Investigating the Impact of Electro-Non-radioactive ...€¦ · Unconsolidated Dual Sandstone Reservoir Systems in the EMI-Field, Eastern Niger Delta 127 trend across the study area

European Journal of Scientific Research

ISSN 1450-216X / 1450-202X Vol. 155 No 1 December, 2019, pp.124 -133

http://www. europeanjournalofscientificresearch.com

Investigating the Impact of Electro-Non-radioactive Properties

of Productive Unconsolidated Dual Sandstone Reservoir

Systems in the EMI-Field, Eastern Niger Delta

A.J. Ilozobhie

Physics Department, University of Calabar, Nigeria

E-mail: [email protected]; [email protected]

E. Ikpang

Physics Department, University of Calabar, Nigeria

D. I. Egu

Petroleum Department, Madonna University, Nigeria

Abstract

The impact of fluid resistivity and radioactivity of a dual sandstone reservoir system

in the EMI Field, Niger Delta as an alternative reservoir characterization tool was

investigated. Average values of gamma ray and resistivity log readings were obtained from

the lithostratigraphic log panels of identified sandstone reservoirs ER1 (top) and ER2

(bottom) from the six well by which various models were generated using mathematical

algorithm. Electro-nonradioactive properties in ER1 showed similar patterns of minimum

quadratic curves in wells EMI-04 and EMI-03. A decreasing pattern was recorded in wells

EMI-02, EMI-01 and EMI-05 while only well EMI-06 showed increasing trend. Results of

wells in ER2 showed similar decreasing trend in wells EMI-02 and EMI-05 while wells

EMI-04 and EMI-03 had increasing trends. Comparison of trends in ER1 and ER2 showed

a quadratic maximum curves at the reservoir top(ER1) in wells EMI-02 and at the bottom

(ER2) in well EMI-01,while wells EMI-04 (ER1) and EMI-06 (ER2) showed a quadratic

minimum curves, wells EMI-01 (ER1), EMI-05 (ER1), EMI-02 (ER2) and EMI-05 (ER2)

showed decreasing trends. Wells EMI-06 (ER1), EMI-04 (ER2) and EMI-03 (ER2) showed

increasing trends. Low gamma radiations and high resistivity characteristics are appropriate

for delineation of a good pay zone or good horizon delineation. The analysis clearly shows

that electro-nonradioactive properties or patterns gives a better understanding of

unconsolidated sandstones and their fluid contents which can be used for effective reservoir

management and maintenance. These patterns can be further mapped out for enhanced oil

recovery projects for particularly complex and severely depleted Fields.

Keywords: Radioactivity, resistivity, sandstones, reservoirs, patterns, characteristics,

gamma ray

Introduction Hydrocarbon reservoirs are tapped by wells and the wells are basically the source of most of the

information concerning the reservoir (Kruisi and Idiagbor, 1994 Obi, et. al . 2017). Such information

includes; resistivity, radioactivity, porosity, fluid saturation, permeability and lithology, all of which

Investigating the Impact of Electro-Non-radioactive Properties of Productive

Unconsolidated Dual Sandstone Reservoir Systems in the EMI-Field, Eastern Niger Delta 125

are very crucial for reservoir characterization, description and management (Tearpock and Bischke,

1990). Reservoir characterization is essential for determination of storage capacity, distribution of

porosity and permeability within the field, prediction of reservoir performance, estimation of

production rate and evaluation of ultimate recovery for various depletion plans (Ilozobhie and Egu,

2014). It is on record that many oil fields within the Niger Delta which were initially abandoned after

serving their estimated life time have been reactivated and are producing more oil because of reservoir

analysis of such fields ( Ojo, 1996, Oyedele, et al., 2013, Bateman, 1985 and Ilozobhie and Egu,

