Journal of Petroleum Science and Technology
Volume:10 Issue: 4, Autumn 2020

Wellbore instability has always been one of the challenging issues in the drilling industry, and it could cause a delay in the drilling program, leading to an increase in the cost of the drilling projects. This study utilized data from seven wells to investigate and model directional wells’ stability in a shale formation during drilling in one of the largest oilfields in the southwest of Iran. In this study, two mthods, i.e. (1) mechanical earth model (MEM) and (2) quantitative risk assessment (QRA) are applied to investigate and model directional wells’ stability in shale formation. Herein, a wellbore with full suite log data and compressional and shear wave slowness was selected to construct the mechanical earth model (MEM). Appropriate equations are provided to estimate the field’s static geomechanical data, and laboratory data were used for validation (i.e. core). The minimum mud weight required at azimuth and different angles of the directional well was calculated using numerical and analytical analysis of the wellbore stability using the Mohr-Coulomb failure criterion. The purpose of the quantitative risk assessment (QRA) phase is to investigate the impact of the uncertainty of key parameters (i.e. input variables of the minimum mud weight equation based on the Mohr-Coulomb failure criterion) and their sensitivity to an increase in success rate and a decrease in failure. In the QRA phase, the Monte Carlo simulation method is used, and the results are displayed on a Tornado diagram. The results of the Hoek-Brown and Mogi-Coulomb failure criteria propose that the sensitivity of the mud density obtained by the above methods to the uncertainty is low. The results maintain that the prediction of the minimum mud weight required for the stability of the investigated wellbore is strongly dependent on changes in the maximum horizontal stress (σ_H) parameter and minimum horizontal stress. Moreover, the internal friction angle and rock adhesion coefficient have the least impact on determining the minimum mud weight needed for wellbore stabilization.

The preformed particle gel (PPG) oil flooding system has several problems: (1) in the process of injection, particles easily settled and block the end face, which the process results in high pressure, and (2) the matching relationship between PPG particle size and formation pore throat has not been quantified sophisticatedly. To have a better description of the matching relationship between the median particle size of the dispersed phase and the pore throat diameter of the formation, its relationship has been quantified by us through the combination of core physical simulation and thin-tube experiments. Moreover, a calculation method of equivalent pore throat diameter has been proposed based on the principle of compact packing, which is more suitable for a sand-filled pipe model. To improve the performance of the system, the polymer and surfactant have been added into the PPG solution. The result indicates that when the pore throat diameter is between 1 to 5 times more than the median particle size of the dispersed phase, the dispersed phase can enter the pore throat smoothly, and the plugging rate is over 50%, which it means that the plugging is effective. When the pore throat diameter is more than 12 times of the median particle size of the dispersed phase, the plugging rate is less than 30%, and the effective residual resistance coefficient cannot be established. In order to improve the suspension performance of PPG particles, the polymer was added to the solution. In the presence of polymers, the suspension performance of PPG particles was greatly enhanced. Under the same injection volume, the PPG + polymer + surfactant system has the best oil displacement performance.

Permeability is arguably the most critical property for evaluating flow in the reservoir. It is also one of the challenging parameters which must be measured in the field. Nuclear Magnetic Resonance (NMR) logging across the borehole is among the popular techniques, which it is utilized to determine permeability across the reservoir. However, available correlations in literature for estimating permeability from NMR data do not usually provide acceptable accuracy in the carbonate rocks. Therefore, a new model is proposed to estimate permeability by establishing a relationship between core derived permeability and extracted features from the T2 distribution curve of NMR data with the ensemble LSBoost algorithm. The feature extraction process is performed using peak analysis on T2 distribution curves which it leads to 5 relevant parameters, including T2lm, TCMR, prominence, peak amplitude and width. The proposed model is validated by comparing the proposed method’s correlation coefficient against Timur-Coates and SDR equation estimation accuracy. The results show that our model generally provides better prediction accuracies in comparison with the empirical equation-based derived permeabilities.

