normalized to a constant length scale (Freeman et al, 2008). For the same pressure differential, mobility and phase there should be a linear relationship between the ECFT and the fluid flow across the fault.…”