2018),

The EMI Field has a lot of hydrocarbon potentials but it’s severely limited to complex detailed

reservoir characterization particularly as it pertains to radioactivity and resistivity relationships of the

highly demanded porous reservoir sands and its fluid content. Quicker correlations using gamma ray

and electrical resistivity logs are also not available for effective reservoir characterization. This has

over time made reservoir management and monitoring very difficult particularly in the delineation of

reservoirs ER1 and ER2 from the six wells and 3-D seismic data used thus the present research will

critically investigate the impact of fluid resistivity and radioactivity of a dual sandstone reservoir

system in the EMI Field, Niger Delta as an alternative reservoir characterization tool, by developing

petrophysical models of resistivity and radioactivity of reservoir sands and subsequently monitor the

patterns associated with the correlations and then carrying out a detailed comparison of the models for

the dual reservoir systems with a view to use it for monitoring and management of reservoirs through

which quicker hydrocarbon characterization can be achieved by conversion of the predicted models to

software.

Materials and Methods Materials

The present study area is located between latitudes 40.00

1 and 6

0.00

1N and longitudes 5

0.00

1 and 7

0.00

1

E at the offshore depobelt of Eastern Niger Delta, Nigeria Figure-1. Materials used are composite well

logs consisting of gamma ray logs and resistivity logs in six wells in the EMI Field which are EMI-02,

EMI-04, EMI-01, EMI-03, EMI-05 and EMI-06 well spaced for enhanced productivity (Figure-2).

Gamma log was primarily used in lithology identification and boundary demarcation while the

Resistivity log was used for fluid identification ( Nton and Esan 2010, Helander,1983, Asquith and

Krygowski, 2004). The two logs were provided for all the wells.

Figure 1: Map showing the location of Emi field

126

Methods

Lithostratigraphic correlation panels for the top and bottom reservoir systems were used to extract the

data for resistivity of formation fluids and sand radioactivity. Average values of gamma ray (API) and

resistivity (ohm

EMI

mathematical software. Summary of all the data for each well was also produced to investigate the

126

Methods



resistivity (ohm

EMI-05 and EMI

The data was used




resistivity (ohm-m) were extra

05 and EMI-06 from A to A’ as shown in Figures

Figure 3:

The data was used


A

Figure 2:



m) were extracted from the pay zones from wells EMI

06 from A to A’ as shown in Figures

3: Lithostratigraphic correlation of top and base of reservoir sand ER1

The data was used to produce the result and models were predicted using available


2: The Base map of the Study Oil



cted from the pay zones from wells EMI

06 from A to A’ as shown in Figures

Lithostratigraphic correlation of top and base of reservoir sand ER1

to produce the result and models were predicted using available


The Base map of the Study Oil



cted from the pay zones from wells EMI

06 from A to A’ as shown in Figures-3 and 4.




A.J. Ilozobhie

The Base map of the Study Oil Field



cted from the pay zones from wells EMI-02, EMI

3 and 4.




A.J. Ilozobhie, E. Ikpang

Field



02, EMI-04, EMI




E. Ikpang and D. I. Egu



04, EMI-01, EMI




a

D. I. Egu



01, EMI-03,





trend across the study area. An attempt was also made to compare results for both identified reservoirs

ER1 and ER2. Figure 4: Lithostratigraphic correlation of top and base of reservoir sand ER2

Results Fluid Resistivity and Sand Radioactivity Content for Top Reservoir ER1

Results of well EMI-02 showed the fluid resistivity ( r) described a maximum quadratic curve with

sand radioactivity (g ) and the software generated model gave r = -66.66g2 + 4033g – 60100 as shown

in Figure -5. In well EMI-04, the resistivity described a minimum quadratic curve with radioactivity

given as r = 222g2 – 14452g + 23497 Figure-6. In well EMI-01, resistivity declined with radioactivity

with r = -450g2 + 10335g – 58105 Figure-7. Result of well EMI-03 also described a minimum

quadratic curve of resistivity with radioactivity with r = 95.16g2 – 2566g + 18418 Figure -8. Result of

well EMI-05 described a similar trend to well EMI-01 but with predicted model of r = -0.713g2 +

29.07g + 1074 Figure-9. In well EMI-06, resistivity increased with radioactivity with a model of r = -

0.154g2 + 13.18g + 834.7 Figure-10.

