Petrophysical Data Analysis for Enhanced Hydrocarbon ...

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Petrophysical Data Analysis for Enhanced Hydrocarbon Production in the Coastal Swamp Depobelt, Niger Delta Basin, Nigeria 1 1 1 1 Nwike, I.S. , Nwozor, K.K. , Onuba, L.N. , Chiadikobi, K.C. , 1 2 Okpoko, E.I. and Aniwetalu, E.U. 1 Department of Geology, Chukwuemeka Odumegwu Ojukwu University, Uli Campus, Nigeria. 2 Department of Geological Sciences, Nnamdi Azikiwe University, Awka, Nigeria. Corresponding E-mail: [email protected] Introduction The integration of well log analysis and petrophysical analysis are the the most efficient technique that can be adopted to estimate the reserve of any hydrocarbon bearing field in the oil and gas industry for effective productivity in commercial quantity and profitability. The Niger Delta Basin to date is the most prolific and economic sedimentary basin in Nigeria. It is an excellent petroleum province, ranked by the U.S Geological Survey World Energy Assessment as the twelfth richest in petroleum resources, with 2.2 % of the world's discovered oil and 1.4 % of the world's discovered gas (NNPC, 2005). The knowledge of reservoir characterization is an important factor in quantifying producible hydrocarbon (Schlumberger, 1942). According to Asquith (2004), well logs are used to correlate zones suitable for hydrocarbon accumulation, identify productive zones, determine depth and thickness of zones. Pateke Field is located within the Coastal Swamp Depobelt, Niger Delta Basin, Nigeria (Figure 1). In this study, we carried out petrophysical evaluation of the "Pateke" Field from a suite of wire-line logs comprising of gamma ray, resistivity, neutron and density logs of the wells. Good reservoir must be porous, permeable, oil saturated and of appreciable thickness (Adewoye et al., 2013) hence, accurate determination of these parameters is therefore necessary. The analyses carried out involved the delineation of lithologies, identification of reservoirs and fluid types, wells correlation and determination of petrophysical 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 analyze the petrophysical properties of the conventional reservoirs in the Pateke Field using well log data data to aid reservoir characterization in Pateke Field, Niger Delta Basin, Nigeria. Geology Setting of the Niger Delta Basin The Niger Delta is situated on the Gulf of Guinea off the coast of West Africa. The Niger Delta clastic wedge formed along a failed arm of a triple junction system that originally developed during break-up of the South American and African plates in the late Jurassic. Two arms followed the southwestern and southeastern coast Abstract An investigative study of three (3) wells from the Pakete Field in the Niger Delta Basin of Nigeria was carried out in order to identify and analyze the petrophysical properties / characteristics of the reservoirs in the field. This was achieved by combining the techniques of well log analysis and petrophysical analysis. Results from the well log interpretation showed the lithology penetrated by the wells to be mainly sand and sand-shale intercalation of the Benin Formation and Agbada Formation, respectively. The lithologies are dominantly sandstones, siltstones, and shale. An integrated analysis of Gamma Ray, Resistivity, Neutron and Density logs show that four (4) hydrocarbon to identify and analyze the petrophysical properties of the reservoirs in the field bearing reservoirs – Pateke A, B, C and D -were identified and these reservoirs were correlated across the three wells. Petrophysical parameters calculated for the reservoirs revealed that Pakete A reservoir is thickest in well eleven with thickness of 96.00m and thinnest in well five with thickness of 81.00m, with average thickness of 88.50m, Pakete B reservoir is thickest in well eleven with thickness of 97.00m and thinnest in well five with thickness of 65.00m, with average thickness of 81.00m, Pakete C reservoir is thickest in well five with thickness of 88.00m and thinnest in well six with thickness of 38.00m, with average thickness of 68.00m. Pakete D reservoir is thickest in well six with thickness of 90.00m and thinnest in well five with thickness of 62.00m, with average thickness of 75.00m. The petrophysical analysis of the Field reveals that reservoir porosity ranges from 12-28%, hydrocarbon saturation ranges from 0.45-0.90, water saturation ranges from 0.10-0.55, volume of shale ranges from 0.07-0.45, net-to-gross ranges from 0.51-0.98. The results of this study can be used by explorationist as a model to identify and develop other frontier deep exploration targets in other fields within the Niger Delta Basin. Also this research will be helpful in making investment decisions during oil and gas projects by the exploration and production department of oil and gas industries. Keywords: Petrophysical, Data Analysis, Hydrocarbon, Coastal Swamp, Niger Delta, Nigeria Journal of Mining and Geology Vol. 55(2) 2019. pp. 147 - 154 147

