Geology Reference
In-Depth Information
Table 10.2.
Detailed reservoir scorecard for assessment of the feasibility of time lapse seismic (after Lumley et al.,
1997
)
Reservoir scorecard
Score
5
4
3
2
1
0
Dry bulk modulus
Gpa
<
3
3
-
5
5
-
10
10
-
20
20
-
30
30+
Fluid compressibility contrast
% change
250+
150
-
250
100
-
150
50
-
100
25
-
50
0
-
15
Fluid saturation change
% change
50+
40
-
50
30
-
40
20
-
30
10
-
20
0
-
10
Porosity
%
35+
25
-
35
15
-
25
10
-
15
5
-
10
0
-
5
Predicted impedance change
% change
12+
8-12
4-8
2-4
1-1
0
Travel-time change
#samples
10+
6-10
4-6
2-4
1-2
0
too conservative. Marsh et al.(
2003
) present a sim-
pler ranking tool based on practical experience of
time-lapse projects, in which the normal incidence
reflectivity of a notional contact is referenced against
different acquisition and processing strategies.
Following the initial screening phase, more
detailed modelling is also carried out to evaluate
whether the production effects can be seen against
the noise background with a level of detail that will
be of any use to the reservoir engineer. Models for
various production scenarios would typically include
modelled gathers based on well logs as well as 2D
models. However, in order to address issues such as
lateral sweep efficiency it is common for the reservoir
simulation to be used to generate a 3D model. This
type of approach is time consuming, requiring a
detailed rock physics model for both reservoir and
non-reservoir units and a consideration of how to
address differences in scale between geological and
reservoir models.
generally higher in basins where DHI recognition is
possible (e.g. Rudolph,
2001
).
In practice, both geological and DHI risking are
undertaken. The DHI evidence can be used to modify
individual risking elements, such as the risk on hydro-
carbon migration, or to condition the overall risk (e.g.
Roden et al.,
2005
; Forrest et al.,
2010
) or indeed it may
be used to override the geological risk altogether. The
process, however carefully prescribed, is often subject-
ive; two different interpreters may not assess the sig-
nificance of the observations in exactly the same way.
It is also not free of an emotive element; using the label
'
may imply more certainty of hydrocarbon pres-
ence and a much narrower range of possible outcomes
than is warranted (Citron and Rose,
2001
).
Clearly, amplitude related observations need to be
subjected to a rigorous evaluation before assigning
significance in terms of risk. This will include an
assessment of the validity of a DHI interpretation as
well as evaluating the play and risking context. It is
often overlooked that DHI evaluations are to some
degree dependent on the knowledge of the play. The
interpreter who has been working with seismic ampli-
tudes in a basin for several years is perhaps more likely
to recognise what is and what is not a DHI more
accurately than an interpreter who is new to the basin.
DHI
'
10.5 Amplitudes inprospect evaluation
Traditionally, the risk (or chance of success) on a
hydrocarbon prospect is determined by identifying
the probability of there being an effective trap, with
a reservoir which has been charged by hydrocarbons
migrating from a mature source rock. Thus there are
numerous geological elements which need to be
evaluated both separately and together as part of the
petroleum system. The presence of reliable seismic
indications of the presence of hydrocarbon in the
seismic (i.e. a DHI), can suggest, however, that all
the individual components are present and the risking
process becomes focussed on the validity of the DHI.
It is well documented that drilling success rates are
10.5.1 An interpreter
'
s DHI checklist
A checklist questionnaire is a useful tool in checking
the validity of a DHI and commonly forms the basis
of a
(Roden et al.,
2012
). an example of
such a questionnaire is shown in
Table 10.3
. These
types of questions can be arranged into a scorecard
for the purpose of creating a DHI risk.
A simple approach to guide a DHI risking exercise
is to use a play specific success matrix (e.g. Citron and
'
DHI Index
'
247