Figure 5: Electro-Nonradioactive pattern result from well EMI-02 (ER1)

0

200

400

600

800

1000

28 29 30 31 32 33Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

A A

128 A.J. Ilozobhie, E. Ikpang and D. I. Egu





r = 222g2 - 14452g + 23497

R² = 1

-500

0

500

1000

1500

28 30 32 34 36Re

sist

ivit

y (

oh

m-m

Gamma Ray (API)

r = -450g2 + 10335g - 58105

R² = 1

0

500

1000

1500

10.5 11 11.5 12 12.5 13 13.5

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

r = 95.16g2 - 2566g + 18418

R² = 1

1050

1100

1150

1200

1250

1300

1350

0 5 10 15 20Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

r = -0.154g2 + 13.18g + 834.7

R² = 1

1000

1050

1100

1150

0 10 20 30 40 50Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)




Fluid Resistivity and Sand Radioactivity Content for Top Reservoir ER2

Results of wells EMI-02 and EMI-04 showed similar trend with decreased and fairly constant

resistivity with radioactivity relationships and with predicted models of r = -6.879g + 768.7 and r = -

6.578g + 1003 Figures -11 and 12. Results of well EMI-01 gave a maximum quadratic curve with a

predicted model of r = -42.52g2 + 1276g – 8389 Figure-13 while well EMI-03 had an increased fluid

resistivity with sand radioactivity with r = -75g2 + 2225g – 15750 Figure-14. Well EMI-05 gave a

linearly declining result of resistivity with radioactivity and a model of r = -3.986g + 878.7 Figure-15

while EMI-06 showed a minimum quadratic curve of resistivity with radioactivity and a predicted

model of r = 16g2 – 598g + 5980 Figure-16.



r = -0.713g2 + 29.07g + 1074

R² = 1

0

500

1000

1500

0 10 20 30 40 50Re

sist

ivit

y (

oh

m-m

)Gamma Ray (API)

r = -6.879g + 768.7

R² = 0.426

0

200

400

600

800

1000

0 20 40 60 80 100Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

r = -6.578g + 1003.

R² = 0.004

0

500

1000

1500

2000

0 10 20 30 40

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)






r = -42.52g2 + 1276g - 8389

R² = 1

0

500

1000

1500

0 5 10 15 20 25

Re

sist

ivit

y (

oh

m-m

)Gamma Ray (API)

r = -75g2 + 2225g - 15750

R² = 1

0

200

400

600

800

12.5 13 13.5 14 14.5 15 15.5Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

r = -3.986g + 878.7

R² = 0.995

0

200

400

600

800

1000

0 20 40 60 80 100

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)

r = 16g2 - 598g + 5980

R² = 1

380

400

420

440

460

16 17 18 19 20 21

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)



Table 1: Comprehensive Result of Gamma Ray and Resistivity Logs for Reservoir ER1

Wells Depth (ft) GR (API) Res (ohm-m)

EMI-02

2590 30 900

2650 32 700

2700 29 800

EMI-04

2640 35 1100

2700 30 1210

2770 31 300

EMI-01

2640 12 1115

2700 11 1130

2770 13 200

EMI-03

2755 14 1135

2800 15 1328

2900 12 1320

EMI-05

2800 40 1095

2900 20 1370

2940 17 1362

EMI-06

2880 45 1115

2900 22 1050

2930 18 1022

Discussion of Results It was observed that similar trends occurred in some wells for both reservoir systems. In reservoir ER1,

well EMI-04 and EMI-03 had similar trends with minimum quadratic models while wells EMI-01 and

EMI-05 steadily showed declining resistivity with radioactivity. These similarities may indicate

synergized pattern of reservoir fluids and radioactive sands which may vary in different wells as shown

in wells EMI-02 and EMI-06. This may be attributed to the geologic age in characteristic properties of

the top reservoir Table 1 and Figure-17.

