Article Open Access QUANTITATIVE PETROPHYSICAL EVALUATION AND RESERVOIR CHARACTERIZATION OF WELL LOGS FROM "DATOM" OIL FIELD, NIGER DELTA

Abstract

This paper presents a detailed reservoir characterization of three wells in "Datom" Oil Field, Niger Delta using well logs data. The distributions and thicknesses of sand bodies were determined within each of the wells in the field using interactive petrophysical (IP) software. The quantitative and qualitative analysis were done for the three exploration wells with the depth ranges of 8700-9200ft for Datom North well , 8900-9400ft for Datom West well, and 9000-9500ft for Datom East well. Two distinctive porous sand bodies were identified across the field (A and B), Datom North has it reservoirs as 1A (8815-8903ft) and 1B (9100-9157ft), Datom West has its reservoir as 2A (8996-9095ft) and 2B (9263-9321ft) and Datom East as 3A (9101-9219ft) and 3B (9357-9418ft). Petrophysical evaluation was made from a suite of wire-line logs comprising of gamma ray, resistivity, neutron and density logs of the wells. The average porosity values obtained are in the range of 0.18-0.22 with average net pay permeability values ranging from 322.70mD to 733.20mD. The water saturation obtained for each reservoir unit in combination with the resistivity index was used to prove the presence of hydrocarbon in the sand units. The hydrocarbon saturation of the reservoirs are in the range of 0.6-0.7 across the prospect zones with gas effect of the combination logs of neutron and density indicating the hydrocarbon accumulation is predominantly gas. The average net to gross ratio across the reservoirs (0.7-0.9) is defined using an average porosity (∅) and volume of clay (í µí±‰ í µí±í µí±™í µí±Ží µí±¦) cut offs values of ≥ 0.1 í µí±Ží µí±›í µí±‘ ≤ 0.5 respectively. With a moveable hydrocarbon index (MHI=í µí±† í µí±Š í µí±† í µí±‹í µí±‚ ⁄) less than 0.7 across the sand units, it shows favorable hydrocarbon moveability in the reservoirs. The results clearly revealed that the gas bearing sand units have good reservoir potentials favorable for hydrocarbon production.

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Article Open Access
QUANTITATIVE PETROPHYSICAL EVALUATION AND RESERVOIR CHARACTERIZATION OF WELL LOGS
FROM “DATOM” OIL FIELD, NIGER DELTA
Lawson-Jack Osaki1, and Alexander Ifeanyichukwu Opara2*
1 Rivers State University of Science and Technology, Nkporo, Rivers State, Nigeria
2 Department of Geology, Federal University of Technology, Owerri, Nigeria
Rece ived March 31, 2018; Accepted June 20, 2018
Abstract
This paper presents a detailed reservoir characterization of three wells in “Datom” Oil Field, Niger Delta
using well logs data. The distributions and thicknesses of sand bodies were determined within each of
the wells in the field using interactive petrophysical (IP) software. The quantitative and qualitative ana-
lysis were done for the three exploration wells with the depth ranges of 8700-9200ft for Datom North
well , 8900-9400ft for Datom West well, and 9000-9500ft for Datom East well. Two distinctive porous
sand bodies were identified across the field (A and B), Datom North has it reservoirs as 1A (8815-
8903ft) and 1B (9100-9157ft), Datom West has its reservoir as 2A (8996-9095ft) and 2B (9263-
9321ft) and Datom East as 3A (9101 -9219ft) and 3B (9357-9418ft). Petrophysical evaluation was
made from a suite of wire-line logs comprising of gamma ray, resistivity, neutron and density logs of
the wells. The average porosity values obtained are in the range of 0.18-0.22 with average net pay
permeability values ranging from 322.70mD to 733.2 0mD. The water saturation obtained for each
reservoir unit in combination with the resistivity index was used to prove the presence of hydrocarbon
in the sand units. The hydrocarbon saturation of the reservoirs are in the range of 0.6-0.7 across the
prospect zones with gas effect of the combination logs of neutron and density indicating the hydrocar-
bon accumulation is predominantly gas. The average net to gross ratio across the reservoirs (0.7-0.9)
is defined using an average porosity ( and volume of clay (
  cut offs values of    re-
spectively. With a moveable hydrocarbon index (MHI=
 less than 0.7 across the sand units, it
shows favorable hydrocarbon moveability in the reservoirs. The results clearly revealed that the gas
bearing sand units have good reservoir potentials favorable for hydrocarbon production.
