Role of high-density brines in reservoir development stages:A review

High-density brines have been recognized beneficial for oilfield applications,with various key areas such as drilling,completion and formation evaluation.High-density brines can play a critical role in the development and production of oil and gas reservoirs during the primary,secondary,and tertiary recovery phases.High-density brines can enhance the mobility and recovery of the oil in the reservoir by controlling the density and viscosity.However,a less attention has been given to the application of high-density brine in the area of reservoir development.This review is shedding light on a concise overview of reservoir development stages in association with the recovery mechanisms.In addition,most possible applications of high-density fluids have also been reviewed in the field of the reservoir development.In summary,this review state that high-density brines can be used to stimulate reservoirs by hydraulic fracturing during the primary recovery phase.However,the risk of increased interfacial tension,which relies on the density difference of two fluids,can trap more residual oil relative to conventional water flooding.In addition,high-density brines are effective in decreasing the mobility ratio and facilitating favorable displacement during polymer flooding.However,they can be least effective in alkaline flooding due to the high IFT related to large density differences.Thus,it is suggested to consider the utilization of sustainable high-density brines by taking into account effective factors in petroleum engineering aspects such as stimulation,secondary recovery and polymer flooding.

Biogas Production from the Co-Digestion of Cornstalks with Cow Dung and Poultry Droppings

The Anaerobic digestion of Corn Stalk (CS) with Cow Dung (CD) and Poultry Droppings (PD) was investigated. Batch mono-digestion and Co-digestion experiments were performed with initial total solid loading of 37.5%. The main objective of this work was to investigate the biogas yield at different CS to CD ratios and CS to PD ratios. Results show that the highest Cumulative Gas Yield (CGY) of 6833 mL/g of biomass was achieved in 21 days for CS-CD ratio of 2:1. Similarly high CGY of 6107 mL/g, 6100 mL/g and 5333 mL/g were obtained for CS-PD ratio of 2:1, CS-CD ratio of 1:1 and CS-PD ratio of 1:1 respectively. It is concluded that co-digestion of Cow dung or poultry droppings is beneficial for improving bio-digestibility and Biogas yield from corn stalk. The results of this work provide useful information to improve the efficiency of co-digestion of CS with CD and PD under anaerobic conditions.

Emerging applications of nanomaterials in chemical enhanced oil recovery:Progress and perspective

In enhanced oil recovery,different chemicalmethods utilization improves hydrocarbon recovery due to their fascinating abilities to alter some critical parameters in porous media,such as mobility control,the interaction between fluid to fluid,and fluid to rock surface.For decades the use of surfactant and polymer flooding has been used as tertiary recovery methods.In the current research,the inclusion of nanomaterials in enhanced oil recovery injection fluids solely or in the presence of other chemicals has got colossal interest.The emphasis of this review is on the applicability of nanofluids in the chemical enhanced oil recovery.The responsiblemechanisms are an increment in the viscosity of injection fluid,decrement in oil viscosity,reduction in interfacial and surface tension,and alteration of wettability in the rock formation.In this review,important parameters are presented,which may affect the desired behavior of nanoparticles,and the drawbacks of nanofluid and polymer flooding and the need for a combination of nanoparticles with the polymer are discussed.Due to the lack of literature in defining the mechanism of nanofluid in a reservoir,this paper covers majorly all the previous work done on the application of nanoparticles in chemical enhanced oil recovery at home conditions.Finally,the problems associatedwith the nano-enhanced oil recovery are outlined,and the research gap is identified,which must be addressed to implement polymeric nanofluids in chemical enhanced oil recovery.

