DEPARTMENT OF PETROLEUM ENGINEERING

Gas condensate is very important reservoir fluid because it is made up of a mixture of low density mixture of hydrocarbon in which during processing it yields other products like associated dry gas and also creates condensate oil after being extracted. A condensate reservoir exhibits a unique characteristic which make it special and at the same time difficult to recover due to liquid banking which is formed as a result of pressure and temperature change during production. In other to optimize production in a gas condensate reservoir proper attention must be paid to its phase behavior.The objective of this study is to model a gas condensate reservoir. The approach used in this study is the compositional analysis (the use of software) to determine the components of the gas condensate and compared with experimental approach which involve constant composition expansion (CCE) test and constant volume depletion (CVD) test. CCE provides information about the dew point, relative volume of fluid and condensate liquid while CVD provides information about condensate oil saturation and condensate oil and gas recovery. Finally the empirical method which is the equation of state model (EOS) using a simulation software to match the results gotten from the different approaches. The result of the study from compositional analysis simulation shows that the P-T diagram of critical pressure, temperature can be constructed and its results shows that composition significantly varies as a function of fluid phase behavior and also affects the producing sequence of a condensate reservoir. It as well pointed out the need to conduct more studies on characterization in other to be able to make the best recovery choice for optimal production from a gas condensate reservoir

The accuracy and reliability of flow measurement play a vital role in process industries, particularly in petroleum engineering, where precise monitoring of fluid transfer is essential for operational control and financial accountability. This study investigates the effect of temperature on the repeatability of flow meters, focusing on how variations in thermal conditions influence meter performance and measurement consistency. Experimental tests were conducted using standard flow metering systems at controlled temperature ranges. The results revealed that temperature fluctuations significantly affect flow meter readings, primarily due to changes in fluid properties such as density and viscosity, as well as thermal expansion of meter components. These variations lead to slight
deviations in output signals, thereby reducing measurement repeatability when temperature compensation is not applied. Statistical analysis, including Analysis of Variance (ANOVA), confirmed that temperature has a measurable impact on flow meter stability across repeated trials. The findings highlight the importance of temperature correction, regular calibration, and proper material selection in ensuring accurate and repeatable flow measurements. This study contributes to improved metering practices and supports the development of more
reliable flow

This study investigates the dimensionless pressure and pressure derivative responses of a horizontal well within a reservoir characterized by inclined impermeable boundaries. Horizontal wells have gained prominence in recent years due to their potential to enhance hydrocarbon recovery from unconventional reservoirs. However, their behavior in reservoirs with nonconventional boundaries remains less understood. In this research, we employ analytical and numerical techniques to model the pressure and pressure derivative responses of a horizontal well situated in such a reservoir. By utilizing dimensionless
analysis, we aim to generalize the findings across various reservoir conditions and well geometries. The influence of inclined impermeable boundaries on well performance is examined, considering
factors such as boundary angle, reservoir anisotropy, and wellbore inclination. Through comprehensive simulations and sensitivity analyses, key insights into the behavior of horizontal wells in reservoirs with inclined impermeable boundaries are elucidated. The derived
dimensionless pressure and pressure derivative solutions provide valuable tools for reservoir
engineers to optimize well design and production strategies in such challenging environments. This study contributes to a deeper understanding of the complex interactions between wellbore
geometry, reservoir boundaries, and fluid flow dynamics, paving the way for more efficient exploitation of hydrocarbon resources in unconventional reservoirs.

Due to the general increase in the usage of petroleum resources, drilling of oil wells are frequently done in very challenging and hostile settings. Loss of circulation has been one of the main challenge facing engineers during drilling operations. Hence there have been extensive researches done over the years in order to minimize the impact of loss circulation, however, this have led to a myriad of viewpoints as to what product and method is suitable to battle it. However, a lot of the products and guidelines available for battling lost circulation are often biased towards self-promotion for a particular service company. The purpose of this study is to develop practical guidelines that are universal and not biased towards any particular service company product and which will also serve as a reference guide for lost circulation prevention and control at the well-site for drilling personnel