Keywords: Petrophysics; Net-to-Gross; Niger delta; well logs; Porosity; Water and Hydrocarbon Saturation.
1. Introduction
The search for hydrocarbons st arts with a regional knowledge of the prevailing geology in
a geologic basin, where the geologist is in charge of the sedimentary sand deposition. After
the geophysicist c onducts seismic surveys and data processing, risky wildc at exploration wells
may be drilled to t est the best geological and seismic structural model. If a hydrocarbon dis-
covery is made, data must be c ollected to evaluate the scale, quality, and quantity of the
discovery. The resolution of moving an exploration well to c ompletion is depended on its eco-
nomic valiabity. To establish this viability a qualitative and quantit ative analysis of all available
well data is paramount. This analysis carried out at about the midpoint of a critical financial
investment in the field development study will eventually determine whether to proceed with
well completion and incur t he relative cost or otherwise. Unarguably petrophysics plays a sen-
sitive role in the evaluation of well and field potential.
Petrophysics actually c onverts resistivity, gamma ray and porosity tool measurements into
reservoir properties, resistivity and porosity are the single most important measurements
made by c onvectional logging tools and form the foundation on which the entire industry is
built . Petrophysics evaluation combines well log, core, mud log, and other disparate data
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sources for the purpose of analyzing, predicting, and establishing formation lithology and po-
rosity, hydrocarbon saturation, permeability, producibility, and estimating t he economic via-
bility of a well. According t o Asquith and Krygowski [1], well logs are used t o correlate zones
suitable for hydrocarbon accumulation, identify productive zones, determine depth and thick-
ness of zones, distinguish between gas, oil and water in a reservoir and to estimate hydrocar-
bon reserves.
Qualit atively the petrophysical evaluation is centered on translating geophysical responses
to geological parameters, for instance, what nat ural radioactivity means as regard shale con-
tent; how sonic velocity can be interpreted as regard shale compaction; what bulk density
means in terms of mineral composition etc. The ambit of this independent study is limited to
the use of geophysical well log data to ac hieve not only the lithology and fluid type of the
prospect zones but also the average water saturation and the productive capabilities will be
predicted. However, as relevant as log paramet ers are, they should not be applied without the
consultation of other necessary data like drill stem test, mud log evaluation, sample shows,
nearby product ion etc, before taking a decision to drill.
In this st udy therefore, we c arried out petrophysical evaluation and volumet ric estimation
of the “Datom” Field from a suite of wire-line logs comprising of gamma ray, resistivity, neu-
tron and density logs of the wells. The analyses c arried out involved the delineation of lithol-
ogies, identification of reservoirs and fluid types, wells correlation and det ermination of petro-
physical parameters (porosity, hydrocarbon saturation, volume of shale, formation resistivity,
net to gross ratio, water saturation, permeability etc) of the identified reservoirs. The objective
of this study therefore was to carry out a detailed hydrocarbon reservoir characterization of
the “Datom” Field using well log data.
1.1. Location and geology of the study area
The ‘Datom’ Oil Field is located within the central swamp depobelt of Niger delta basin,
Nigeria (Figure 1). Several earlier scholars have presented detailed information on the regional
geology, stratigraphy and st ructure of the Niger delta basin in several key publications [2-10]
.
Niger Delta according to Klett et al. [11] is situated within the Gulf of Guinea with extension
throughout the Niger Delta Province. It is located in the southern part of Nigeria between the
longit ude 40 –90 E and latitude 40-60 N. It is situated on the West African continental margin
at the apex of the Gulf of Guinea, which formed the site of a triple junct ion during c ontinental
break-up in the Cretaceous [12 ].
From t he Eocene to the present, the Niger delta has prograded south-westward, forming
depobelts that represent the most active portion of the delta at each stage of its development
[12]. T hese depobelts form one of the largest regressive deltas in the world with an area of
some 300, 000km2 , a sediment volume of 500,000 km3 and a sediment thickness of over 10
km in the basin depocenter [13]. Niger Delta Province contains only one identified petroleum
system referred to as the Tertiary Niger Delta (Akata –Agbada) Petroleum System [13-14 ].