Figure 17: Electro-Nonradioactive pattern result from all six wells in reservoir ER1

However, the bottom reservoir sand ER2 showed fairly similar patterns in behaviours where

wells EMI-02, EMI-04, EMI-03 and EMI-05 gave fairly linear correlations suggesting an older

geologic age for this bottom reservoir (Table 2 and Figure-18). Cumulative average results of

variations of fluid resistivity and sand radioactivity of top reservoirs ER1 and bottom reservoir ER2

showed fairly similar characteristics indicating that both reservoirs may have originated from the same

rock while conditions for sedimentation may also be similar.

r = - 0.027g5 + 1.910g4 - 67.28g3 + 1264g2 -

11971g + 45588

R² = 0.269

0

500

1000

1500

0 10 20 30 40 50

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)


Table 2: Comprehensive Result of Gamma Ray and Resistivity Logs for Reservoir ER2

Wells Depth (ft) GR (API) Res (ohmm)

EMI-O2

4500 21 910

4530 82 200

4570 20 350

EMI-04

4490 32 850

4550 20 1500

4565 21 180

EMI-01

4485 18 800

4550 10 118

4560 20 120

EMI-03

4590 15 750

4600 14 700

4670 13 500

EMI-05

4500 22 800

4550 23 778

4590 80 560

EMI-06

4490 17 438

4500 20 420

4580 18 400

Figure 18: Electro-Nonradioactive pattern result from all six wells in reservoir ER2

A comparison of patterns in wells from both reservoir systems revealed the existence of fairly

similar patterns in wells EMI-02 (averagely declining), well EMI-04 (averagely increasing), EMI-01

(averagely declining), well EMI-03 (averagely increasing), well EMI-05 (averagely declining), while

well EMI-06 gave different result patterns as shown in Table 3.

Table 3: Comparative Patterns of Predicted Models for Wells in Reservoirs ER1 and ER2

S/N Wells Reservoirs Patterns

Remark ER1 ER2

1. EMI-02

Fairly similar

2. EMI-04

Fairly similar

3. EMI-01

Fairly similar

r = -0.001g4 + 0.146g3 - 7.523g2 +

173.5g - 833.2

R² = 0.1830

500

1000

1500

2000

0 50 100

Re

sist

ivit

y (

oh

m-m

)

Gamma Ray (API)



S/N Wells Reservoirs Patterns

Remark ER1 ER2

4. EMI-03

Fairly similar

5. EMI-05

Fairly similar

6. EMI-06

Different

Conclusion Low gamma radiations and high resistivity characteristics are appropriate for delineation of a good pay

zone or good horizon delineation. It is clear that electro-nonradioactive properties or patterns gives a

better understanding of unconsolidated sandstones and their fluid contents which can be used for

effective reservoir management and maintenance. These patterns can be further mapped out for

enhanced oil recovery projects for particularly complex and severely depleted Fields that have served

their estimated years of productivity leading to reactivation of such fields.

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Petroleum Geologists Methods in Exploration Vol.16; pp. 31-35.

[2] Bateman, R. M. 1985. Open-hole log analysis and formation evaluation, IHRDC Publishers,

Boston MA, pp 645-649.

[3] Helander, D. P. 1983. Fundamentals of formation evaluation. Oil and gas consult international

Inc., Tulsa.

[4] Ilozobhie, A.J, and Egu, D.I, 2014. Economic evaluation modelling of a gas field for effective

reservoir management in the Niger Delta. International journal of Natural and Applied

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[7] Nton, M. E, and Esan, T. B, 2010. Sequence stratigraphy of EMI Field, offshore Eastern Niger

Delta, Nigeria. European Journal of Scientific Research, Vol. 44; (No 1) pp 115-132.

[8] Obi, D.A, Ilozobhie A.J, Lebo, S.E and Zoogbara, E 2017. Modelling Magnetic Basement in

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[9] Ojo, A. O, 1996. Pre-drill prospect evaluation in deep water. Nigeria. Nigerian Association of

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[10] Oyedele, K.F, Ogagarue, D. O., and Mohammed, D.U. (2013), Integration of 3D seismic and well

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Documents

Investigating the Impact of Electro-Non-radioactive ...€¦ · Unconsolidated Dual Sandstone Reservoir Systems in the EMI-Field, Eastern Niger Delta 127 trend across the study area