Type curves come in handy when our pressure buildup and pressure drawdown analysis do not yield a straight line hence generating a master curve for wells completed within a pair of sealing faults. The type curves from an observed data is superimposed on the master curve to estimate reservoir system properties. A sealing fault creates image wells, which communicate with each other and the object well. As a result, object well performance can be affected by reservoir boundaries, and positioning of a well therefore must be strategic to ensure oil production for a long time. This is because pressure drop across the producing well is the addition of the pressure drop of the object well and the several image wells created because of the inclination. This is the principle of superposition. The inclination of a sealing fault influences the number of image wells, n, with the model n = (360/) -1. With different angles of inclination of the sealing faults, polygons are constructed to determine the distances between the object well and corresponding image wells. In this paper, both dimensionless pressure and dimensionless pressure derivatives type curves as functions of number of image wells, are produced assuming that a vertical well is completed within a pair sealing faults. Wellbore storage and skin effects are considered. The results provide distances for several angles of inclination. Object well design, image well distances and faults angle affect dimensionless pressure and dimensionless pressure derivative. Dimensionless pressure and dimensionless pressure derivative of 1.1513(n+1) per cycle and 0.5(n+1), respectively are observed. Generating dimensionless pressure derivative curves helps the engineer to identify the point where the hump expires and where the straight-line analysis begins. That is the right point for well test analysis.

This chapter deals with compositions for drilling muds and special chemical used for drilling muds. Drilling fluids are mixtures of natural and synthetic chemical compounds used to cool and lubricate the drill but, clean the hole bottom, carry cuttings to the surface, control formation pressures, and improve the function of the drill string and tools in the hole. Drilling muds are divided into two general types: water-based drilling muds and oil-base drilling muds. Each type needs special additives which are discussed in this chapter.
The type of fluid base used depends on drilling and formation needs, as well as the requirements for disposition of the fluids after it is no longer needed. Drilling muds are special class of drilling fluids used to drill most deep wells.

Predicting the subsurface temperature distribution within sedimentary and petroleum‐bearing formations is essential for accurate hydrocarbon maturation modeling, well‐bore stability, and drilling‐fluid design. Traditional approaches—relying on sparse bottom‐hole temperature (BHT) measurements and one‐dimensional conductive models—often misestimate true formation
temperatures by 5–10 °C in heterogeneous settings such as the Niger Delta. To address these limitations, this study develops a data‐driven workflow that employs machine learning algorithms trained on routinely acquired drilling logs to produce continuous, high‐resolution temperature profiles. First, we assembled a dataset from Niger Delta wells comprising wireline logs (gamma‐ray, four‐pad resistivities, density, neutron porosity, sonic velocity), drilling parameters (equivalent circulating density, rate of penetration, exposure time), and corrected BHT readings. After replacing sentinel values (–9999) with NaNs and depth‐referencing all curves to true vertical depth (TVD), each log was clipped to its 1st–99th percentile range to mitigate extreme outliers. Features were standardized to zero mean and unit variance. Derived attributes—such as depth‐derivatives and moving‐window averages—were also explored to enhance lithofacies and thermal signal detection. We compared three regression models: a multilayer perceptron neural network (ANN), a Random Forest (RF) ensemble, and Support Vector Regression (SVR). Hyperparameters were tuned via grid search with k-fold cross‐validation, and models were evaluated on a hold‐out subset (20 % of depths). Error metrics (RMSE, MAE, R²) and well‐log–style scatter and depth‐track plots quantified predictive performance and bias. The ANN achieved an RMSE of 0.16 °F and R² = 0.97, producing smooth temperature gradients. The RF delivered an RMSE of 0.25 °F and R² = 0.985, with feature‐importance analysis highlighting mid‐pad resistivities and drilling parameters as primary predictors. SVR, with an RMSE of 0.47 °F and R² = 0.955, was less competitive but still captured over 95 % of temperature variance. Well‐log plots demonstrated that both ANN and RF closely track actual temperature profiles across lithologic transitions. This end‐to‐end pipeline—from data cleaning and feature engineering to model training, validation, and interpretation—demonstrates that machine learning can offer accurate, cost‐effective alternatives to physics‐based thermal models. Future work will explore hybrid physics–ML models, temporal drilling‐data integration, expanded feature fusion (e.g; seismic attributes), and explainable‐AI techniques, with the goal of operationalizing these tools in real‐time drilling workflows