Extended research by Tuttle et al. [15] confirmed this one petroleum system with the delta,
which was formed at the triple junct ion related to t he opening of the southern Atlantic begin-
ning in the late Jurassic and continuing into t he Cretaceous. The delta began its development
in t he Eocene with the accumulation of sediments that are now about 10 kilometers thick [12-14]
.
The area is geologically a sedimentary basin, and consists of three basic Formations: Akata,
Agbada and the Benin Formations. The Akata is made up of thick shale sequences and it serves
as the potential source rock. It is assumed to have been formed as a result of the transporta-
tion of terrestrial organic matter and c lays to deep waters at the beginning of Paleocene [12]
.
According to Doust and Omatsola. [12] the thickness of this formation is estimat ed to about
7,000 meters thick, and it lies under the entire delta with high overpressure. Agbada For-
mat ion is the major oil and gas reservoir of the delta, It is the t ransition zone and consist of
intercalation of sand and shale (paralic siliciclastics) with over 3700 met er t hick and represent
the deltaic portion of the Niger Delta sequence [13,16]. Agbada Formation is overlain by the top
Format ion, which is Benin. Benin Format ion is made of sands of about 2000m thick [2].
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Fig 1. Map of Nigeria Showing the Location of the Niger Delta and the Base map of Datom oil field with
well locations (well 1,2,3) representing Datom North, Datom East and Datom West respectively (Modi-
fied from Whiteman [16])
2. Methodology
Log analysis, or format ion evaluation was done with Interactive petrophysics (IP) software.
The evaluation requires t he synthesis of logging tool response physics, geological knowledge,
and auxiliary measurements or informat ion t o ext ract the maximum petrophysical informat ion
concerning the subsurface formations. The qualitative and quantitative analyses were c arried
out on t he available petrophysical logs (GR,Resistivity, neutron and Density logs) of the Datom
oil field. While qualitative analysis involves the assessment of reservoir properties, fluid type
from log pattern, quantitative analysis deals with the numerical estimation of reservoir prop-
erties viz; % of gas, oil and water. Empirical formulae were used to estimate the petrophysical
properties of the mapped reservoir units delineated on the well logs.
The first task is to identify the zones with a low- volume frac tion of shale since such zones
(clean zones) are more likely to produce accumulated hydrocarbons. This task has traditionally
been acc omplished through t wo measurements: the gamma ray and combine effect of the
neutron and density log, In the reservoir units, gamma ray (GR) log which measures natural
radioactivity in format ions reflec ts the shale contents while the compensated neutron/density
log was use to validate t he porosity and the lithology both logs were used for the identification
of sand / shale lithology in t he Datom field. T he resistivity log in c ombination with the GR logs
were used to differentiate bet ween hydrocarbon and non-hydrocarbon bearing zones since
hydrocarbon is a nonconductor. The combination of t he neutron and density log further vali-
dates t he sand-shale zones and det ection of gas bearing zones. The reservoir units were fur-
ther characterized quantitatively to arrive at petrophysical parameters, which includes: vol-
ume of shale, formation factor, porosity, water saturation, permeability and so on. Some of
these parameters are discussed.
Gamma Ray Index
The gamma ray log is generally used to determine the gamma ray index using the formula
according to Asquith and Gibson [17 ] as given in equation 1:
IGR = (GRLOG –GRMIN)/(GRMAX –GRMIN) . (1)
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where: IGR =gamma ray index; GRLOG=gamma ray reading of format ion from log ; GRMIN=mini-
mum gamma ray (clean sand); GRMAX= maximum gamma ray (shale).
Volume of shale
The volume of shale was calculated by applying the gamma ray index in the appropriate
volume of shale equation according to Larionov [18] for tertiary rocks as given in equation 2:
Vsh = 0.083[2(3.7 x IGR) – 1.0]… (2)
where: Vsh=volume of shale ,IGR = gamma ray index.
