Index
223
diminishing effectiveness of, 169
discovery process, 13–16, 18,
25, 30
early phase of, 26, 108, 141
effi ciency, 18, 27, 31, 38, 72–3, 164–5,
170
estimation, history of, 72–3
history, reenacting, 31, 171
process, as characterized by
discovery process model, 26–8,
30, 32–3
risk, 5, 37, 39, 106–7, 111, 114–16,
127, 130, 139, 147, 151
time series, 18, 20, 143, 175
“waves,” 28
facies, 9–10, 18–19, 107, 109–12,
114–15, 130, 137–8, 140
distribution, 14
front, 10, 18
wedge, 109–10
feedback mechanism, 6, 17, 27, 141,
149–51, 174–5
fi eld/fi elds, 5, 26, 73, 154–6, 161–4,
167–9
average areal extent of in size
class, 163
defi ned, 5
estimating number of, 73, 161, 169
number of, and relationship to log
hydrocarbon volume, 73
size, 26, 154, 156, 161
total number, in population, 164
undiscovered, 161
fi eld-size distribution, 5, 26, 154, 161,
167, 169
of parent population, 26, 167
inferring parameters of, 26
fi nite population, 3, 5, 12–13, 17, 28,
37, 42–3, 45, 61, 101, 174
statistical approach to, 3–4, 17, 27–33,
51, 72–3, 85, 88, 100, 152, 161–73
fi tting curves and lines, 25, 27, 34–6,
63–70, 73, 81, 88–91, 94, 116–18,
122–4, 126, 139, 144–5, 167–9,
171–2
to assess distribution
assumptions, 88–91
to compute areas, Monte Carlo
approach, 116–19
to empirical distribution, 144–5
to estimate log hydrocarbon volume
and number of fi elds, 73
to extrapolate past exploration
performance, 171–2
to historical data, 171–2
to log fi eld size vs. discovery
number (creaming method
extension), 169
to log-geometric distribution and
observed discoveries, 167
to lognormal distribution, 139
to log probability, 25
to negative exponential, 63–70
to play-resource distribution, Monte
Carlo procedure, 57–8
to pool-size distribution, 27, 34–6
computed by Monte Carlo
procedure, 118–19, 126, 147
impact of negative covariance
on, 122–4
to reserves records, 81
to Weibull distribution, 94
formation, 10–13, 18, 116, 140–41, 143,
146, 158
depth, 140
sandstone porosity values, 11–13
thickness, 103, 137, 147
volume factor, 116, 137, 140
fractal method, 153, 161, 171–3
estimates compared to
superpopulation estimates, 173
frontier play, 6, 132–3, 136–9, 146
probability of existence of, 137
future discovery rate, forecasting, 73,
169, 171–2
gamma distribution, 18, 62, 65, 90–91,
94, 102, 105
density function, defi ned, 62
gas, 11, 19, 26–7, 42–5, 82, 88, 103, 107,
116, 140, 144, 156–9, 167, 169–70,
172
booked reserves, 80–85
composition, 140
fi eld distribution, 167, 169
formation volume factor, 116, 137,
140
marketable, 19, 140, 172
oil-equivalent volume, 43
play, 11, 19, 21, 39, 42, 44, 80–85,
91–3, 99–100, 103, 111, 146–8,
170–73
window, 81–5, 107, 159–61
gas/oil reserves, appreciation and/or
depreciation of, 83–4
gas/oil volumes, natural logarithms
of, 44
geo-anchored method. See Chen and
Sinding–Larsen
223
diminishing effectiveness of, 169
discovery process, 13–16, 18,
25, 30
early phase of, 26, 108, 141
effi ciency, 18, 27, 31, 38, 72–3, 164–5,
170
estimation, history of, 72–3
history, reenacting, 31, 171
process, as characterized by
discovery process model, 26–8,
30, 32–3
risk, 5, 37, 39, 106–7, 111, 114–16,
127, 130, 139, 147, 151
time series, 18, 20, 143, 175
“waves,” 28
facies, 9–10, 18–19, 107, 109–12,
114–15, 130, 137–8, 140
distribution, 14
front, 10, 18
wedge, 109–10
feedback mechanism, 6, 17, 27, 141,
149–51, 174–5
fi eld/fi elds, 5, 26, 73, 154–6, 161–4,
167–9
average areal extent of in size
class, 163
defi ned, 5
estimating number of, 73, 161, 169
number of, and relationship to log
hydrocarbon volume, 73
size, 26, 154, 156, 161
total number, in population, 164
undiscovered, 161
fi eld-size distribution, 5, 26, 154, 161,
167, 169
of parent population, 26, 167
inferring parameters of, 26
fi nite population, 3, 5, 12–13, 17, 28,
37, 42–3, 45, 61, 101, 174
statistical approach to, 3–4, 17, 27–33,
51, 72–3, 85, 88, 100, 152, 161–73
fi tting curves and lines, 25, 27, 34–6,
63–70, 73, 81, 88–91, 94, 116–18,
122–4, 126, 139, 144–5, 167–9,
171–2
to assess distribution
assumptions, 88–91
to compute areas, Monte Carlo
approach, 116–19
to empirical distribution, 144–5
to estimate log hydrocarbon volume
and number of fi elds, 73
to extrapolate past exploration
performance, 171–2
to historical data, 171–2
to log fi eld size vs. discovery
number (creaming method
extension), 169
to log-geometric distribution and
observed discoveries, 167
to lognormal distribution, 139
to log probability, 25
to negative exponential, 63–70
to play-resource distribution, Monte
Carlo procedure, 57–8
to pool-size distribution, 27, 34–6
computed by Monte Carlo
procedure, 118–19, 126, 147
impact of negative covariance
on, 122–4
to reserves records, 81
to Weibull distribution, 94
formation, 10–13, 18, 116, 140–41, 143,
146, 158
depth, 140
sandstone porosity values, 11–13
thickness, 103, 137, 147
volume factor, 116, 137, 140
fractal method, 153, 161, 171–3
estimates compared to
superpopulation estimates, 173
frontier play, 6, 132–3, 136–9, 146
probability of existence of, 137
future discovery rate, forecasting, 73,
169, 171–2
gamma distribution, 18, 62, 65, 90–91,
94, 102, 105
density function, defi ned, 62
gas, 11, 19, 26–7, 42–5, 82, 88, 103, 107,
116, 140, 144, 156–9, 167, 169–70,
172
booked reserves, 80–85
composition, 140
fi eld distribution, 167, 169
formation volume factor, 116, 137,
140
marketable, 19, 140, 172
oil-equivalent volume, 43
play, 11, 19, 21, 39, 42, 44, 80–85,
91–3, 99–100, 103, 111, 146–8,
170–73
window, 81–5, 107, 159–61
gas/oil reserves, appreciation and/or
depreciation of, 83–4
gas/oil volumes, natural logarithms
of, 44
geo-anchored method. See Chen and
Sinding–Larsen