Technological advancements in the exploration and production (E&P) of oil and gas have been on the increase worldwide in recent decades. Nigeria, being one of the major oil and gas producers in the world, has become a hub of international oil and gas investors since the early 1960s. Nigeria hosts more than 80 oil and gas companies in its upstream sector, including international oil companies (IOCs), indigenous oil companies (IndOCs), marginal-field operators (MFOs). and a national oil company (NOC). However, there is an increasing concern from policy makers over scanty quantitative information on the relative technical efficiency (RTE) of these operators for effective upstream performance analysis. This paper attempts to cover this gap by providing estimates of the RTE index for upstream operators in Nigeria from 2010 to 2016. An output-oriented data-envelopment-analysis (DEA) framework is adopted that is based on constant-return-to-scale (CRTS) assumptions. For a CRTS-DEA model (cDEA model), three input and two output variables were considered. Empirical results show that approximately 19% of the operators perform along the CRTS efficient-production frontier. Consequently, it is recommended that policy makers formulate upstream policies that encourage aggressive reserves growth and ensure an optimal reserves/production ratio.
This paper presents detailed theories and method of determining fault transmissibility and production history matching using the multi-tank material balance. This approach uses a two-step optimization process whose algorithm can be written as macros in spreadsheets. The upper-level (outer) stage optimizes the transmissibility and hydrocarbon initially-in-place while the lower-level (inner stage) optimizes the pressure of the support tank at each time step. This approach is validated using numerical simulation. This approach will be highly beneficial in effective reservoir management where little or no 3D seismic exists and for cases of sparse production data.
The need for operators of Oil and Gas assets to maintain depleting reserves have led to the development of new productive zones in mature fields. With new technology and improved understanding of the existing reservoirs, more discoveries within mature fields have been made requiring drilling activities to be performed below the existing mature fields. Drilling across previously produced intervals can be challenging as the depleted layers (or low pressure zones) have narrow margins between the pore pressure and fracture pressure gradients resulting in drilling problem as lost circulation.
To drill through such intervals successfully, loss prevention materials are incorporated in the drilling fluid as a preventive measure as against a corrective approach after experiencing losses. The sizing of loss prevention materials is however hinged on the accurate prediction of the induced fracture widths.
In this study, Artificial Neural Network (a subset of artificial intelligence) is utilised to construct a tool to predict the width of induced fractures and determine the sizing for loss prevention materials. The Artificial Neural Network (ANN) is trained and validated using a limited 30-point input data set. This resulted in a squared correlation of 79%. The results from the ANN is compared with existing 2D fracture models and benchmarked against experimental results published in literature.
The problems associated with oil production are assuming unprecedented proportion and complexity. As a field matures, with high water cut from wells, water breakthrough from water flood operations or other artificial pressure maintenance programs, water production and consequently, the produced fluid water cut and gas-oil ratio would be changing. As these fluids flow from the reservoir to surface facilities, the fluid is subjected to agitation and changes in temperature and pressure, which result in the precipitation of originally soluble substances in the crude to form emulsions, scales, hydrates, etc along the flowline. Although, the water content in the crude oil is reduced in the separators, a considerable amount enough to cause havoc is left behind in the crude and this could cause high transportation cost, as valuable transportation capacities will be occupied by valueless water. In many other instances, the separator fluid loading may exceed the original design capacity of the vessel resulting in poor oil and water effluent standards. This paper develops a procedure that describes the impact of crude oil emulsion on the efficiency of horizontal separators. The procedure can be used to monitor and optimize the operating conditions of horizontal separators to achieve good effluent qualities, thus providing a diagnostic tool to identify areas in the separation train that may be experiencing problems.