Porosity
The computation of porosity was done in stages, the first involved the use of the Wyllie
equation t o estimat e the density derived porosity (фD), and then the neutron-density porosity
(фN-D), was estimated using the neutron (фN) porosity coupled with the density derived po-
rosity. The Wyllie equation for density derived porosity is given as shown in equation 3 [19]:
фD = (ℓmax- ℓb)/(ℓmax- ℓfluid) (3)
where:ℓmax =density of rock matrix = 2.65 g/cc ; ℓb = bulk density from log; ℓfluid = density of
fluid occ upying pore spaces (0.74g/cc for gas, 0.9g/cc for oil and 1.1 g/cc for water).
The Neutron – Density porosity could be calculated according to The Neutron-Density porosity
could be c alculated using the equation of Hussien et al. [20] as:
фN-D = (фN + фD)/2 for oil and water column (4)
фN-D = (2 фD+ фN)/3 for gas bearing zones… (5)
Formation factor
The estimation of the Formation Factor was achieved using the popular Humble Equation [39]:
F = a/Øm (6)
where, F = formation factor; a = tortuosity factor = 0.62 ; Ø = porosity; m=c ementation
fac tor = 2.15
Formation water resistivity (Ωm)
Using the Archie’s equation that related the formation factor (F) to the resistivity of a for-
mat ion at 100% wat er saturation (Ro) and the resistivity of formation water (Rw), the resis-
tivity of the formation wat er was estimated as:
Rw = Ro/F … (7)
Water saturation
Determination of the water saturation for t he uninvaded zone was achieved using the Archie [21]
equation given.
Sw2 = (F x Rw)/RT (8)
But, F = Ro/Rw (9)
Thus, Sw2 = Ro/ RT (10)
where: Sw = wat er saturation of the uninvaded zone; Ro= resistivity of formation at 100%
water saturation; RT= true formation resistivity.
Hydrocarbon saturation
This was obtained directly by subtracting the percentage of water saturation from 100.
Thus Shy = 1 - Sw rr Shy %= 100 - Sw% (11)
where: Shy is the hydrocarbon saturation (expressed as a fraction or as percentage).
Resistivity Index
This was estimat ed using the ratio of formation true resistivity (Rt) to resistivity of formation
at 100% sat uration (Ro) as given in equation 12:
I = Rt/Ro … (12)
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where: I is the resistivity index. When I is equal to unity, it implies that the reservoir is at
one hundred percent (100%) water saturation, T he higher the value of I, the greater the
percentage of hydrocarbon saturation.
Bulk volume water
Bulk volume of water (BVW) was estimated as the product of water saturation (S w) of the
uninvaded zone and porosity (ØN-D). Thus, the bulk volume of water is shown in equation 13:
BVW = Sw x ØN-D … (13)
where: ØN- D = neutron-density porosity.
Hydrocarbon pore volume
The hydrocarbon pore volume (HCPV) is the fraction of the reservoir volume occupied by
hydrocarbon. This was calculated as the product of neutron-density porosity and hydrocarbon
saturation as shown in equation 14:
HCPV = ØN-D x (1 - Sw) (14a)
HCPV = ØN-D x (Sh) (14b)
Irreducible water saturation
The irreducible water saturation was calculated using the following relationship in equation 15.
However, this theoretical estimate of irreducible water is majorly useful in the estimation of
relative permeability.
= (F/2000)1/2 … (15)
where: = irreducible water saturation; F =formation fac tor.
Permeability
This was based on the relationship between permeability, porosity, and irreducible water
saturation according to Wyllie and Rose [19]. The relationship is expressed in equation 16 as:
K = [(250 x (ØN-D)3)/Swi]2 … (16)
Shaliness (Vsh Total)
This is the total volume of shale represented as a depth factor within a well. It is c alculated
by using equation 17:
Average Vsh x Gross thickness … (17)
Net thickness
This is the c olumn of the reservoir that is occupied by reservoir format ion (e.g. sand) only
and exclusive of non-reservoir formations (e.g. shale). It is calculated by using equation 18:
Gross Thickness – Vsh Total … (18)
Net to Gross ratio (NTG)
This is the ratio between the net reservoir thickness and the gross reservoir thickness.
