Fault seal risk analysis

What is involved in fault seal risk analysis and what future requirements can be defined ... 

Fault seal risk analysis and future requirements... 

Fault seal probability analysis is a quantitative method that allows an assessment of the risk of a fault acting either as a barrier to hydrocarbon migration, or as a trapping element within a structure. Fault seal probability is a value ranging from one to zero where a value of one is the highest probability for sealing, and zero is the lowest. This value is derived from the equation that combines the main parameters involved in the formation of fault seal. These parameters, fault displacement, connectivity, and net to gross ratio, are related to the processes of cataclasis and cementation, juxtaposition, and shale smear. The parameters, their measurement and impact on fault seal, are discussed below. 

This paper has highlighted that a number of components, important to fault seal analysis, are often either not included or not quantified in sufficient detail to allow a low risk seal evaluation. The main components which are not always considered in detail are (i) the errors in throw patterns which arise from seismic resolution and fault damage zone structures (ii) the assumption that juxtaposition of reservoir against low permeability units and shale smear are the only sealing mechanisms and (iii) that fault seal data from anywhere is directly applicable to any other sealing problem, i.e., that the geohistory is not critical... 

Despite the common assumption of fault sealing in hydrocarbon fields, very few faults have been characterised in the detail needed which allows identification of the sealing mechanism or controls. Without the construction of a robust set of case histories from such analysis, future seal evaluation will remain a high risk venture. These case histories are also needed to integrate seal behaviour with pressure test, production and in situ stress analysis. The paper has highlighted the importance of an integrated approach from micro to macro and stressed the value of core-based studies to quantify fault rock properties, sub-seismic fault populations and sealing mechanisms. 

The hydraulic properties of faults determine whether they act as migration barriers or pathways across the region. Fault seal analysis was applied, therefore, to predict the degree of fault seal across the area and hence define migration pathways and also to risk trap integrity. The fault seal analysis is also used to explain earlier well results and to calculate likely hydrocarbon column heights in undrilled prospects. 

Another example of a seal with an often unpredictable continuity is one formed by diagenetic alteration of fault rocks. Should an area be characterized by such unpredictable processes, it must be risked high, and one can only resort to an empirical black box approach to fault seal analysis. 

Fig. 1. Simplified evaluation strategy for top seal assessment. The flow chart begins by determining if faults throws are greater than the top seal thickness. If so, then a fault seal analysis is an additional requirement. Top seals are simplified into three main types (1) massive shale, (2) layered shale/sand/silt, and (3) massive strata of other coarser grained lithologies. Key top seal risks and the data required to carry out their assessments are shown in the flow chart. The rectangles represent leakage scenarios and the ellipses indicate data which will contribute to analysis of the scenarios (abbreviations Fluid P, formation fluid pressure <5 hor, minimum horizontal stress Entry P, capillary entry pressure HC prop s, hydrocarbon physical properties, including wetting characteristics).

Fig. 7. Fault assisted top seal leakage, (a) Probability of top seal leakage. Analytical solution for shale beds of constant thickness /, in which identical faults of maximum throw are randomly dispersed. This relationship for probability of seal leakage also holds approximately for seals in which the shale layers and fault throws are each normally distributed about the same mean t. (b) Determination of the throw-cumulative frequency relationship. Faults in a volume of rock, from a map-based statistical analysis of the fault population. Adding 1 to the slope C2 simulates the addition of the third dimension (Gauthier and Lake, 1993). Here a length/Tfnjx fst o 100 1 was used, (c) Determination of the seal risk. Comparing the number of faults required for leakage with the number of faults in the trap volume determines the seal risk. In the example shown, the probability that the seal is breached lies between 50 and 90%, For points in the sealed field, the effect of increasing fault throw on the number of faults needed for breaching is illustrated.

The analysis presented in the paper has highlighted the need to integrate data sets from different scales into a seal analysis (e.g., Leveille et al., 1996). Fig. 18 reviews the four critical factors needed from the different scales. These include (i) data on the 3D sediment architecture (ii) the petrophysical properties of the fault rocks present (iii) the architecture of individual fault zones and (iv) the fault array evolution. It is the combined resolution and characterisation level of each of these which defines the risk level of the seal analysis. There is an important geohistory component in each of these factors. This emphasises the problems associated with transferring data or results from areas with different geohistories, with-out consideration of the different geohistories involved. 

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