Permeability prediction using hydraulic flow units and electrofacies analysis

It is essential to characterize fluid flow in porous media to have a better understanding of petrophysical properties.Many approaches were developed to determine reservoir permeability among which the integrated analysis of hydraulic flow unit(HFU)and electrofacies(EF)is considered to be useful one.However,the application of HFU and EF analysis has not been totally understood with a limited data to develop correlation for less distance offset wells.In this study,an attempt was made to show the application of integrating HFU and EF for reliable estimation of permeability using core and wireline log data in one of the gas fields in Pakistan.The results obtained indicate that the integrated approach proposed in this study can be used,especially in less distance offset wells when a limited number of data are available for petrophysical characterization.

Nigerian Biomass for Bioenergy Applications:A Review on the Potential and Challenges

Nigeria,often referred to as“the giant of Africa,”boasts a sizable population,a thriving economy,and abundant energy resources.Nevertheless,Nigeria has yet to fully harness its renewable energy potential,despite its enormous capacity in this field.The goal of this review paper is to thoroughly examine the difficulties and untapped opportunities in utilizing biomass for bioenergy production in Nigeria.Notably,Nigeria generates substantial volumes of biomass annually,primarily in the form of agricultural waste,which is often either discarded or burned inefficiently,resulting in significant ecological and environmental damage.Therefore,an efficient approach to reducing pollution and transforming waste into wealth involves converting these biomass resources into energy.This work critically examines the status of biomass utilization for energy applications in Nigeria and highlights the bottlenecks that impede its widespread adoption.The review emphasizes the economic and ecological advantages of biomass utilization over traditional waste treatment methods.Additionally,it underscores the appeal of biomass as an industrial fuel source,particularly considering the current high cost of fossil fuels in contemporary Nigeria.Relevant literature on biomass,energy,agricultural waste,fossil fuel,and calorific value in the context of Nigeria was reviewed by utilizing a thorough search technique in key scientific databases.The analysis did not include any non-English publications.The findings of this research provide valuable insights into the challenges faced in maximizing Nigeria’s biomass potential and offer strategic recommendations to promote the use of biomass for bioenergy development.This review paper will assist a wide range of local and international readers,as well as industries interested in green and bioenergy,in making informed decisions regarding the most suitable types of biomass for biofuel production.

Effect of Different Etching Time on Fabrication of an Optoelectronic Device Based on GaN/Psi

Gallium nitride(GaN)/porous silicon(PSi)film was prepared using a pulsed laser deposition method and 1064 nm Nd:YAG laser for optoelectronic applications and a series of Psi substrates were fabricated using a photoelectrochemical etching method assisted by laser at different etching times for 2.5–15 min at 2.5 min intervals.X-ray diffraction,room-temperature photoluminescence,atomic force microscopy and field emission scanning electron microscopy images,and electrical characteristics in the prepared GaN on the Psi film were investigated.The optimum Psi substrate was obtained under the following conditions:10 min,10 mA/cm^(2),and 24%hydrofluoric acid.The substrate exhibited two highly cubic crystalline structures at(200)and(400)orientations and yellow visible band photoluminescence,and homogeneous pores formed over the entire surface.The pores had steep oval shapes and were accompanied by small dark pores that appeared topographically and morphologically.The GaN/Psi film fabricated through PLD exhibited a high and hexagonal crystallographic texture in the(002)plane.Spectroscopic properties results revealed that the photoluminescence emission of the deposited nano-GaN films was in the ultraviolet band(374 nm)related to GaN material and in the near-infrared band(730 nm)related to the Psi substrate.The topographical and morphological results of the GaN films confirmed that the deposited film contained spherical grains with an average diameter of 51.8 nm and surface roughness of 4.8 nm.The GaN/Psi surface showed a cauliflower-like morphology,and the built-in voltage decreased from 3.4 to 2.7 eV after deposition.The fabricated GaN/Psi film exhibited good electrical characteristics.