However in terms of hydrocarbon pay, it c ould be calculated as the ratio between the net pay
thickness and the gross pay t hickness. The four main steps in the application of a net -pay cut
off to a particular reservoir interval are to establish a standard, c alibrate one or more logs to
the chosen standard, confirm that the calibration step produces results consistent with the
standard, and apply the calibrated model to all wells [22-23]. The primary geological consider-
ations in determining pay and non pay in the reservoir interval are depositional environment
and hydrocarbon and structural history. The "net -to-gross ratio" or "net/gross" (N/G) is the
total amount of pay footage divided by the total thickness of the reservoir interval (for sim-
plicity, the well is assumed here to be vertical). The depositional environment provides a pic-
ture of whether the overall reservoir interval is sand rich (high N/G) or shale rich (low N/G)
and the nat ure of the interbedding of high-quality rock with poor-quality rock. If the reservoir
interval is quite interbedded with high-quality roc k intimately layered with poor-quality rock
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on the scale of a few inc hes to a few feet, the poor-quality rock intervals, if t hey contain
hydrocarbons, will likely contribute t o production [24-26 ]. However, if t he layering is on a muc h
larger scale with thick high-quality rock intervals separated from thick low- quality rock inter-
vals, then t he poor-quality rock intervals are muc h less likely to c ontribute significantly to
production [22-26]. The NTG is generally estimated using equation 19:
NTG = Net thickness ÷ Gross Thickness (19)
Effective Porosity
This is t he porosity of the interconnected pore spaces. It assumes the absence of shale
from the reservoir. It can be calculated using the following relationship as shown in equation 20:
Фeffective = (1 – VSHALE) * фN-D (20)
Storage Volume
This is t he capacity to store hydrocarbon in the reservoir. The storage volume is always
higher than the hydrocarbon pore volume within a well because the net pay zone is inc lusive
of the grain matrix whereas t he grain matrix is absent in the hydrocarbon pore volume com-
putation as only the hydrocarbon in the pore spaces is calculated for. The storage volume is
generally estimated using the formula given in equation 21.
Storage Volume = фN-D * Net Pay T hickness … (21)
3. Result interpretation
In this st udy based on t he analysis, two hydrocarbon bearing zones (Reser A and B) were
identified for further interpretation.The sand units (Reser A and B) were delineated as hydro-
carbon bearing sands within the Agbada formation of the field as shown from the correlation
of t hree wells using well logs (Figure 2). The sands were identified to be highly prolific in
hydrocarbon yield and were completely analyzed to estimate their petrophysical parameters.
Increasing trend of the thickness of the shale units with depth indic ate that the sequence is
approaching the Akata Format ion. The parameters deduced from the analysis include gamma
ray index, porosity, net to gross, volume of shale, format ion fac tor, irreducible water satura-
tion, hydrocarbon saturation, water saturation and hydrocarbon pore volume etc. These pa-
rameters help to effectively quantify t he reservoirs.
Datom North
The reservoirs (1A and 1B) of the Datom Nort h well have its top and base at a depth interval
of 8815.50ft - 8903.50ft and 9100ft - 9157.50ft respectively with a gross thickness of 88ft
and 57.50ft, net pay interval of 79.25 and 38ft, N/G are 0.9 and 0.6 .T he average neutron-
density derived porosity for the reservoirs are 20% and 18%, Average water saturations are
0.32 and 0.33 respec tively. The net pay permeability of reservoir 1A and 1B is fair to
good,733mD and 598mD,average wat er of the flushed zone (  is 0.82 and 0.79 respectively
(table 1.).