Transcript of Petrophysical Data Analysis for Enhanced Hydrocarbon ...

Petrophysical Data Analysis for Enhanced Hydrocarbon Production in the Coastal Swamp Depobelt, Niger Delta Basin, Nigeria

1 1 1 1Nwike, I.S. , Nwozor, K.K. , Onuba, L.N. , Chiadikobi, K.C. ,

1 2Okpoko, E.I. and Aniwetalu, E.U.

1Department of Geology, Chukwuemeka Odumegwu Ojukwu University, Uli Campus, Nigeria.2Department of Geological Sciences, Nnamdi Azikiwe University, Awka, Nigeria.

Corresponding E-mail: [email protected]

Introduction

The integration of well log analysis and petrophysical analysis are the the most efficient technique that can be adopted to estimate the reserve of any hydrocarbon bearing field in the oil and gas industry for effective productivity in commercial quantity and profitability. The Niger Delta Basin to date is the most prolific and economic sedimentary basin in Nigeria. It is an excellent petroleum province, ranked by the U.S Geological Survey World Energy Assessment as the twelfth richest in petroleum resources, with 2.2 % of the world's discovered oil and 1.4 % of the world's discovered gas (NNPC, 2005). The knowledge of reservoir characterization is an important factor in quantifying producible hydrocarbon (Schlumberger, 1942). According to Asquith (2004), well logs are used to correlate zones suitable for hydrocarbon accumulation, identify productive zones, determine depth and thickness of zones. Pateke Field is located within the Coastal Swamp Depobelt, Niger Delta Basin, Nigeria (Figure 1).

In this study, we carried out petrophysical evaluation of the "Pateke" Field from a suite of wire-line logs

comprising of gamma ray, resistivity, neutron and density logs of the wells. Good reservoir must be porous, permeable, oil saturated and of appreciable thickness (Adewoye et al., 2013) hence, accurate determination of these parameters is therefore necessary. The analyses carried out involved the delineation of lithologies, identification of reservoirs and fluid types, wells correlation and determination of petrophysical 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 analyze the petrophysical properties of the conventional reservoirs in the Pateke Field using well log data data to aid reservoir characterization in Pateke Field, Niger Delta Basin, Nigeria.

Geology Setting of the Niger Delta Basin

The Niger Delta is situated on the Gulf of Guinea off the coast of West Africa. The Niger Delta clastic wedge formed along a failed arm of a triple junction system that originally developed during break-up of the South American and African plates in the late Jurassic. Two arms followed the southwestern and southeastern coast