Synthesized graphene oxide and fumed aerosil 380 dispersion stability and characterization with partially hydrolyzed polyacrylamide

Hydrolyzed polyacrylamide(HPAM)is a commonly used polymer for the chemicals,mining and refining processes of hydrocarbon but suffers from a persistent high-temperature instability problem.In contrast,the nanoparticle suspension remains a technical challenge because of the strong interactions of van der Waal forces within nanoparticles,which always encourage aggregation.This research sought to improve nanoparticles(NP)stability and polymer(HPAM)rheological properties to improved hydrocarbon recovery by utilizing synthesized graphene oxide(GO)nanosheets and fumed Aerosil 380 Silica oxide(SiO_(2)).The aqueous nanocomposites based on HPAM-GO and HPAM-SiO_(2) in aqueous polymeric solutions have been developed,and its viscoelastic and static behaviour is studied.The results imply that by adding fumed silica NP,the viscoelastic behaviour of HPAM is marginally improved,particularly in high temperatures and salinity,however,the inclusion of GO's significantly improves the viscosity and stability of the base polymer fluid at high temperatures.The Fourier data for the transformation of the infrared spectrum confirmed that the hydrogen bonding formed between HPAM carbonyl groups and silica NP surface silanol functionality and covalent interlinking of electrostatic h-bonding between HPAM and functional GO contributed to the improved stabilization and improved rheological performance that helps to recover high salinity and temperature hydrocarbons.

Studies on the Effects of Bentonite (Nanoclay) on the Mechanical Properties of High-Density Polyethylene

In this work, the effect of Bentonite (Nanoclay) on the mechanical and mor-phology properties of HDPE/Nanoclay composite pipe material was investi-gated. This led to the development of a composite material with improved me-chanical properties. The HDPE/nanoclay composites were produced using an injection moulding machine at 200?C and rotor speed of 50 rpm. The compati-bilizer used in this study was Polyethylene-graft-Maleic Anhydride. Different compositions of nanoclay reinforcements were prepared and added to HDPE resin. A particle size of 425 μm was used in proportions of 0%, 5%, 10%, 15%, and 20% on weight fraction basis. All the composites samples were characterized by Zwick Roell tensile testing machine and Scanning Election Microscopy (SEM). Experimental results obtained showed improvements in the tensile strength, and modulus at the expense of elongation. The maximum tensile strength and modulus was obtained at 10% filler composition. These enhanced properties are due to the homogenous dispersion of nanoclay in HDPE matrix, which is evident from the structure that was evaluated using SEM.

Methane and Hydrogen Storage in Metal Organic Frameworks: A Mini Review

The need for a net zero carbon emission future is imperative forenvironmental sustainability hence, intensive carbon fuels would need tobe replaced with less carbon emitting energy sources such as natural gastill clean energy source such as hydrogen becomes commercialized. Asa result, this mini review discusses the use of metal organic framework(MOF) for adsorption of methane and hydrogen in specially designed tanksfor improved performance so as to increase their applicability. Herein,adsorption (delivery) capacity of selected high performing MOFs formethane and hydrogen storage were highlighted in reference to the targetsset by United States Department of Energy’s Advanced Research ProjectsAgency-Energy (ARPA-E) and Fuel Cells Technology Office. In thisregard, specific design and chemistry of MOFs for improved methane andhydrogen adsorption were highlighted accordingly. In addition, an overviewof computational and molecular studies of hypothetical MOFs was done- the various approaches used and their proficiency for construction ofspecific of crystalline structures and topologies were herewith discussed.

Estimating Volume of Shale in a Clastic Niger Delta Reservoir from Well Logs: A Comparative Study

