011 - the static model, hydrocarbons in place
TRANSCRIPT
7/23/2019 011 - The Static Model, Hydrocarbons in Place
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Network of Excellence in Training
The Static Model
Hydrocarbons–in–place
7/23/2019 011 - The Static Model, Hydrocarbons in Place
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Network of Excellence in Training 19/12/15 Slide 2
How much have we found?How much have we found?
N – STOIIP Stock Tank Oil Initially In Place
– GIIP
as Initially In Place
ross !ock "olume containin# the oil $ !" m%& ft%&acre ft
'(mount of )#ood* reservoir – net to #ross ratio NT+
'(mount of void in the rock $ porosity +
'(mount of oil in the void – hydrocarbon saturation So +
',actor relatin# reservoir to surface volume of the oil-#as–,ormation "olume ,actor ,", +
'conversion factor to bbl or scf or sm%
N = GRV*NTG*
*So*FVF*C
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Network of Excellence in Training 19/12/15 Slide 3
Data SourcesData Sources
Spatial data:
GRV: maps prepared from seismic and well data define the reservoir envelope and the fluid contacts
FVF: the proper! term is "# This is determined from representative
reservoir fluid samples from wireline samplers$ DSTs and well production tests
Point source data %wells&: %or crudel'$ areal distri(ution from )D and *Dseismic data sets&
: core data and the famil' of porosit' +OGS
So: the families of Resistivit' +OGS
,TG: core data and a variet' of +OGS
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Network of Excellence in Training 19/12/15 Slide 4
-.IIP Methods:-.IIP Methods:
Area-DepthDeterministicProbabilistic
DeterministicEqi!alent "il Colmn#nitialisation o$ Reser!oir Simlator
%aterial &alance Eqation'hen () +C##P pro,ce,
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Network of Excellence in Training 19/12/15 Slide 5
ED Ser!ices
Volmetric Constrction
AreaDepth
&. Reser!oir
Depth/ m
Area/ 0m1
.222
..22
.122
.32 132 432
5
5
5
&V 6oil7= 683.-23971=.3:)*.29m
4
NG = 239
; = 231)
So = 239
.&o = 23<
ST"##P = 14 .2<m
4* :31< = .)2 % bbl
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Network of Excellence in Training 19/12/15 Slide 6
/rea depth deterministic/rea depth deterministic
Reservoir structure mapMeasure succeedin0 closed contour areasPlot a0ainst depth/dd fluid contact depths
h
area
0oc
owc
1ei0ht avera0e reservoir thic2ness-an0 (elow area lineMeasure volumes enclosed %0ives GRV&
0oc
owc1ei0ht avera0e petroph'sical data
/ppl' to GRV$ appl' FVF
'ields -.IIP
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Network of Excellence in Training 19/12/15 Slide 7
34/,TIFI./TIO, of 4,.5RT/I,T634/,TIFI./TIO, of 4,.5RT/I,T6The pro(a(ilistic approachThe pro(a(ilistic approach
%the actual data is 7 89%the actual data is 7 89;; < of the whole&< of the whole&
Gross roc2 volume4suall' the ma=or uncertaint'Pro(lems are mainl' seismolo0ical: the pic2$ vertical and hori>ontal resolution$timedepth conversion$ particularl' if fault 0eometr' controls trap# Fluid contacts are
usuall' 2nown#
Two approaches: "' ta2in0 seismic uncertaint' into account? Geostatisticall' 0enerate man' structural
maps and esta(lish GRV apparent distri(ution
Generate most reasona(le! minimum and ma@imum maps to accompan' the mostli2el'! and (e 0uided (' D-Is if present
,5V5R add plusAminus percenta0e
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Network of Excellence in Training 19/12/15 Slide 8
Seismic 4ncertaint'Seismic 4ncertaint'
velocit' error
timin0 error
pic2 error
mi0ration error
cali(ration
error
The main uncertaint' is in time to depth conversion
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Network of Excellence in Training 19/12/15 Slide 9
tA> on flan2Bon crestB
fault positionB
fault dipB
shale thic2ness ,:GB Most +i2el' PC9
Most reasona(le minimum: PC
Most reasona(le ma@imum: P8C
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Network of Excellence in Training 19/12/15Slide 10
Inherent 4ncertaint' in Data Inherent 4ncertaint' in Data %0enuine EA&%0enuine EA&
thic2ness %lo0s&: 8<
porosit' %lo0s&: 899<
porosit' %core&: C89<
saturation %lo0s&: 89C9<
saturation %pc&: C8C<saturation %o(c&: C8C<
net to 0ross: BBB
FVF %PVT&: C89<
FVF %charts&: 89)9<
For porosit' %saturation and ,:G& there will (e a 0enuine distri(utionaround the field$ or a field analo0ue: use it$ (ut ,5V5R use the %vertical&
distri(ution from one well# .ommonl' there is onl' one PVT anal'sis$
use EA 89<
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Network of Excellence in Training 19/12/15Slide 11 ED Ser!ices
E5pectation cr!e constrction
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Network of Excellence in Training 19/12/15Slide 12 ED Ser!ices
Volmetric ncertaint> 1
$
23. ; 234
&VSo
NG
$
)2 ST"##P 422
%onte Carlo
p
)2 ST"##P 422
2
2
.22
42
E5pectation Cr!e
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Network of Excellence in Training 19/12/15Slide 13 ED Ser!ices
E5pectation Cr!es
C m l a t i ! e
p r o b a b i l i t >
2
.22
ST"##P in %bbls
.)
9)
)2
?o' %e,im +i@h
A$ter appraisal