Reservoir Evaluation and Volumetric Analysis of Rancho Field, Niger Delta, Using Well Log and 3D Seismic Data

Exploration and exploitation for hydrocarbon are associated with a lot of complexities, it is therefore necessary to integrate available geologic models for accurate hydrocarbon prospecting and risk analysis. This study is aimed at determining the structural, petrophysical and volumetric parameters for reservoir evaluation within the Rancho field. 3D seismic data was used for evaluating the hydrocarbon potential of the field. A suite of well logs but not limited to gamma ray logs (GR), deep resistivity log (DRES), neutron log (NPHI) and density log (RHOB) from four (4) wells were employed in characterising dynamic properties of the reservoirs. The GR log was used in lithology identification while the resistivity log was used in identifying probable hydrocarbon bearing sands. A correlation exercise was carried out to identify lateral continuity and discontinuity of facies across the wells. Thereafter petrophysical parameters were analysed from the suite of wire line logs. Major faults were mapped on the 3D seismic data and identified hydrocarbon bearing sand tops from the well logs were mapped as horizons on the seismic section, maps were generated and volumetric analysis was done. Nine (9) hydrocarbon sands (Sands A I) were identified within the study area. The well log revealed an alternation of sand and shale layers as well as shale layers increased in thickness with depth, while the sand bodies reduced in thickness with depth which characterized the Abgada Formation of the Niger Delta. The effective porosities of the sands range from 21% 31%, the permeability ranges from 28% 44%, 70% 80% for the net to gross, volume of shale range from 14% 40% and hydrocarbon saturation ranges from 63% 82%. Twelve (12) faults were mapped within the study area and the structural styles revealed a fault assisted closures. The volumetric analysis showed that Sand F had Stock Tank Oil Initially In Place (STOIIP) of 5,050,000,000 bbls of oil and Sand G had STOIIP of 17,870,000,000 bbls, these sands are proposed How to cite this paper: Owolabi, A.O., Omang, B.O., Oyetade, O.P. and Akindele, O.B. (2019) Reservoir Evaluation and Volumetric Analysis of Rancho Field, Niger Delta, Using Well Log and 3D Seismic Data. Open Journal of Geology, 9, 974-987. https://doi.org/10.4236/ojg.2019.913100 Received: September 20, 2019 Accepted: December 24, 2019 Published: December 27, 2019 Copyright © 2019 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access A. O. Owolabi et al. DOI: 10.4236/ojg.2019.913100 975 Open Journal of Geology to be developd because of the volume of oil in them and area covered by the reservoir, calculated Gross Rock Volume (GRV) of 29.5 km and 104.5 km respectively.


Introduction
The search for hydrocarbon reservoir rocks is a goal in the exploration phase in the oil and gas industry. The exploration and production asset teams are faced with great challenges in predicting and making decisions on the life cycle of hydrocarbon bearing reservoirs. Accurate modeling of field scenarios is therefore needed before making decisions, as good decisions optimize hydrocarbon extraction and finally save precious time and capital. Earlier to decision making by the asset team some geologic exercises are carried out which include identifying and mapping structures and describing the stratigraphy of the economic hydrocarbon reservoirs. Some mathematic computations such as calculating for porosity, permeability, hydrocarbon saturation, net to gross ratio, oil in place, stock tank and volume of shale among others are done to evaluate prospective hydrocarbon bearing reservoirs.
The amount of oil in a subsurface reservoir is called oil in place (OIP) [1].
Only a fraction of this oil can be recovered from a reservoir. This fraction is called the "Recovery factor" [2]. The portion that can be recovered with improved technology is considered to be a potential. The portion that is not recoverable is not included unless and until methods are implemented to produce it [3]. Stock Tank Original Oil in Place (STOOIP) refers to the oil in place before the commencement of production, while Stock Tank Oil Initially in Place (STOIIP) is being referred to the volume of oil after production at surface pressure and temperature.
The enormous cost of exploration and production for hydrocarbon makes it a thing of necessity to strive for high level of perfection in the methods to be adopted for its detection and quantification. Also drilling time and cost-effectiveness are one of the driving factors in the oil and gas industry, interest in reservoir evaluation is being channeled towards qualifying and quantifying hydrocarbon reservoirs. This has been done to reduce the level of uncertainty associated with geological models. The integration of well log analysis and 3-D seismic interpretation are among the most efficient techniques and approaches that can be adopted to estimate the reserve of any hydrocarbon bearing field in the oil and gas industry for profitability and effective productivity in commercial quantity, the need for evaluating the reserve of the Rancho field hence this study.

