Changes

In structurally simple fields, the main control on production behavior is the distribution of lithofacies. In structurally complex fields, faults and fractures provide major elements influencing production performance. This chapter discusses the data used to establish the presence of faults and how faults are mapped for reservoir models. The reservoir structure can be analyzed at two different scales: the seismic scale and the well scale. The interpretation of faults and structure at the seismic scale is made by the seismic interpreter whereas the production geologist analyzes the structures from core and log data. Having established a fault framework for a field, it is important to know whether or not fluid flow communication occurs across the faults. Techniques are available to predict the likelihood of this. Sometimes sealing faults break down and open up to flow after a field has been producing for a few years. This reflects the change in the stress state of the reservoir as a result of pressure depletion.

In structurally simple fields, the main control on production behavior is the distribution of lithofacies. In structurally complex fields, faults and fractures provide major elements influencing production performance. This chapter discusses the data used to establish the presence of faults and how faults are mapped for reservoir models. The reservoir structure can be analyzed at two different scales: the seismic scale and the well scale. The interpretation of faults and structure at the seismic scale is made by the seismic interpreter whereas the production geologist analyzes the structures from core and log data. Having established a fault framework for a field, it is important to know whether or not fluid flow communication occurs across the faults. Techniques are available to predict the likelihood of this. Sometimes sealing faults break down and open up to flow after a field has been producing for a few years. This reflects the change in the stress state of the reservoir as a result of pressure depletion.

[[file:M91Ch6FG47.JPG|thumb|300px|{{figure number|1}}Seismic line and equivalent interpretation through the Penguin C South field, UK North Sea (from Dominguez, 2007). Reprinted with permission from the Geological Society.]]

[[file:M91Ch6FG47.JPG|thumb|300px|{{figure number|1}}Seismic line and equivalent interpretation through the Penguin C South field, UK North Sea (from Dominguez<ref name=Dominguez_2007>Dominguez, R., 2007, Structural evolution of the Penguins cluster, UK northern North Sea, in S. J. Jolley, D. Barr, J. J. Walsh, and R. J. Knipe, eds., Structurally complex reservoirs: Geological Society (London) Special Publication 292, p. 25–48.</ref>). Reprinted with permission from the Geological Society.]]

==Seismic interpretation of faults==

==Seismic interpretation of faults==

Offshore, hydrocarbon columns up to 200 m (656 ft) thick are found within compartments interpreted as being sealed by clay smears along faults. The general observation is that the blanket of clay smear along faults only appears to be continuous and effective where the shale content of the displaced section exceeds 25%. The shale smear factor was estimated for faults from two of the fields in the basin. SSF values of between 1 and 4 were found for faults with throws more than 150 m (492 ft) that sealed the longest hydrocarbon columns. It was concluded that faults in this area could be modeled as sealing along their length provided the SSF did not exceed a value of 4.

Offshore, hydrocarbon columns up to 200 m (656 ft) thick are found within compartments interpreted as being sealed by clay smears along faults. The general observation is that the blanket of clay smear along faults only appears to be continuous and effective where the shale content of the displaced section exceeds 25%. The shale smear factor was estimated for faults from two of the fields in the basin. SSF values of between 1 and 4 were found for faults with throws more than 150 m (492 ft) that sealed the longest hydrocarbon columns. It was concluded that faults in this area could be modeled as sealing along their length provided the SSF did not exceed a value of 4.

[[file:92

[[file:M91Ch13FG92.JPG|thumb|300px|{{figure number|14}}Comparison between (a) depth-converted seismic interpretation from the Gullfaks field, Norwegian North Sea, and (b) a plaster model deformed by plane strain extension. The plaster model shows that many small-scale faults are expected to exist in the Gullfaks structure but are below seismic resolution (from Fossen and Hesthammer, 1998). Reprinted with permission from the Geological Society.]]

==Subseismic faults==

==Subseismic faults==

Only the faults that the geophysicist can pick from seismic data will be mapped, that is, those faults with vertical displacements down to the limit of seismic resolution. As mentioned in chapter 6, this can be about 20–40 m for reservoirs at moderate depths. However, a significant number of subseismic faults will probably be present with vertical displacements less than this (Figures 92, 93). Thus, the true degree of the structural complexity of a reservoir will be underrepresented.

Only the faults that the geophysicist can pick from seismic data will be mapped, that is, those faults with vertical displacements down to the limit of seismic resolution. As mentioned in chapter 6, this can be about 20–40 m for reservoirs at moderate depths. However, a significant number of subseismic faults will probably be present with vertical displacements less than this ([[:file:M91Ch13FG92.JPG|Figure 14]], [[:file:M91Ch13FG93.JPG|Figure 15]]). Thus, the true degree of the structural complexity of a reservoir will be underrepresented.