Table 1. Summary of the calculated averages of Petrophy sical parameters of Datom North
Zone
Nam e
To p
res e rv.MD
(ft)
Base
res e rv.MD
(ft)
Gros s
interva l
(ft)
Net pa y
interva l
MD (ft)
N/G
ratio
Av.P hie
(%)
Av Sw
(%)
Swirr
(%)
Av Vcl
(%)
RESER 1 A
8815.50
8903.50
88 .00
79 .25
0.90
20
32
31
22
RESER 1 B
9100.00
9157.50
57 .50
38 .00
0.66
18
34
32
36
Zone
Nam e
Net pa y pe r-
m eab ility
(m d )

BVW
MHI
HC P V

RESER 1 A
733.20
0.82
0.06
0.39
13 .56
0.68
RESER 1 B
598.60
0.79
0.06
0.43
11 .90
0.66
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Fig 2. Well-to-well correlation panel of the study area showing hydrocarbon bearing sand units
Fig 3. showing GR log histogram and cros s plot of neutron-density log of reservoir 1A and 1B of the
Datom north well for shale volume estimation
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Fig 4. Comparison of petrophysical parameter logs of Datom north to validate lithology, fluid type, hy-
drocarbon producibilty
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Fig 5. Showing summary of cut off from average porosity, volume of clay, water saturation to estimate
net pay zones of Datom north well
Datom West
The average porosity of the reservoirs (2A and 2B) of t he Datom West well is approximately
18%, with well top and base at 8996.50ft-9095ft and 9263ft-9321ft respectively. It has a
gross thickness of 98ft and 58ft, Net pay thickness of 86.50ft and 48ft with a N/G ratio of
0.878 and 0.828. The water saturation is relatively good at 0.38 and 0.32. The permeability
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of the net pay zone and the water saturation of the flushed zone for reservoir 2A and 2B are
640mD and 471mD (permeabilit y) and approximately 0.9 for  (table 2).
Fig 6. Comparison of petrophysical parameter logs of Datom west to validate lithology, fluid type, hy-
drocarbon producibilty
Table 2. Summary of the calculated averages of Petrophysical parameters of Datom west
Zone
Nam e
To p re se rv.M D
(ft)
Base
res e rv.
MD( ft)
Gros s in -
terval.
MD, (ft)
Net pay
interval
MD( ft)
N/G ra -
tio
Av.P hi
e (%)
Av Sw
(%)
Sw irr
(%)
Av Vcl
RESER 2A
8996.50
90 95 .00
98 .50
86 .50
0.88
19
37
35
0.14
RESER 2B
9263.00
93 21 .00
58 .00
48 .00
0.83
18
32
31
0.13
Zone
Nam e
Net pa y permeabil-
ity, (md)

BVW
MHI
HC P V

RESER 2A
64 0.5
0.88
0.07
0.26
11 .84
0.62
RESER 2B
47 1.9
0.84
0.06
0.38
12 .22
0.68
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Fig 7. Comparison of petrophysical parameter logs of Datom east to validate lithology, fluid type, hydro -
carbon producibilty
Datom East
The reservoirs in this well have average thicknesses from 9101ft -9219ft in reservoir 3A and
9357.50ft-9418ft in reservoir 3B. The average neutron-density derived porosity for the reser-
voirs are bet ween 19% and 22%, which indic ates good average porosity. The water saturation
of the reservoirs is 0.34 and 0.22 with a gross interval of 118ft and 61ft respectively. The net
pay thickness is 88.50ft and 48ft,N/G ratio of approximately 0.8, Average net pay permeability
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is 587mD and 322mD with wat er saturation of flushed zone to be 0.81 and 0.79 respec tively
(table 3).
Table 3. Summary of the calculated averages of Petrophysical parameters of Datom East
Zone
Nam e
To p re se rv.M D
(ft)
Base
res e rv.
MD( ft)
Gros s in -
terval.
MD, (ft)
Net pay
interval
MD( ft)
N/G ra -
tio
Av.P hi
e (%)
Av Sw
(%)
Sw irr
(%)
Av Vcl
RESER 2A
9101.00
92 19 .00
118.00
88 .50
0.75
19
34
34
36
RESER 2B
9357.50
94 18 .50
61 .00
48 .00
0.79
22
21
20
35
Zone
Nam e
Net pa y pe rmeabil-
ity, (md)

BVW
MHI
HC P V

RESER 2A
587.30
0.81
0.07
0.42
12 .50
0.66
RESER 2B
322.70
0.79
0.05
0.27
17 .25
0.78
4. Discussion
A c areful examination of the logs recorded through the three wells Datom (North, West and
East) oil field shows two distinctive porous and permeable sand bodies (fig 3),where t he shal-
low reservoir is indicat ed as Reservoirs (1A,2A,3A)and reservoirs (1B,2B and 3B) as the
deeper reservoir of the three wells. The average porosity and net pay permeabilit y are hydro-
carbon production friendly and also the consistent decrease of these lithologic al properties
with depth is perhaps due to compaction resulting from the weight of the overburden. While
the resistivity logs were used to detect the presence of hydrocarbon in the reservoirs, the
combination response (gas effect) of the neutron-density log through the sand units (clastic
reservoirs) indicates t hat the hydrocarbons will dominantly be gas inferred from Figures 4, 6
and 7 [26-27].