The volume of shale (Vsh) is a critical parameter in petrophysical analysis that enables the accurate estimation of other petrophysical parameters like effective porosity, saturation and Net-to-Gross. This is an important step in characterization of reservoirs as well as valuation of hydrocarbon potentials. GR (Gamma Ray), Neutron and Density as well as Potassium, Uranium and Thorium logs were adopted to estimate and analyze Vsh for sand 4 reservoir interval across five wells using the empirical (GR-linear and non-linear) and Neutron-Density methods. Results show that Vsh estimated by the different methods varied from 0.24 - 0.39 for the GR linear method (highest), 0.12 - 0.24 for the Larionov method (intermediate), and 0.04 - 0.28 for the Neutron-Density method (lowest). Although the Neutron-Density method gives the lowest values of volume of shale, this does not translate to the most accurate and reliable results. This may be attributed to the non-singularity in measurements and varying sensitivities of the well logs used in this method as well as the complexities of the wellbore condition. The GR non-linear (Larionov) method provides consistent and comparable volume of shale estimations with the neutron-density method than the linear GR method and consequently, the non-linear GR method is recommended for estimation of Vsh in the studied field.

Iso-propyl caprylate and iso-propyl linolenate synthetic fluids as novel alternatives in deep-water drilling operations:Critical fluid properties and aerobic biodegradability assessments

Present drilling fluids for deep water wells have severe degenerative effect on the environment with high operational and disposal costs.Thus,making them less desirable in recent times.Ester synthetic drilling fluid provides a novel environmentally friendly alternative but conventional ester-based drilling fluids exhibit high viscosities in deep-water wells causing excessive equivalent circulating density(ECD)and increased risk of lost circulation owing to narrow mud density window.This study experimentally investigates the critical fluid properties and aerobic biodegradability potentials of two newly developed deep-water synthetic ester drilling fluids namely:iso-propyl caprylate(COIPE)and iso-propyl linolenate(LOIPE)synthetic fluids and their comparison with synthetic-paraffin(SP-SBF)and isomerized-olefin(IOSBF)synthetic hydrocarbon fluids.The esters of iso-propyl caprylate and iso-propyl linolenate were produced from the isolation of ester mixtures that were obtained from the homogeneous catalytic transesterification of coconut and linseed plant oil biomass respectively.The COIPE was isolated from the coconut oil iso-propyl ester mixture by low-pressure fractional distillation technique.While fractional distillation and crystallization were used to isolate the LOIPE ester from the linseed oil iso-propyl ester mixture.Meanwhile,the aerobic biodegradation investigation was conducted by a modified oxygen consumption respirometry technique.The GC-MS analysis of the COIPE and LOIPE showed that the former contains essentially of lower saturated carbon compounds(C8).Whereas the latter contains higher molecular weight and unsaturated carbon compounds(C18+).The COIPE and LOIPE kinematic viscosity values are in good agreement with that of the reference synthetic hydrocarbon fluid samples(SP-SBF and IO-SBF).Although,the COIPE synthetic ester has lower viscosity value owing to the presence of shorter chain and saturated carbon atoms(C8 esters).Similarly,the linolenic oil iso-propyl ester has excellent cold flow characteristics for deep-water well drilling owing to lower values of cloud and pour points as a result of higher concentration of poly-unsaturated linolenic esters.The iso-propyl caprylate and the iso-propyl linolenate ester synthetic fluids are readily biodegradable in the sea water inoculum under aerobic condition.However,the iso-propyl caprylate is inherently biodegradable because its degradation level and that of the reference chemical sample were already above 60%during the 10-day window period.The SP-SBF and the IO-SBF synthetic fluids have lower aerobic biodegradation values because they contain little quantity of poly aromatic hydrocarbons as evident in their GC-MS profiles.Finally,esters and unsaturated synthetic-based fluid are more rapidly biodegradable than paraffinic synthetic fluids and the rate of biodegradation of organic compounds decreases as molecular weight increases.

