Oluwatosin J. Rotimi

Optimizing the rheological properties of silica nano-modified bentonite mud using overlaid contour plot and estimation of maximum or upper shear stress limit

Abstract An optimization based statistical (response surface) approach was used to evaluate the rheological properties of bentonite mud treated with silica nanoparticles. The overlaid contour plot established the feasible region for the various factor settings from multiple regression equations. The steepest method was used to further determine the optimal factor settings for minimum rheological properties and this was established at 6.3 wt.% bentonite content and 0.94 wt.% silica nanoparticles. The rheological properties of the bentonite mud containing and without silica nanoparticles was evaluated using a Hyperbolic (new) model and related with other oil industry based models: Herschel Bulkley, Sisko, Casson. The hyperbolic rheological model estimated the rheological behaviour of the nano-modified mud satisfactorily while also predicting a shear stress limit for the nano-modified mud. The maximum shear stress limit values for 6.3, 13 and 15 wt.% mud were 14.59, 61.74 and 107.4 Pa respectively. Upper shear stress values obtained from a 1.5 wt.% silica nanoparticle modified 6.3, 13 and 15 wt.% bentonite mud were 22.27, 72.62 and 171.3 Pa respectively, which represents an increment of 34.5 to 37.4% in the upper limit of shear stress. The effect of silica nanoparticles on the upper shear stress limit was quantified using a response surface design.

A proposed solution to the determination of water saturation: using a modelled equation

Reservoir characterization is an important phase in oil and gas field development, which takes place during the appraisal phase of either a green field or a brown field upon which further development options are considered. Water saturation is a very important parameter in the general description of the reservoir as well as equity determination and dynamic modelling. Numerous equations have been developed which have been used to determine water saturation, but calculated water saturation values have been inconsistent with the saturation values determined from core analysis. This is generally due to their inability to account for the varying distribution of shale in the reservoir and the often incorrectness of their underlying assumptions. The major aim of this research is to develop a model which can be used to determine water saturation values using data from well logs; also, to compare the developed model with other existing models used in the oil and gas industry, using data from core analysis and well logs as the input data; and then finally, to discuss the results of the comparison, using the core-derived saturation values as the bench mark. The model is based on a parallel resistivity model, which is based on the assumption that the conductivity of the sandstone term and the shale term exist in parallel in the shaly-sand reservoir. The shale term in the reservoir of the model is based on the assumption that the clay-bound electrons do not move in the same conductivity path as the sandstone electrons. The shale conductivity term is based on the bound water saturation and the bound water resistivity. The modelled equation was compared in two scenarios using well log data and core data from two different reservoirs, and the model showed consistency in predicting the average water saturation in both reservoirs. The results of the comparison were positive for the modelled equation, as it gave coherent results in both comparison scenarios and matched reasonably the average water saturation of the selected reservoirs. This developed model can serve as an accurate means of determining water saturation in reservoirs, especially for reservoirs with similar characteristics as the selected reservoirs in this research.

Experimental dataset of enhanced rheological properties and lubricity of Nigerian bentonite mud using kelzan® xcd polymer and identifying it optimal combination

The experimental dataset in this article are for improved rheological properties and lubricity of Nigerian bentonite mud using Kelzan® xcd polymer and identifying it optimal combination. For this study, water base mud was formulated using a Nigerian bentonite and a statistical based method was used to analyze the rheological and lubricity properties of the drilling fluid, when enhanced with kelzan® xcd polymer. The significant and interaction level of these factors were closely observed on the mud properties test that were conducted. The use of response surface design was engaged to analyze the influence of bentonite quantity and the quantity of kelzan® xcd polymer on the lubricity and rheological properties of the mud. Minitab 17 (Minitab Inc. USA) was used for the response surface design. The p-values were used to determine which of the factors in the model are statistically significant, which was compared to α-level (0.05). The p-values for the quantity of kelzan® xcd polymer are 0, 0, and 0.007 for Apparent viscosity (cp), Yield point (Ib/100 ft^2), Plastic viscosity (cp) respectively. All these values are lesser than the α-level (0.05), which means that the effect of kelzan® xcd polymer is significant on the model. While the effect of Bentonite content and the interaction between Bentonite content and kelzan® xcd polymer are insignificant because their p-values are higher than the -level (0.05).

Reservoir characterization and modeling of lateral heterogeneity using multivariate analysis

Reservoir characterization deals with the description of the reservoir in detail for rock and fluid properties within a zone of interest. The scope of this study is to model lateral continuity of lithofacies and characterize reservoir rock properties using geostatistical approach on multiple data sets obtained from a structural depression in the bight of Bohai basin, China. Analytical methods used include basic log analysis with normalization. Alternating deflections observed on spontaneous potential (SP) log and resistivity log served as the basis for delineating reservoir sand units and later tied to seismic data. Computation of variogram was done on the generated petrophysical logs prior to adopting suitable simulation algorithms for the data types. Sequential indicator simulation (SIS) was used for facies modeling while sequential gaussian simulation (SGS) was adopted for the continuous logs. The geomodel built with faults and stratigraphical attitude gave unique result for the depositional environment studied. Heterogeneity was observed within the zone both in the faulted and unfaulted area. Reservoir rock properties observed follows the interfingering pattern of rock units and is either truncated by structural discontinuities or naturally pinches out. Petrophysical property models successfully accounted for lithofacies distribution. Porosity volume computed against SP volume resulted in Net to gross volume while Impedance volume results gave credibility to the earlier defined locations of lithofacies (sand and shale) characterized by porosity and permeability. Use of multiple variables in modeling lithofacies and characterizing reservoir units for rock properties has been revisited with success using hydrocarbon exploration data. An integrated approach to subsurface lithological units and hydrocarbon potential assessment has been given priority using stochastic means of laterally populating rock column with properties. This method finds application in production assessment and predicting rock properties with scale disparity during hydrocarbon exploration.