The bulk wat er volume (BVW) of the reservoirs was ca lculated at several depths and are
almost constant (0.06-0.07), t his indicates homogeneity of the reservoirs and is validated by
the close values of t he water saturation ( and irreducible water saturation (as shown
in tables 1,2&3.The implication is that hydrocarbon production from the zones at irreducible
water saturation should be water free [28].With a moveable hydrocarbon index (MHI=

less t han 0.7 across t he sand units shows favorable hydrocarbon moveability in the reservoirs [29]
,
this is in agreement with the increase in average water saturation  of the flushed zones
relative t o water saturation  ac ross the entire reservoir (table 1,2,3). T he average net to
gross ratio across the reservoirs (0.7-0.9) is defined using an average porosity ( and volume
of clay (
  cut offs values of   respectively (fig 5), validates t he high level of
clean sand in t he reservoirs, such sand bodies c onfirm that the permeability and porosity are
prospective [30-32 ]. An average hydrocarbon saturation (1-) ranging from 0.6-0.7 (table
1,2,3) indicates that hydrocarbon is relatively higher than water in t he reservoir, it is important
to note that water saturation does not represent the ratio to hydrocarbon that will be produced
from the reservoir but a reflection of relative proportion of the fluids contained in the reservoir.
Petrophysical analysis of the study area revealed average porosity values of 18-22% while
the permeability values ranged from 322.70 – 733.20 md ac ross the reservoirs. Hydrocarbon
saturation and reservoir thickness across t he reservoirs ranges from 66 - 78% and 48-98.50
ft respectively. The escalator regression sedimentation model of the Niger Delta makes it clear
that younger sediments are found in the distal part of the basin with pronounced thickness
greater than that on the proximal part [33]. Compaction was initiated early in the older rocks
of proximal fac ies of the Depobelts of the Niger Delta and graded down basin ward. Similarly,
the net-to- gross across the study area varies from 0.60- 0.9. Since it is well known that the
lower the volume of shale the higher the N/G and t he better the reservoir quality, therefore
the higher N/G values ac ross the study area is indicative of very good hydrocarbon reservoirs.
Since it is generally believed by some authors that t he sealing capacity of faults in a reservoir
is a funct ion of the shale percentage / shale content or the shale-sand ratio in a reservoir, it
therefore means that t he faults of t he reservoir with more shale content may be more sealing
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than the faults of the reservoir with lower shale content [12,34]. There also seem to be a gradual
decrease in sand percentage moving away from t he structure building bounding faults towards
the distal flanks [35]. The stacked thicknesses of t he reservoirs ranging between 18.20-33.86m
and 31.48-77.47m for reservoirs Sand_A and Sand_B are relatively high.
5. Summary, Conclusion and Recommendation
Gamma ray, neutron, density, resistivity/conductivity logs were employed in the evaluation
and examination of three wells, Datom (North, West and East). Two gas rich bearing sand
units were delineated across the formation, with porosity ranging from 0.18 to 0.22 indicating
a suitable reservoir quality, Favorable net pay permeabilit y values from 322.70mD to
733.20mD derived from logs and hydrocarbon saturation range of 0.62 to 0.78 implied high
hydrocarbon production. These results in addition with the hydrocarbon movability index
(MHI) values suggest high hydrocarbon potential and a reservoir system whose performance
is considered satisfactory for hydrocarbon production.
However, as relevant as log parameters are, they should not be applied without the con-
sultation of ot her necessary data like drill stem test, mud log evaluation, sample shows,
nearby produc tion etc before taking a decision to drill. Secondly, the hydrocarbon reserve
was not estimat ed due to unavailability of t he area extent of the reservoir therefore I recom-
mend t hat 3-D seismic data should be incorporated to allow for detailed and complimentary
study of “Datom” Oilfield, which includes necessary paramet ers to enable an accurate static
and dynamic model of the reservoir t o be constructed. This will enhance the geometry of the
geologic features, reveal the area extent of prospect zones and reduce inherent uncertainty.
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