[[file:93

[[file:M91Ch13FG93.JPG|thumb|300px|{{figure number|15}}Fault maps of the East Pennine coalfield, United Kingdom. In map (a), only faults with throws of 20 m (64 ft) or more are shown. These are equivalent to faults that are detectable by seismic surveys at reservoir depths. In map (b), every mapped fault is shown, with fault throws of between 10 cm (4 in.) and 180 m (590 ft) (from Watterson et al., 1996). Reprinted with permission from the Journal of Structural Geology.]]

It is possible to input subseismic faults into a reservoir model using stochastic methods (Munthe et al., 1993; Hollund et al., 2002). Stochastic modeling is described in more detail in chapter 19 of this publication. In summary, this is a computerized procedure for randomly inserting shapes representing geological features into a 3-D model while still honoring predefined rules and statistics controlling the global distribution of the data.

It is possible to input subseismic faults into a reservoir model using stochastic methods (Munthe et al., 1993; Hollund et al., 2002). In summary, this is a computerized procedure for randomly inserting shapes representing geological features into a 3-D model while still honoring predefined rules and statistics controlling the global distribution of the data.

The first part of the method involves making an estimate of the number of subseismic faults by extrapolating from statistics on the length versus frequency of known seismic faults into the subseismic region. Fractal analysis has been used on the assumption that fault-size populations approximate to fractal distributions (Gauthier and Lake, 1993). Statistics are also compiled on fault orientations, length to throw ratios, and fault densities per square kilometer. A further step is to determine those areas of the field where subseismic faults are more likely to be present than elsewhere. One method is to predict the paleostrain regime of the reservoir at the time of faulting (Maerten et al., 2006). On this basis, a model will be made, which will include both the seismic and subseismic faults. Fault seal analysis can be applied to the subseismic faults in the model to determine whether they are sealing or not.

The first part of the method involves making an estimate of the number of subseismic faults by extrapolating from statistics on the length versus frequency of known seismic faults into the subseismic region. Fractal analysis has been used on the assumption that fault-size populations approximate to fractal distributions (Gauthier and Lake, 1993). Statistics are also compiled on fault orientations, length to throw ratios, and fault densities per square kilometer. A further step is to determine those areas of the field where subseismic faults are more likely to be present than elsewhere. One method is to predict the paleostrain regime of the reservoir at the time of faulting (Maerten et al., 2006). On this basis, a model will be made, which will include both the seismic and subseismic faults. Fault seal analysis can be applied to the subseismic faults in the model to determine whether they are sealing or not.

General experience with inserting subseismic faults into simulation models is that they will influence the flow behavior (Damsleth et al., 1998; England and Townsend, 1998; Ottesen et al., 2005). The critical feature seems to be whether the faults are sealing or not. Sealing faults can create an open framework of short baffles, which helps to improve sweep. The baffles increase the tortuosity of the flood front and delay water breakthrough. A large number of sealing subseismic faults in a reservoir will, on the other hand, create numerous dead ends, which will reduce the sweep efficiency of a waterflood. Nonsealing subseismic faults form cross-fault juxtapositions, which can improve vertical connectivity and enhance sweep.

General experience with inserting subseismic faults into simulation models is that they will influence the flow behavior (Damsleth et al., 1998; England and Townsend, 1998; Ottesen et al., 2005). The critical feature seems to be whether the faults are sealing or not. Sealing faults can create an open framework of short baffles, which helps to improve sweep. The baffles increase the tortuosity of the flood front and delay water breakthrough. A large number of sealing subseismic faults in a reservoir will, on the other hand, create numerous dead ends, which will reduce the sweep efficiency of a waterflood. Nonsealing subseismic faults form cross-fault juxtapositions, which can improve vertical connectivity and enhance sweep.

[[file:94

[[file:M91Ch13FG94.JPG|thumb|300px|{{figure number|16}}Reservoir intervals thicken markedly across growth faults. They are common in areas with thick delta sequences and mobile substrates such as shale or salt. This example is from Upper Triassic deltaic sediments exposed in the coastal cliffs of Svalbard (from Edwards, 1976).]]

==Growth faults==

==Growth faults==

Growth faults are faults that were active at the same time as the sediments were being deposited (Figure 94). Many show a listric geometry with the fault soling out into shale horizons. They are common in areas with thick delta sequences. Growth fau lts can be recognized because sediments thicken into the hanging wall of a growth fault and the throw of the fault increases with depth. All the individual reservoir units may thicken up across a mapped growth fault. Alternatively, growth can be taken up by additional layers filling the accommodation space in the hanging wall (Hodgetts et al., 2001).

Growth faults are faults that were active at the same time as the sediments were being deposited ([[:file:M91Ch13FG94.JPG|Figure 16]]). Many show a listric geometry with the fault soling out into shale horizons. They are common in areas with thick delta sequences. Growth faults can be recognized because sediments thicken into the hanging wall of a growth fault and the throw of the fault increases with depth. All the individual reservoir units may thicken up across a mapped growth fault. Alternatively, growth can be taken up by additional layers filling the accommodation space in the hanging wall (Hodgetts et al., 2001).

==Faults as flow conduits==

==Faults as flow conduits==