AbstractAn investigative study of three (3) wells from the Pakete Field in the Niger Delta Basin of Nigeria was carried out in order to identify and analyze the petrophysical properties / characteristics of the reservoirs in the field. This was achieved by combining the techniques of well log analysis and petrophysical analysis. Results from the well log interpretation showed the lithology penetrated by the wells to be mainly sand and sand-shale intercalation of the Benin Formation and Agbada Formation, respectively. The lithologies are dominantly sandstones, siltstones, and shale. An integrated analysis of Gamma Ray, Resistivity, Neutron and Density logs show that four (4) hydrocarbon to identify and analyze the petrophysical properties of the reservoirs in the field bearing reservoirs – Pateke A, B, C and D -were identified and these reservoirs were correlated across the three wells. Petrophysical parameters calculated for the reservoirs revealed that Pakete A reservoir is thickest in well eleven with thickness of 96.00m and thinnest in well five with thickness of 81.00m, with average thickness of 88.50m, Pakete B reservoir is thickest in well eleven with thickness of 97.00m and thinnest in well five with thickness of 65.00m, with average thickness of 81.00m, Pakete C reservoir is thickest in well five with thickness of 88.00m and thinnest in well six with thickness of 38.00m, with average thickness of 68.00m. Pakete D reservoir is thickest in well six with thickness of 90.00m and thinnest in well five with thickness of 62.00m, with average thickness of 75.00m. The petrophysical analysis of the Field reveals that reservoir porosity ranges from 12-28%, hydrocarbon saturation ranges from 0.45-0.90, water saturation ranges from 0.10-0.55, volume of shale ranges from 0.07-0.45, net-to-gross ranges from 0.51-0.98. The results of this study can be used by explorationist as a model to identify and develop other frontier deep exploration targets in other fields within the Niger Delta Basin. Also this research will be helpful in making investment decisions during oil and gas projects by the exploration and production department of oil and gas industries.

Keywords: Petrophysical, Data Analysis, Hydrocarbon, Coastal Swamp, Niger Delta, Nigeria

Journal of Mining and Geology Vol. 55(2) 2019. pp. 147 - 154

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of the Nigeria and Cameroon and are developed into the passive continental margin of West Africa, whereas the third failed arm formed the Benue Trough (Doust and Omatsola, 1990).

Renewed subsidence occurred as the continents separated and the sea transgressed the Benue trough. The Niger Delta clastic wedge continued to prograde during Middle Cretaceous time into a depocenter located above the collapsed continental margin at the site of the triple junction. Sediment supply was mainly along drainage systems that followed two failed rift arms, the Benue and Bida Basins. Other depocenters along the African Atlantic coast also contributed to deltaic build-ups. Sediment propagation was interrupted by episodic transgressions during Late Cretaceous time. Syn-rift sediments accumulated during the Cretaceous to Tertiary, with the oldest dated sediments of Albian age. Thickest successions of syn-rift marine and marginal marine clastics and carbonates were deposited in a series of transgressive and regressive phases (Doust and Omatsola, 1989). During

the Tertiary, sediment supply was mainly from the north and east through the Niger, Benue, and Cross Rivers. Cross and Benue Rivers provided substantial amounts of volcanic zone beginning in the Miocene (Nwachukwu, 1972). Regression rates increased in the Eocene, with an increasing volume of sediments accumulated since the Oligocene (Short & Stauble, 1967). The Niger Delta constitutes an advance of terrrestrial deposits into a high energy marine environment. Short and Stauble (1967), defined three stratigraphic unit in the tertiary Niger Delta based on the dominant environmental influence. The main sedimentary environments are the continental environment, the transitional environment, and the marine environment. The sequence is capped by a section of massive continental sands. Based on the history or relative unbroken progradation throughout the Tertiary, these depositional lithofacies are readily identified despite local facies variations, as the three regional and diachronons formations ranging from Eocene to Recent age. The three major lithostratigraphic units defined in the subsurface of Niger Delta (Akata,

Fig. 1: A descriptive map of the Niger Delta showing main depobelts and the study area (Modified from Doust and Omatsola, 1990)

b

a

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Gamma Ray Index

The gamma ray index is defined as the linear scaling of the GR between GR and GR Calculation of the min max.

gamma ray index is the first step needed to determine the volume of shale from a gamma ray log. The gamma ray log can be used to calculate volume of shale in porous reservoirs. The gamma ray index using the formula according to Asquith and Gibson (1982) as given in question 1:

...............................................(1)

Where,I = gamma ray indexGR

GR = gamma ray reading of formation from loglog

GR = minimum gamma ray (clean sand) min

GR = maximum gamma ray (shale)max

Volume of Shale

The volume of shale was calculated by applying the gamma ray index in the appropriate volume of shale equation according to Wyllie (1950) for tertiary rocks as given in question 2:

(3.7 * IGR)V = 0.083 (2 – 1) ...........................................(2)sh

Where, V = volume of shalesh

I = gamma ray index.GR

Net To Gross Ratio (NTG)

This is the ratio between the net reservoir thickness and the gross reservoir thickness.