Evaluation of influential parameters for supersonic dehydration of natural gas: Machine learning approach

The supersonic dehydration of natural gas is gaining more attention due to its numerous advantages over the conventional natural gas dehydration technologies.However,supersonic separators have seen minimal field applications despite the multiple benefits over other gas dehydration techniques.This has been mostly attributed to the uncertainty in ascertaining the design and operating parameters that should be monitored to ensure optimum dehydration of the supersonic separation device.In this study,the decision tree machine learning model is employed in investigating the effects of design and operating parameters(inlet and outlet pressures,nozzle length,throat diameter,and pressure loss ratio)on the supersonic separator performance during dehydration of natural gas.The model results show that the significant parameters influencing the shock wave location are the pressure loss ratio and nozzle length.The former was found to have the most significant effect on the dew point depression.The dehydration efficiency is mainly dependent on the pressure loss ratio,nozzle throat diameter,and the nozzle length.Comparing the machine learning model-accuracy with a 1-D iterative model,the machine learning model outperformed the 1-D iterative model with a lower mean average percentage error(MAPE)of 5.98 relative to 15.44 as obtained for the 1-D model.

A delayed royalty framework for investments in the exploration and production of hydrocarbon

The nature of oil and gas Nation's petroleum fiscal system affects the survival of exploration and production(E&P)companies during periods of low oil price as these companies are expected to pay royalty to the government irrespective of the price of oil.This affects the sustainability of E&P companies during periods of low oil price.There is the need to design a petroleum fiscal systems that increases the chances of survival of firms during periods of low oil price.This research therefore considered the economic analysis of a delayed royalty framework for investments in the exploration and production of hydrocarbon.The delay in royalty payment was hinged as a function of the time it takes the contractor to recoup his investment capital.Three economic models for petroleum investment in an onshore oil field were built.Royalty rate in the models was varied between 0 and 30%and oil price was also varied between$30-$120/bbl.Model 1 was the base case model with zero royalty payment.While model 2(Scenario 1)had royalty payment.Model 3(Scenario 2)had a delayed royalty payment.Risk analysis was also carried out to see how the delayed royalty framework increases the sustainability of E&P firm using@Risk software.It was observed that the delayed royalty framework increases the chances of survival of firms as the NPV for Scenario 2 was positive but without the framework,it was negative at an oil price of$30/bbl.The payout period,government and contractor's take and the internal rate of return also show that the delayed royalty framework will increase the chances of a firm's survival during periods of low oil price.It is seen that the delayed royalty framework is another way to make a petroleum fiscal system progressive aside the already known factors used globally.

Assessment of parameters effectiveness in the reserve estimation methods applicable to coal bed methane reservoirs

The reserve estimation of coal bed methane(CBM)reservoirs is ascertained through the analytical methods(volumetric method,material balance equation and decline curve analysis).However,the adoption of reserve estimation methods depends on exploration stage and availability of the required parameters.This study deals with the analytical assessment of parameters that participate in effecting the reserve estimation of CBM reservoirs through the analytical techniques.The accurate measurement challenges always exist for the parameters which participate in the reserve estimation of the conventional and unconventional reservoirs because of the inclusion of limitations while measurement.Therefore,the impact of that measurement challenge must be assessed.The study specifies the impact of parametric change on the reserve estimation of CBM reservoirs so that the degree of parametric effectiveness is analyzed.Uncertain values are adopted which are associated during the evaluation of input parameters for each method to determine the overall impact on potential of CBM reserves.Results reveal that change in specific parameters considering each method provide relatively more effect on estimation of reserves.Thus,the measurement of parameters must be done accurately for assessing reserves of CBM reservoirs based on available methods.

Applicability of deep neural networks for lithofacies classification from conventional well logs: An integrated approach