Insolubility challenges have reduced the efficiency and rate of environmental bioremediation of hydrophobic pollutants occurring in hydrocarbons, soil and water environments. As biosurfactants, sophorolipids possess the unique capacity of activity at the interface of immiscible liquids or solid-liquid phases, thus reducing surface and interfacial tensions through emulsification, dispersion, foaming and wetting, with advantages of stability, ecological acceptability and ability to be produced from renewable and cheaper substrates. In light of the above, this study was aimed at assessing the hydrocarbons emulsification and heavy metals detoxification efficiencies of sophorolipid biosurfactants produced from harvested mushrooms and yeasts isolated from a hydrocarbon contaminated site in Obohia, Abia State, Nigeria. Isolates were cultured on an optimized media fortified with agro-industrial waste substrates of rice bran and food industry waste oil as hydrophilic and hydrophobic sources of carbon, respectively. However sophorolipids production from the yeast, Candida bombicola, was confirmed by the emulsification index after 24 h, surface tension (ST), FT-IR spectroscopy and GC-MS analyses. Solubilization of selected hydrocarbons (used engine oil, kerosene, unused engine oil, diesel and crude oil) was observed with percentage emulsification activities at 60.7, 56.7, 46.9, 44.8 and 40.0 %, respectively. Furthermore, various concentrations of chromium, lead, zinc, copper and cadmium salt solutions incubated with culture supernatants of sophorolipids for 24 h were observed to remove 43.41% chromium from a 10mg/l salt solution and 23.11( Cr), 9.93 ( Pb), 7.29 (Zn), 4.96 (Cu) and 15.71 (Cd) from the highly toxic 70 mg/L salt solutions upon analysis via atomic absorption spectrometry. Our results indicate that sophorolipid biosurfactants could enhance the rate of bioremediation efficiency by emulsifying, solubilizing and detoxifying environmental contaminations of hydrocarbons and heavy metals respectively. Sophorolipids of agro-industrial waste origin possess good surface-active properties that can facilitate the solubilization, dispersion and desorption of hydrophobic environmental contaminants for microbial uptake and bioremediation.
Ikwan, Ukauku (Emerald Energy Institute) | Egba, Amba Ndoma (Department of Petroleum Resources) | Dosunmu, Adewale (University of Port Harcourt) | Iledare, Wumi (Emerald Energy Institute, University of Port Harcourt)
The primary objective of an E & P company is to drill and produce hydrocarbon at minimum cost with high level of safety without compromising environmental standards. With the current global downward slide in oil prices most E & P firms are slashing costs to shore up profitability. Drilling operations are high capital-intensive projects that drive unit production cost northwards. This paper presents a comparative analysis of drilling costs in three geographical locations of the world petroleum provinces viz; North Sea, Gulf of Mexico and Niger Delta with sensitivities of the various elements that affect drilling cost with a view to assisting operators and rig owners on optimizing activities in a lean environment.
Relying on panel data sourced from databases of a global energy consultant and industry operators, historical absolute average cost and footage trends were compared during the period of 10 years (2005-2014). A randomly selected well cost data was used to carry out the sensitivity analysis to deduce key determinants.
It was found that although there are regional differences that reflect the local geology and some economic factors, drilling times and all costs rise sharply with increasing depth. Also drilling cost for the Niger delta province is highest compared to the other two regions. The sensitivity study showed that the highest contributor to high drilling cost is the intangible element in which the rig rate, hole problems and security issues should be the focus in drilling cost reduction and economics. Contract renegotiation strategy to drive down rig rates and establish new market equilibrium is recommended in this lean environment. Also tangible costs from tubulars can be reduced with favourable policy on reviving Nigerian steel industries to enable local sourcing of these tubulars, improve employment rate hence reduce insecurity in the Niger Delta area.
Ramson, Enotoriuwa (African Centre of Excellence, University of Port Harcourt) | Oluchi, Nwachukwu Eunice (University of Port Harcourt) | John, Ugbebor (University of Port Harcourt)
This study assessed air quality in selected oil operating areas in Rivers State of Nigeria with consideration to land use type such as oil and gas facilities, major bus stops, schools, Markets, hospitals, residential areas, vegetation and commercial centers. Air quality and meteorological parameters across 25 locations were monitored during the wet season (April to October) 2015 to ascertain major air pollutant sources. The parameters monitored were, Nitrogen dioxide (NO2), Sulphur dioxide (SO2), Carbon ii oxide (CO), Volatile organic compounds (VOCs), particulate matter (PM) 1, PM2.5, PM4, PM7, PM10, TSP, wind speed, humidity and temperature. Descriptive statistics, agglomerative hierarchical cluster analysis (AHCA), Principal component analysis (PCA), Multiple linear regression (MLR) and Principal component regression (PCR) were used in the data analysis and modeling of Air quality index. Results showed that SO2 values ranged from 0.04 ppm to 0.15 ppm, NO2 values ranged from 0.025 ppm to 0.162 ppm, CO concentration ranged from 0.24 ppm to 6.36 ppm, VOC values ranged from 0.18 ppm to 2.19 ppm across all study locations. Particulate matter also varied across the study locations. Three clusters were obtained from AHCA. The dendogram plot from AHCA showed that the observed variation can be attributed to the land use pattern in the study area. Three principal components were extracted from the PCA based on eigenvalue of >1 and from the biplot after varimax rotation revealed that the major sources of air pollution in the area based on land use type are markets, major bus stops, residential and commercial centers. Vehicular emissions, biomass burning and dusty roads are the major sources of air pollution in the study area. MLR performed better than PCR with MLR and PCR having an R2 of 0.967 and 0.930 respectively. PCA, AHCA, MLR and PCR proved to be useful tools in air quality analysis for source apportionment and prediction as this can aid in air pollution abatement planning. There is need to improve existing policies in other to proactively mitigate the impacts of air pollution from oil and non-oil operation sources.