Geology of the Study Area
Rancho field is located within the onshore Niger Delta. The Niger Delta is situated in the Gulf of Guinea and extends throughout the Niger Delta Province ( Figure 1). The Niger Delta province contains only one identified petroleum system, known as the Tertiary Niger Delta (Akata-Agbada) petroleum system [4] [5]. The Niger Delta has been the focus of hydrocarbon exploration since 1937. Now it is Africa's leading oil province. Today, the Niger Delta is covered with a dense grid of 2-D and 3-D seismic data and it has been penetrated by more than 5000 wells. Petroleum occurs throughout the Agbada formation of the Niger Delta. The Akata Formation is Paleocene in age. It is composed of thick shales, turbidite sands, and small amounts of silt and clay. Akata formation is formed during low stands in sea level and in oxygen deficient conditions. This formation is estimated to be up to 7000 meters thick. While the Agbada Formation dates back to Eocene. It is a marine facies with both freshwater and deep sea characteristics. This is the major oil and natural gas bearing facies in the basin. The hydrocarbons in this layer formed when this layer of rock became sub aerial and was covered in a swamp type of environment that contained lots of organics. It is estimated to be 3700 meters thick. The Benin Formation is Oligocene and younger in age. It is composed of continental flood plain sands and alluvial deposits.

Method of Study
The data used in this study consist of digital three-dimension seismic data and a suite of wire line logs consisting but not limited to Gamma ray, Deep Resistivity, Neutron and Density logs. The well logs were used to delineate the stratigraphic sections of the study area. The stratigraphic correlation of the four (4) wells was carried out by using gamma ray log and the deep resistivity log. Hydrocarbon bearing sands were identified and mapped as sections with low gamma ray reading and high resistivity log readings from the well section. A cross plot of the sands formation density and neutron logs were done for hydrocarbon typing.
Thereafter petrophysical analysis was calculated for the reservoirs of interest the parameters calculated for are as follows: Shale volume (Vsh) was estimated, using the [7] formula in Equation (1), which uses values from the gamma ray (GR) [8] in Equation (2).
For porosity values, Ø D was determined from [7] equation by replacing the bulk density readings gotten from the density log within each reservoir into the where ma ρ = matrix density, b ρ = formation bulk density and f ρ = fluid density.
Effective porosity formula is used to compute the effective porosity is shown below: where Vsh = volume of shale, total ∅ = total porosity, eff ∅ = effective porosity.
The effective porosity was recorded in percentage (%) by multiplying the value of effective porosity by 100 shown below: To calculate water saturation (Sw), the equation requires the determination of water resistivity (Rw) value at formation temperature calculated from the porosity and resistivity logs within clean water zone, using the Ro from the equation below: Water saturation (Sw) can be calculated using [9] equation.
where w R = water resistivity at formation temperature, wa R = water resistivity in the zone of interest.
Hydrocarbon Saturation (Sh) is the percentage of pore volume in a formation that is occupied by hydrocarbon. Sh can be determined by subtracting the value obtained for water saturation from 100% i.e.
( ) Permeability (K), of each identified hydrocarbon reservoir is calculated using Equation (7) where S wir is the irreducible water saturation [10] The petrophysical parameters of the delineated hydrocarbon bearing reservoirs were estimated using Equations (1)