Parametric understanding for specifying formation characteristics can be perceived through conven-tional approaches.Significantly,attributes of reservoir lithology are practiced for hydrocarbon explora-tion.Well logging is conventional approach which is applicable to predict lithology efficiently as compared to geophysical modeling and petrophysical analysis due to cost effectiveness and suitable interpretation time.However,manual interpretation of lithology identification through well logging data requires domain expertise with an extended length of time for measurement.Therefore,in this study,Deep Neural Network(DNN)has been deployed to automate the lithology identification process from well logging data which would provide support by increasing time-effective for monitoring lithology.DNN model has been developed for predicting formation lithology leading to the optimization of the model through the thorough evaluation of the best parameters and hyperparameters including the number of neurons,number of layers,optimizer,learning rate,dropout values,and activation functions.Accuracy of the model is examined by utilizing different evaluation metrics through the division of the dataset into the subdomains of training,validation and testing.Additionally,an attempt is contributed to remove interception for formation lithology prediction while addressing the imbalanced nature of the associated dataset as well in the training process using class weight.It is assessed that accuracy is not a true and only reliable metric to evaluate the lithology classification model.The model with class weight recognizes all the classes but has low accuracy as well as a low F1-score while LSTM based model has high accuracyas well as a high F1-score.

Artificial neural network model for predicting drill cuttings settling velocity

The traditional method of using the coefficient of drag–Reynolds number relationship to predict cuttings settling velocity involves an implicit procedure that requires repeated,time-consuming and tedious iterations using Newtonian or mostly non-Newtonian correlations.Usually,these correlations are limited to certain fluid flow regimes.Besides,most of the explicit and direct cuttings settling velocity models that exist are based on the assumption that the cuttings are spherical particles.However,in the field,the cuttings are a mixture of various shapes and are hardly spherical,hence these models when applied to field conditions come off with huge errors.The objective of this work was to use a nature-inspired algorithm(artificial neural network-ANN)to develop a model for estimating cuttings settling velocity that would be robust and useful in the field that would take into account the shape of the cuttings.The data used for this work was obtained from research experiments in the literature.The model was then evaluated using four performance metrics namely:mean squared error(MSE),root mean square error(RMSE),sum of squares error(SSE)and goodness of fit(R2).It was found that the model's predictions obtained in this work agreed with experimental evidence.Furthermore,the developed model possesses the capacity to generalize across new input datasets and can be applied to particles of any shape,hence,defining the novelty of this research and bridging the gap between theory and practice.When compared with state-of-the-art models,the developed models show a high degree of robustness,as the ANN model performed reasonably well with an MSE of 7.5×10−4,an R2 of 0.978,RMSE of 0.0274 and SSE of 0.25.To generalize the results across new input datasets,the developed model was cross-validated with new data that was not part of the training process.It was found that the ANN model had an MSE value 0.00807,RMSE of 0.0898,MAE of 0.065,SSE of 2.74 and MAPE of 0.675%.To ensure the replicability of the ANN model,the weights and biases for the inputs,hidden and output layers are presented in this work unlike other artificial intelligence-based models in the literature.The range of application for the developed ANN model is 0.0001<Particle Reynolds's number<100 and 0.471<cuttings sphericity<1.With the model developed in this work,the cuttings settling velocity can be predicted with minimal errors in a quick,less cumbersome,non-iterative manner and is not limited by cuttings shapes'factor and fluid flow regimes.

An approach to improve wellbore stability in active shale formations using nanomaterials

Drilling through active shale formations has been a challenging practice in the oil and gas industry for a long period of time,given the complexity of shale structure and its interaction with Water Based Muds(WBMs).Although there have been many additives and methodologies proposed for a safe drilling through shale formations using WBMs,little success has been reported to the application of these methods once tested under different field conditions.In this paper,a new WBM formulated by nanomaterials was proposed to stabilize active shale layers during drilling.A series of rheological,density,filtration loss,bentonite dispersion and shale recovery tests were conducted on the mud samples formulated by nanosilica and Nano Glass Flakes(NGFs).The results indicated that NGF,as a cheap but effective nanomaterial,is able to significantly reduce the flirtation loss without posing any significant impacts on the density and the rheology of WBMs.It also appeared that the bentonite molecules were incapable to either hydrate or disperse in the drilling fluid system in the presence of NGFs.It seems that NGFs can stabilize clay minerals and reduce the filtration loss as remarkably efficient additive,but caution must be taken to ensure that they are properly disperse in the WBMs.