Drilling through shale formation can be challenging and sometimes results in wellbore instability problems due to the reaction between hydrophilic shale and drilling fluids. The typical low permeability of shale, the presence of ions and charged surface of the constituent clay are factors which makes the problem of wellbore instability very complex despite efforts dedicated to the study by researchers. The study of wellbore stability in shale is quite important because 75% of all formation drilled worldwide are shale formations and 90% of all wellbore instability problems occur in shale formations costing the industry more than $1 billion USD/year (Chenevert, 2002; Zeynali, 2012); the lost time due to this challenge also account for over 40% of all drilling related non-productive time (Zhang et al, 2009) and these instabilities are responsible for 10-20% of the total drilling cost. A solution through this challenge is critical to the sustenance of the investment made by operating companies in the oil and gas industry. This will drastically reduce drilling cost, completion and workover cost as well as the accompanying downtime involved. It will also improve the net present value of operating company in the industry. Basically wellbore instability occurs when the mechanical stress induced by drilling into the formation exceeds the formation rock strength. Chemical interactions between the drilling mud and the in-situ shale affect the in-situ stress state of the formation hence the stability of the formation. Geo-mechanical models have been designed to tackle mechanical wellbore instability in the Niger Delta the challenge therefore is a chemical solution to the wellbore instability problems of the region. Oil-based muds have been known to overcome wellbore stability problems, but disposal challenges and environmental concerns have led to infrequent use. The challenge therefore is to formulate an environmentally friendly drilling mud having the inhibitive properties to tackle the wellbore instability challenges. This paper presents a review of studies carried out to characterize the mineralogy of shales and the salinity distribution of formation water in the Niger Delta depobelts with a view of designing a "balanced-activity" drilling fluid to help stabilize the formation during drilling. Results obtained from the reviewed researches showed that shale mineralogy characterization and formation water salinity distribution is critical in designing a balanced-activity drilling mud that can effectively tackle the problems of wellbore instability.
Drillstring vibration has adverse effect on rate of penetration, causes equipment failure and increase in non productive time (NPT). In carrying out this research work on torsional and lateral vibrations of Polycrystalline Diamond Compact (PDC) bits in directional drilling, harmonic and modal finite element analyses were adopted for the obvious advantage that it is able to approximate the real structure with a finite number of degrees of freedom. The effect of weight on bit on rate of penetration, resonance, damping effect of drilling mud and friction between drillstring and the wellbore were analyzed. In the cause of the analysis, different critical load, critical speed for the finite element of the drillstring and the BHA and saturation points were developed for the different components of the drillstring from the Euler model to determine the crippling loads that will cause each component to buckle and propagate lateral and torsional vibration. The effect of angle inclination was also considered in the design of the vibration analysis model for directional wells application. A new concept, managing WOB while drilling was also advanced to avoid reaching the founder's point in real time drilling operation. The deductions and findings resulted in the development of a computer model, vibraCOM which detects, analyses and mitigates torsional and lateral drillstring vibrations realtime for practical applications. The results shows that it is better to drill below the critical speed of the finite elements of the drillstring and BHA to avoid resonance and to ensure the axial forces acting on the BHA is below the critical load.
Drilling activities have progressed to deep and ultra deep seas in recent times and with it comes more challenges. Due to the difficulty of directly obtaining important parameters like in-situ stress and fracture gradient, simple models have been evolved. This study is a novel attempt to make up for the gap inherent in such models namely that they neglect chemical and thermal effects, settling for only effective stress and a time-dependent analysis. The study applied the Neural Network (NN) technology to predict geomechanical parameters. Neural Network (NN) as a branch of Artificial intelligence (AI) possesses the ability of training available parameters to replace data that cannot be immediately or easily acquired. Data of a well drilled in the Niger Delta Region of Nigeria was used as the case study. A training set of input data was used to train the network and a validation set ensured a completely independent measure of network accuracy. A Neural Network model was developed in Neuroph Studio, Java neural network platform and the Netbeans IDE. The model has the advantage of being easy to use, open source, cross-platform and generally designed to save the cost associated with wellbore instability.