Well Log Analysis and Correlation
The gamma ray log which is a type of lithology aided the litho-stratigraphic in- Open Journal of Geology tivity and low water saturation were mapped as sand lithology, which are also regions of high hydrocarbon saturation ( Figure 2). Hydrocarbon bearing sand units were delineated using the gamma-ray (GR) and resistivity logs to identify zones that are hydrocarbon bearing in all the wells studied. Nine (9) probable hydrocarbon bearing sand units (Sand A to Sand I) were delineated, all of which are laterally continuous (Figure 2). Sand A was observed to contain hydrocarbon due high resistivity signature in three wells (Rancho 1, 2 and 4), while the sand was interpreted to contain saline water in Rancho well 3 due to low resistivity signature reading. Sand B and Sand C were observed to contain hydrocarbon only in Rancho well 2 and interpreted wet in the other three wells (Rancho 1, 3 and 4) in the study (Figure 2).
Sand D was observed to be a thick sand unit ranging between 70 -81 meters and this sand was interpreted to be hydrocarbon bearing in only well Rancho 2.
Sand E contained hydrocarbon across two wells (Rancho 1 and 4). Sand F is hydrocarbon bearing as depicted by the high resistivity values in Rancho 1 and Rancho 2 respectively. Sand G is hydrocarbon bearing in Rancho wells 1, 2 and 4 due to high resistivity log reading in the sand zone and in Rancho well 3 the sand was interpreted to be water bearing due to low resistivity reading. Sand H was observed to contain hydrocarbon in all the four Rancho wells. Sand I was observed to be the thickest sand unit in the study area with reservoir thickness ranging from 101 -136 meters and this sand unit was interpreted to be hydrocarbon bearing in the four wells due to high resistivity reading from the sand units. A good lateral continuity was observed across the correlated sand units within the wells (Figure 2).

Fluid Differentiation
The fluids present in the identified hydrocarbon reservoir sands were differentiated using the resistivity and neutron-density combination logs. The resistivity   (Figure 3). When neutron-density logs are superimposed, the two curves will cross over in hydrocarbon zones. Gas is of higher density to oil therefore density log (black) deflect to the left and neutron (red) deflecting to the right showing a balloon shape for gas and linear cross over for oil (Figure 3).

Petrophysical Analysis
Petrophysical parameters were computed to characterize the nine (9) hydrocarbon reservoir sand units (Sand A to Sand I). The volume of shale, water saturation, hydrocarbon saturation, water saturation of the flushed zone, effective porosity, irreducible water saturation, effective permeability and bulk volume of water were computed for the nine reservoir sand units in Tables 1-9. The summary of the petrophysical parameters needed in the volumetric estimation was calculated in Table 10.

Seismic Interpretation
A total of twelve (12) faults were picked on the seismic sections. All the faults intersected the horizons of interest which are the tops of hydrocarbon bearing          sands of interest. The variance edge attribute was used to aid the interpretation of the faults. This attribute is also effective for detecting edge effects, channels, discontinuous features and to measure the continuity between seismic traces in a specified window. Fault polygon maps of the horizons were generated to show the distribution of faults and the structure trapping the oil in the field. Also, a depth structure map of the subsurface showed that the structure trapping the oil in the field is a fault assisted closures (Figures 4-7).

Volumetric Analysis
The stock tank oil initially in place (STOIIP) was estimated. The estimation was done for Sand A to Sand I, and the average porosity and oil saturation values for the sand units (Sand A -Sand I) were used in calculating the STOIIP (Table 11). Sand A was evaluated for STOIIP calculation with 980,000,000 mbls of oil present with porosity of 0.32 and oil saturation of 0.82. Sand B was estimated for Stock Tank Oil Initially in Place with 1,970,000,000 bbls of oil present with porosity of 0.32 and oil saturation of 0.78 (Table 11)

Conclusion
The litho-stratigraphic interpretation of well logs of the lithology within the area of study is mainly layers of sedimentary rock within the depth of 500 -3600 m depth and the wells exhibit a dominantly shale/sand/shale sequence, typical of the Niger Delta Formation. Gamma-ray (GR) and resistivity logs aided the identification of hydrocarbon bearing sand units in all the Rancho four (4) wells studied. Nine (9) probable hydrocarbon bearing sand units (Sand A to Sand I) were A. O. Owolabi et al.