Petrophysical evaluation of reservoir sand bodies in Kwe Field Onshore Eastern Niger Delta

Asubiojo, T.M.; Okunuwadje, Sunday E.

doi:10.4314/jasem.v20i2.21

Cited by 6 publications

(8 citation statements)

References 8 publications

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“…Figures 1 and 2 show the geology and map of the studied location respectively. The geology of the subsurface of the location clearly shows that of hydrocarbon zone located in the Niger Delta region of Nigeria (Asubiojo and Okunuwadje, 2016). Well bored in the location enhances the procurement of geophysical wireline well logs used for this research (Aigbadon et al, 2022).…”

Section: Study Areamentioning

confidence: 94%

Assessment of Three Non-Linear Approaches of Estimating the Shale Volume Over Yewa Field, Niger Delta, Nigeria

Adepehin¹,

Magi²,

Omokungbe³

et al. 2022

USci

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Accurate shale volume estimation is an important approach in reservoirs characterization as it forms the basis upon which evaluators can ascertain the hydrocarbon content of the reservoirs. The porosity, gamma ray, neutron-density and deep induction logs data were used to arrive at suitable shale volume estimates of the field studied. Analysis of well logs data was done using the TECHLOG Exploration software. Delineation of reservoirs was carried out with OpendTect software. The Microsoft excel spreadsheet was utilized to accurately estimate other suitable petrophysical parameters such as the permeability, water saturation, hydrocarbon saturation and the porosity. Three different non-linear shale volume models, the Larionov, the Steiber and the Clavier models were used to determine the reservoirs’ shale content across three wells of Yewa reservoirs characterized by varying thicknesses. Variation in the depths down hole for each of the methods revealed that shale volume estimates with the Larionov model was determined across thickness 142.646 m with top and bottom depths of 1946.605 m and 2089.252 m respectively in well Y1, thicknes 90.678 m with top and bottom depths of 2164.690 m and 2255.368 m respectively in well Y2 and thickness 107.290 m with top and bottom depths of 2303.374 m and 2410.663 m respectively in well Y3. The estimates with Steiber model were respectively determined across thicknesses 85.649 m, 95.098 m and 121.371 m for Y1, Y2 and Y3 reservoirs, and top and bottom depths of 1947.571 m and 2033.219 m in well Y1, 2041.754 m and 2136.851 m in well Y2 and 2144.979 m and 2266.442 m in well Y3 and the one with Clavier model were respectively determined across thicknesses 146.456 m, 147.752 m and 94.869 m for Y1, Y2 and Y3 reservoirs and top and bottom depths of 1760.601 m and 1907.057 m in well Y1, 1920.312 m and 2068.068 m in well Y2 and 2078.812 m and 2173.681 m in well Y3. The lowest shale volume average estimate was recorded from the Larionov model. Nevertheless, one cannot conclude that the Larionov model is the most reliable as values obtained may be because of instability in the sensitivities of utilized well logs and the complexities in the properties of wells down hole. A further investigation of the sensitivities of the well logs and the down hole properties of the wells showed that the Larionov method gives reasonable, consistent, and repetitive intervals when compared with the Steiber and the Clavier models. The Larionov model is hereby recommended for use in the study area.

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Section: Study Areamentioning

confidence: 94%

Assessment of Three Non-Linear Approaches of Estimating the Shale Volume Over Yewa Field, Niger Delta, Nigeria

Adepehin¹,

Magi²,

Omokungbe³

et al. 2022

USci

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“…Lateral and vertical extents of pay zones are captured in the lithostratigraphic correlation. This is a major step in oil and gas exploration as it helps in the quantification of hydrocarbons [2], [3], [4], [13].Steps involved in Lithostratigraphic correlation include establishing of a reference datum which is a shale layer that is penetrated by all wells. Further establishment of a lithology presented in the wells using the gamma-ray logs.…”

Section: Lithostratigraphic Correlation Of Wellsmentioning

confidence: 99%

“…Density and neutron logs which are porosity logs (with the scale of the neutron log reversed relative to that of density) were co-plotted to discriminate reservoir fluids and estimate contact points between these reservoir fluids. [1], [2], [4], [14], [15]…”