NTG = Net thickness / Gross Thickness .............................(3)

Porosity

The amount of void space within a formation will determine the amount of fluid it will retain. Porosity was computed from density log using the Wyllie's equation (Wyllie and Rose, 1950) as given in equation 4:

.............................................................(4)

Where;Ñ = Matrix densityma

Ñ = Formation bulk densityb

Ñ = Fluid densityf

Ø = neutron-density porosityDen

Agbada and Benin Formations) reflect a gross upward-coarsening clastic wedge. The Akata Formation and upper Agbada Formation are believed to be the main source rocks of the eastern part of the Delta. The Agbada Formation constitutes the main reservoirs of hydrocarbons in the Niger Delta while the Agbada shales mainly constitute the seals. Finally, the Benin Formation is generally water bearing zone. It is the main source of portable ground water in the Niger Delta area. These Formations were deposited in dominantly marine, deltaic and fluvial environments respectively (Weber and Daukoru, 1975).

Materials and Method

Well Log Data

Reservoir Evaluation requires the integration of all available subsurface data such as wireline logs (Gamma ray, Sonic, Density, Resistivity and Neutron logs) checkshot and deviation data. Lithologies were identified with the aid of gamma ray log. A range of 0 to 150 API was used for the GR logs. Shales contain the greatest amount of radioactive minerals and the gamma ray logs are primarily used in identifying shale and shale-rich facies. Sand-rich facies are interpreted with low gamma ray counts. The average shale-baseline used in this study is 65 API. GR values with deviation to the left of the shale-baseline were delineated as sand units while shale was delineated with deviation to the right. Sandy lithologies were identified with yellow colour while shaley lithologies were identified with grey colour for easy identification and thickness evaluation.

The fluid (water or hydrocarbon) present in each of the identified sand unit was identified using the resistivity logs. High resistivity readings are interpreted as probable hydrocarbon bearing sand units, whereas, low resistivity readings are interpreted as probably water bearing sand units.

A decrease in neutron reading with an increase in density reading was interpreted as gas while an increase in neutron reading with a corresponding decrease in density reading was interpreted as oil. Interpretation of the lithologies penetrated by the studied wells within the interval of interest were determined by using petrel calculator to set the cutoffs on the gamma ray logs as follows; <65 API = sand, 65-80 API = silt, >80 API = shale. The well-logs were also interpreted to delineate the hydrocarbon bearing reservoirs within the study area. The approaches below were used to calculate the petrophysical properties of the reservoir.

I = GR

GR - GRlog min

GR - GRlmax min

Ø =Den

Ñ Ñma b - Ñ Ñma f -

Water Saturation (Sw) and Hydrocarbon Saturation (S )h

The water saturation (Sw) is the percentage of pore volume in a rock which is occupied by formation water. The water saturation for the uninvaded zone was calculated using the Archie (1942) equation given as equation 5:

.............................................................(5)

But

so that

Substituting equation into

For the flushed zone, water saturation was calculated using the equation below;

.......................................................(6)

Since the resistivity of the mud filtrate is unknown, the resistivity of the flushed zone was determined from water saturation using the ratio equation by Archie (1942);

Where;S = Water saturation of the uninvaded zonew

R = Resistivity of formation water at formation w

temperatureR = True resistivity of formationt

R = Resistivity of a zone 100% water saturatedo

F = Formation factorS = Water saturation of the flushed zonexo

R = Resistivity of the mud filtrate mf

R = Resistivity of the flushed zonexo

N = Saturation exponent (for most formation n=2)

From water saturation (S ), hydrocarbon saturation (S ) w h

was determined;

S = 1 - S ...................................................................(7)h w

Where;S = Hydrocarbon saturationh

S = Water saturation of the uninvaded zonew

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Result and Discussion

Well Log Data Interpretation

Five (5) wire-line logs were used in this study to interpret the lithology and analyze the petrophysical parameters of the conventional reservoirs of the Pateke Field (Figure 2(a)). The well data used in this study include well-log suites (Gamma ray log, Sonic log, Density log, Resistivity log and Neutron log) which aided the identification and evaluation of four hydrocarbon bearing reservoirs, labelled A, B, C, and D are showed in figure 2(b).