With a variety of EOR methods explored, the discovery is in tune with Low-salinity water Injection (LSW) as a promising enhancement of the rate at which oil is recoverable from the reservoir. However, the comprehensive understanding of the principal mechanism directing this technique, has not been fully harnessed, causing the difficulty of creating the most favourable salinity condition, and the ionic formation, required for the injected solution. However, a wider school of thought holds that, the driving mechanism in LSWI of the carbonate’s reservoir, is vast. Though, the modification in wettability is seen as the primary mechanism driving oil to a more recoverable state, with most literature review proving this, how it works is up for a good intelligent discuss. This literature attempts to reviews a variety of working states of LSWI, from studies, field investigations, as well as individual recommended mechanisms affecting the oil–rock–brine contact interfaces. Furthermore, the uniqueness of this project, is to provides an extensive evaluation of previous treatises, on LSWI in carbonate reservoirs, the analyses, applications, as well as achievements that have given ground for a mastery of the difficulty of the multicomponent systems and the potential benefits it has on the oil production industry

Drilling mud, also known as drilling fluid, is a vital component in the oil and gas industry. As the primary medium for drilling oil and gas wells, its importance cannot be overstated. However, in Nigeria, the procurement of drilling mud is often costly, as the required materials for its formulation are largely imported. This project investigates the suitability of a locally sourced clay, Iyi−Ogene, obtained from one of Nigeria’s numerous clay deposits, as a potential substitute to imported bentonite in drilling
mud formulation. The study aims to promote local material utilization, reduce import dependency, and minimize overall operational costs. Guided by API specifications, rheological properties of the local clay were determined upon preparation using standard procedures. Additionally, carboxymethyl cellulose (CMC) was incorporated to some samples to enhance performance toward API standards. The results indicate that the local clay possesses promising potential for drilling mud formulation, provided adequate beneficiation and optimization of activation conditions are applied. The findings also emphasize the importance of maintaining optimal base concentration during chemical activation, as excessive amounts may yield adverse effects. Overall, this laboratory−based study demonstrates that certain local clays, when properly treated and modified with suitable additives, can perform comparably to imported bentonite. It further underscores the need for field−scale evaluation to validate laboratory results and support the wider adoption of local materials in drilling fluid formulation.

Drilling mud, otherwise known as drilling fluid, is a vital component in the oil and gas industry. As the primary medium for drilling oil and gas wells, its importance cannot be overstated. However, in Nigeria, the procurement of drilling mud is often costly, as bentoniteclay, the conventional material used in its formulation is largely imported. This project investigates the suitability of a locally sourced clay, Okuaghe, obtained from one of the countries numerous clay deposits, as a potential substitute for imported bentonite drilling mud formulation. The study aims to promote local material utilization, reduce import dependency, and minimize overall operational costs. The clay sample was collected from Uhunmwonde local government area in Edo State, then prepared through drying, crushing, and sieving. Portions of the total sample were activated using soda ash (sodium carbonate) to enable comparative analysis. Guided by API specifications, rheological properties such as plastic viscosity, apparent viscosity, yield point and gel strength were determined using standard procedures. Additionally, carboxymethyl cellulose (CMC) was incorporated in some samples to enhance performance toward API standards. The results indicate that the local clay possesses promising potential for drilling mud formulation, provided adequate beneficiation and optimization of activation conditions are applied. The findings also emphasize the importance of maintaining optimal base concentration during chemical activation, as excessive amounts may yield adverse effects. Overall, this laboratory-based study demonstrates that certain local clays, when properly treated and modified with suitable additives, can perform comparably to imported bentonite. It further underscores the need for field-scale evaluation to validate laboratory results and support the wider adoption of local materials in drilling fluid formulation