Section: Fluid Contact Point Identificationmentioning

confidence: 99%

“…Consequently, the integration of sophisticated approachesis needed to understand reservoir and fluid properties that will promote higher production success rates [1], [2]. Reservoir Characterization is a method of integrating several qualities and quantities of data consistently to define reservoir properties of concentration in inter-well locations [2], [3], [4]. It is evaluated to understand the properties and efficiency of reservoirs.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Rock Properties Crossplot and Petrophysics for Enhancement of Litho-Fluid Discrimination and Compartmentalizationto Reduce Uncertainty and Mitigate Hydrocarbon Exploration Risk. ‘A Case of ‘NICK' Field, Onshore Niger Delta’.

Ojo,

Aham

2024

IJLTEMAS

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The main components of reservoir rocks are hydrocarbons and immiscible water in varying ratios. It is essential to precisely identify, characterize, and divide the fluids in these reservoirs into distinct groups according to the characteristics of their rock properties to conduct a successful hydrocarbon exploration. For this reason, petrophysics and rock physics analysis were combined on the "NICK" field in the onshore Niger Delta. Through precise litho-fluid discrimination in the field, this study seeks to improve field hydrocarbon production, lower uncertainty, and mitigate risks related to hydrocarbon exploration. The suites of well logs (Gamma-ray neutron, bulk density, sonic, and resistivity logs) from three wells—NICK-1, NICK-3, and NICK-6—make up the data used. Gamma-ray log signatures were used to identify and correlate lithologies throughout the field. Potential reservoirs and fluid content were identified and delineated by high resistivity and adequate neutron-porosity log signatures. Hydrocarbon-bearing sands were recorded at low values of elastic attributes (acoustic impedance, rigidity, incompressibility, and others), which were computed to aid in the characterizations. Two potentialreservoirs’ Sands A and B delineated, constituted the correlated pay zones observed in three wells across the field at depths ranging from 1986.24 to 2599.82m. Petrophysics results generally revealed fair to good porosities of (11-25%) for easy accumulation of hydrocarbon. Permeability ranged from 210- 809mD for Sand A and 27 – 887mD for Sand B, showing that there are suitable permeabilitiesfor fluid movement/migration within the reservoirs. Cross plot of Lambdarho versus Murho, Lambdarho versus Velocity Ratio, and Velocity Ratio versus Acoustic Impedance gave four distinct clusters for litho-fluid zones identification given as gas-sand, oil-sand, brine-sand, and shale. This study has assisted in better characterization and distinguishing of the litho-fluid details for enhancement of hydrocarbon production in the field.

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“…[20] used well logs and 3D seismic to evaluate the hydrocarbon trapping potential and 3D structural analysis of subsurface structures of Otu Field, Niger Delta with the aid of the log data, network of faults, horizon delineation, and extraction of the RMS amplitude which shows that field contains hydrocarbon economically. [21] predicted the reservoir system quality at Kwe field Niger delta and identified its depositional environment using the petrophysical properties of the reservoir and well-log data. He identified 7 reservoirs in the Kwe field.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Hydrocarbon Potential Using AVO Analysis in the FORMAT Field, Niger Delta Basin, Nigeria

Ugbor,

Onyeabor,

Ugwuoke

2024

OJG

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The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 -10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 -1.6 g/cc), pure oil (2.3 -1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to -1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.

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Petrophysical evaluation of reservoir sand bodies in Kwe Field Onshore Eastern Niger Delta

Cited by 6 publications

References 8 publications

Assessment of Three Non-Linear Approaches of Estimating the Shale Volume Over Yewa Field, Niger Delta, Nigeria

Assessment of Three Non-Linear Approaches of Estimating the Shale Volume Over Yewa Field, Niger Delta, Nigeria

Integration of Rock Properties Crossplot and Petrophysics for Enhancement of Litho-Fluid Discrimination and Compartmentalizationto Reduce Uncertainty and Mitigate Hydrocarbon Exploration Risk. ‘A Case of ‘NICK' Field, Onshore Niger Delta’.

Evaluation of Hydrocarbon Potential Using AVO Analysis in the FORMAT Field, Niger Delta Basin, Nigeria

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