Well Five

In this well five, four reservoirs (Pateke A, B, C, D) were delineated and have average thickness which ranges from 62m in reservoir D to 88m in reservoir C. The average shale volume content (Vsh) of the reservoirs is between 0.13v/v in reservoir D to 0.30v/v decimal in reservoir A. The volume of shale values is not within the limits that could affect the values of water saturation (Archie, 1942) and suggests that the reservoirs are clean. The average porosities of the reservoirs are good enough (18% - 28%). The low water saturation of reservoir D (16%) indicates 84% hydrocarbon saturation. The average water saturation of these reservoirs ranges between 11% - 48% (see Figure 3). The low water saturation values of reservoir B and D in this well are indicative of high hydrocarbon saturation in the reservoirs (see Table 1).

Well Six

Two reservoirs were encountered in this well with reservoir thickness ranging from 38m in reservoir C to 90m in reservoir D. These reservoirs are clean and reservoir C indicated low value of volume of shale content (Vsh) while reservoir D whose Vsh value is 45% exceeded the limits that could affect the water saturation. Their porosity values are 17% to 19% respectively. The water saturation of reservoir C and D are low (15% and 22%) which invariably are indication that the hydrocarbon saturations are high (85% and 78%). The hydrocarbon in reservoir C and D could be oil with the tracking together of the density and neutron log signatures (Figure 3). On the other hand, the low water saturation (Sw) values of reservoir C and D are evidence that they are oil- filled reservoirs (15% and 22%) (See Table 2).

S = w Rt

FRw( )1/n

F = Ro

Rw/

R =o FRw

S = w Rt

Ro

S = xo Rxo

F x Rmf( )½

S = xo (S )w5

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Fig. 2(a): Well Log Correlation of the Identified Reservoir

Fig. 2(b): Pateke 11 showing the Petrophysical Logs

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Table 1: Summary of Reservoir’s Parameters of Well Five

Table 2: Summary of Reservoir’s Parameters of Well Six

The porosity and permeability of the reservoir sandstone generally decrease with increasing burial depth, as a result of mechanical compaction and diagenetic alterations. Generally, the permeability reduction with burial depth is more pronounced for fine grained sandstones than for coarse grained; however, the presence of detrital clay, sorting and other elements related to variations in the depositional environments affect permeability. The presence of diagenetic cement may also result in substantial permeability reduction, as the cement reduces the size of the pore throats.

Porosity estimation and those of other parameters obtained in this study were based on sonic logs readings.

Well Eleven

A total number of four reservoirs (Pateke – A, B, C, D) were delineated in this well. The average shale volume (Vsh) of the reservoirs in well 11 is between 0.010v/v to 0.32v/v decimal. This suggests that reservoir A, with Vsh value of 0.32v/v decimal is above the limit of 20% that can affect the water saturation. The average porosity values for the reservoirs range between 0.18% - 0.28%, which indicate good porosity values of typical Niger Delta reservoirs. Reservoir with high value of resistivity is likely hydrocarbon zone and hydrocarbon saturation values for the reservoirs suggest that the reservoirs are mainly oil bearing. (See Figure 3).