The South Pars gas field is one of the southwestern fields of Iran. This field in the Zagros sedimentary basin and consists of two Kangan and Dalan reservoirs. The Kangan and Dalan Formations belong to Dehram Group, and they are the most significant gas reservoirs in the Persian Gulf area. In this research, exploratory and production well data in the South Pars gas field were examined. Moreover, Fracture and reservoir parameters were investigated through from petrophysical logs, FMI image log, and the litholog. Additionally, according to the lithology, shale volume, presence of evaporite sediments, and porosity, the Kangan Formation to K1 and K2, and the Dalan Formation have been zoned to K3 and K4 sections. Furthermore, fractures are essential for the initial migration of hydrocarbons from the source rock to the reservoir, and this study tries to provide useful information for the future. According to FMI log analysis, about 200 Fractures have been detected in Kangan and Upper Dalan reservoir intervals in the studied well up to now. Of which, 2 breakouts, 2 tensile fractures, 4 closed fractures, 19 open fractures, 63 beddings, 2 cross beddings, 35 conductive fractures, 26 stylolites, 47 unclassified fractures have been visible in the results. The findings of this study showed that zones K2 and K4 with the highest porosity and the lowest amount of water saturation have a higher reservoir quality than zones K1 and K3 sections.  Also, the K4 zone has had the highest fracture density in comparison to other zones, which leads to increased porosity of the zone.  Ultimately, zone K2 with the least thickness (43 meters) had a lower fracture density in comparison with the K4 zone (7 conductive fissures and 2 open fractures). Also, in comparison with other zones,  it has low water saturation and high porosity and has a higher reservoir quality than K3 and K1 zones.

An accurate prediction of production rate for wellhead choke is highly vital in petroleum production engineering applications. It is deployed in the control of surface production, prevention of water and gas coning, and optimization of the entire production systems. Although there are several choke correlations in literature to estimate production rate; however, most of the published correlations were derived with datasets outside Niger Delta fields. Thus, this study presents a new empirical-based model, which is a derivative from Choubineh et al. model, to predict the liquid production rate of chokes for Niger Delta oil wells. The new model was developed and optimized using multivariate regression and the Generalized Reduced Gradient (GRG) optimization algorithm. Furthermore, a total of 283 production data points from 21 oil wells in 7 fields in the Niger Delta region, with a randomly generated ratio of 70: 30 of the datasets, was used to develop and validate the developed model. The developed Model 2 predicted the choke production rate with a fitting accuracy of average absolute percentage error (AAPE) of 23.73% and coefficient of determination (R2) of 0.973; in addition, the model predicted validating accuracy of AAPE of 9.33% while the coefficient of determination (R2) stands at 0.982. Consequently, this model can be relied on as a quick and robust tool for estimating the choke production rate of producing oil wells. Moreover, the sensitivity analysis results show that the choke size has the most significant impact on the predicted liquid rate. In contrast, gas gravity has the least impact.

To compare the performance of conventional solvent (N-formylmorpholine or NFM) with deep eutectic solvents (DESs) for benzene extraction, some (choline chloride : ethanolamines) based DESs were selected as extraction solvents. Liquid – Liquid extraction measurements were conducted on a petrochemical cut (pyrolysis gasoline) as feedstock. The influence of the solvent to feed ratio, temperature and extraction time on the (pyrolysis gasoline + NFM or DES) mixtures were investigated. Moreover, the selectivity (S) and solute distribution coefficient (β) were determined for the studied conventional solvent and DESs. Results show that the benzene extraction performance using one of the deep eutectic solvents (choline chloride: monoethanolamine with (1:5) mole ratio) is better than that of the conventional extraction solvent (NFM) at the studied conditions. In addition, lower contamination of extracted benzene (with NFM and other extractors) and immiscibility of DES in the hydrocarbon phase (NFM is partially miscible in the hydrocarbon phase) are among other advantages of this replacement.

Clathrate hydrates (gas hydrates) are solid crystalline compounds formed from water molecules as host molecules and gas molecules as guest molecules. Due to the hydrogen bonds, water constructs a framework that entraps some small nonpolar molecules (typically gases) and in suitable conditions (i. e. low temperature and high pressure) gas hydrate forms. The objective of this research is to estimate the gas and refrigerant hydrate dissociation conditions with and without alcohols and sodium chloride aqueous solutions using simple empirical correlations. Generally, the empirical suggested correlations to estimate the equilibrium clathrate hydrate pressure of CH4, C2H6, C3H8, CO2, N2, H2S, R22, R23, R134a, R116, R125a, R152a, R141b, R410a, R407c, R507c, CH4 + methanol, CH4 + ethylene glycol, CH4 + triethylene glycol, CH4 + ethanol, CH4 + sodium chloride, CO2 + methanol, CO2 + glycerol, CO2 + sodium chloride, R134a + sodium chloride, R507c + sodium chloride and R410a + sodium chloride systems are a function of equilibrium hydrate temperature and concentration. A genetic algorithm was employed as an optimization method to determine correlation coefficients, and the mean squared error was selected as its fitness function. Due to the low values of the calculated absolute average deviations (between 0.00 and 7.65), except for H2S + pure water with the highest amount of the absolute average deviation percent (AAD% equal to 11.51), these correlations are capable of predicting the studied hydrate dissociation conditions.