Fig. 3: The Porosity-Depth and Permeability-Depth relationships between the well 5 in Pateke Field

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Fig. 4: The Porosity-Depth and Permeability-Depth relationships between the well 6 in Pateke Field

Fig. 5: The Porosity-Depth and Permeability-Depth relationships between the well 11 in Pateke Field

Table 3: Summary of Reservoir’s Parameters of Well Eleven

Porosity values range from 12% to 28% are within good to very good reservoir quality. Permeability values range from 615 mD to 984 mD are very good for hydrocarbon production. These computed values are an indication that fluids can flow through the rocks without causing structural changes.

Conclusion and Recommendation

Interpretation of the available dataset of the Pateke Field, Niger Delta was done using well log data. Four reservoirs were identified and correlated across the three wells along depositional dip showing good

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continuity. Petrophysical analysis of the identified reservoirs showed that the reservoirs are of good quality with average porosity ranging from 12% - 28% and average hydrocarbon saturation ranging from 45% - 90%. Hydrocarbon typing showed that the reservoirs all contain oil. These results suggest high hydrocarbon potential and a reservoir system is considered satisfactory for hydrocarbon production. However, the hydrocarbon reserve was not estimated due to unavailability of the area extent of the reservoir therefore I recommend that 3-D seismic data should be incorporated to allow detailed and complimentary study of the Pateke Field which includes necessary parameters

to enable an accurate static and dynamic model of the reservoir to be constructed. This will enhance the geometry of the geologic features and reduce inherent uncertainty.

Acknowledgements

I pleased to thank all the participants of the article for funding this work. Finally, the authors are grateful to the Nigerian National Petroleum Corporation for releasing the data used in this study through its exploratory arm, NAPIMS Lagos.

Adewoye, O., Amigun, J.O., Okwoli, E. and Cyril, A. G. (2013). Petrophysical and structural analysis of maiti field, Niger Delta, using well logs and 3-D seismic data. Petroleum & Coal, 4 (55): 302-310.

Asquith, G. (2004). Basic well log analysis. AAPG methods in exploration series: American Association of Petroleum Geologists, Tulsa, Oklahoma, 16: 12-135.

Archie, G.E. (1942). Introduction to petrophysics of reservoir rocks. American Association of Petroleum Geologists Bulletin, 34(5): 943-961.

Doust, H. and Omatsola, E. (1990). Geology of the Niger Delta, SPDC publishers, 201- 237.

Doust, H. and Omatsola, E. (1990). Niger Delta, in, Edwards, J.D., and Santogrossi, P.A., eds., Divergent/passive Margin Basins, AAPG Memoir 48: Tulsa, American Association of Petroleum Geologists, p239-248

Ekweozor, C. M. and Daukoru, E.M. (1984). Northern delta depobelt portion of the Akata- Agbada petroleum system, Niger Delta, Nigeria, In: Magoon, L.B. and Dow, W. G. (eds); The Petroleum System from Source to Trap, American Association of Petroleum Geologists, Memoir 60: 599-614.

NNPC, 2005. Overview of the Nigeria Petroleum Industry and opportunities for Investment. Paper presented at the 18th World Petroleum Congress, Johannesburg, South Africa, September, p.25-29.

Nwachukwu, S.O. (1972). The Tectonic Evolution of the Southern Portion of the Benue Trough, Nigeria. Geology Magazine, 109: 411-419.

Rider, M. (1996). The Geological Interpretation of Well Logs, 2nd edition, Rider-French Consulting, 1-279.

Schlumberger, (1942). Geological significance of s e i s m i c a t t r i b u t e .

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Short, K. C. and Stauble, A. J. (1967). Outline of Geology of Niger Delta. American Association of Petroleum Geologists Bulletin, 51: 761–779.

Weber, K. J. and Daukoru, E. M. (1975). Petroleum geology of the Niger Delta: Proceedings of the 9th World Petroleum Congress, Geology: London, Applied Science Publishers, Ltd., 2: 210–221.

Wyllie, M.R. and Rose, W.D. (1950). Some theoretical considerations related to the quantitative evaluation of the physical characteristics of reservoir rocks from electric log data. Transactions of the American Institute of Minning and Metallurgical Engineers, 12:67-80.

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References

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