Badrul Mohamed Jan

Increasing Production by Maximizing Underbalance During Perforation Using Nontraditional Lightweight Completion Fluid

Summary The invasion of the pulverized formation rock grains and the resulting low-permeability crushed zone is the primary cause of wellbore damage in perforated completions, as established by Behrmann et al. (1991). To minimize this damage during the perforating process, it is necessary to provide a dynamic underbalance in the well that will deliberately induce flow into the wellbore for tunnel cleanup. Traditional well fluids have a limited application in depleted reservoirs because the lowest achievable density is on the order of 6.6 lbm/gal. In many depleted reservoirs, this density can represent an overbalance. It is not always desirable or operationally practical to provide this underbalance with a gas cushion; therefore, to achieve underbalance, it is desirable to engineer a stable fluid with nondamaging chemical properties, which would have a significantly lower density. This paper reports on the formulation of superlight completion fluids consisting of Shell Sarapar 147 synthetic oil (SO) [Shell Middle Distillate Synthesis (MDS), Kuala Lumpur] and 3M Scotchlite hollow-glass spheres (HGSs) (3M, St. Paul, Minnesota, USA), also known as glass bubbles, as a density-reducing agent, with an appropriate stabilizing agent. Laboratory tests show that density values as low as 5.0 lbm/gal could be achieved. Similar mixtures were prepared and used in perforation operations for Talisman Malaysia. A total of 72 bbl of lightweight completion fluids (LWCFs) at approximately 5.5 lbm/gal was pumped downhole, and the perforation job was completed successfully. Production history of the well shows marked increase in production rate compared to the neighboring wells, which produce from the same reservoir but were perforated traditionally with little or no underbalance. This technology is not necessarily limited to depleted reservoirs. In normally pressured zones where permeability is extremely low, the fluid provides an opportunity to increase the available underbalance by an order of magnitude to assist cleanup.

Composition Prediction of a Debutanizer Column using Equation Based Artificial Neural Network Model

Debutanizer column is an important unit operation in petroleum refining industries. The design of online composition prediction by using neural network will help improve product quality monitoring in an oil refinery industry by predicting the top and bottom composition of n-butane simultaneously and accurately for the column. The single dynamic neural network model can be used and designed to overcome the delay introduced by lab sampling and can be also suitable for monitoring purposes. The objective of this work is to investigate and implement an artificial neural network (ANN) for composition prediction of the top and bottom product of a distillation column simultaneously. The major contribution of the current work is to develop these composition predictions of n-butane by using equation based neural network (NN) models. The composition predictions using this method is compared with partial least square (PLS) and regression analysis (RA) methods to show its superiority over these other conventional methods. Based on statistical analysis, the results indicate that neural network equation, which is more robust in nature, predicts better than the PLS equation and RA equation based methods.

A Tait-like Equation for Estimating the Density of Nontraditional Super Lightweight Completion Fluid at High Pressure and Temperature

Novel nontraditional super lightweight completion fluid (SLWCF) has been proven to be the best means to ensure the success of underbalance perforation. Field test showed that the application of this new fluid has improved the well productivity. The authors present density measurements of SLWCF at high pressure and temperature. Density values of the fluid were measured in laboratory at high temperature ranging from 313.15 to 393.15 K, and pressure up to 25 MPa. Measured densities were fitted to a Tait-like equation. Calculated absolute average deviation, the maximum deviation, bias, and standard deviation values show that the developed model can be used to express the fluid density over a wide range of pressure and temperature. In addition, density value predicted by a Tait-like equation shows a good agreement both with laboratory and field data.

Multivariable control of a debutanizer column using equation based artificial neural network model inverse control strategies

The debutanizer column is an important unit operation in petroleum refining industries as it is the main column to produce liquefied petroleum gas as its top product and light naphtha as its bottom product. This system is difficult to handle from a control standpoint due to its nonlinear behavior, multivariable interaction and existence of numerous constraints on both its manipulated and state variable. Neural network techniques have been increasingly used for a wide variety of applications where statistical methods have been traditionally employed. In this work we propose to use an equation based MIMO (Multi Input Multi Output) neural network based multivariable control strategy to control the top and bottom temperatures of the column simultaneously, while manipulating the reflux and reboiler flow rates respectively. This equation based neural network model represented by a multivariable equation, instead of the normal black box structure, has the advantage of being robust in nature while being easier to interpret in terms of its input output variables. It is implemented for set point changes and disturbance changes and the results show that the neural network based model method in the direct inverse and internal model approach performs better than the conventional PID method in both cases.

The Viscosity of Nontraditional Lightweight Completion Fluid at Elevated Temperature and Pressure

Abstract Experimental viscosity values of nontraditional lightweight completion fluid at pressure and temperature ranges of 0.1 MPa to 4.48 MPa, and of 25°C to 100°C, respectively, were reported. To establish the relationship among viscosity, pressure, and temperature, experimental data were fit to the modification of Mehrotra and Svrceks equation. The result shows that the model could be used to describe the fluid viscosity over a wide range of pressure and temperature. The calculated what is sum of square error and root mean square error are 0.2135 and 0.08892, respectively. It is also shown that the predicted values from the model are in a good agreement with both the experimental values and field data.

Rheology and Temperature Dependency Study of Saraline-Based Super Lightweight Completion Fluid

One of the effective alternatives to minimize this perforation-induced formation damage is by application of underbalanced perforation. Fluid systems with very low density could be used to perforate reservoirs in underbalanced pressure conditions that virtually eliminate or minimize fluid invasion and damage along perforation tunnels. To respond in the need such fluid, Saraline-based super lightweight completion fluid (SLWCF) has been formulated from glass bubble, stabilizing and homogeneity agent. This paper focuses on a rheological and statistical evaluation of Saraline-based SLWCF and its effect on operating temperature. Eight rheological models, namely the Bingham plastic, Ostwald-de Waele, Herschel-Bulkley, Casson, Sisko, Robertson-Stiff, Heinz-Casson, and Mizrahi-Berk, were used to describe the rheological behavior of the fluid. Based on the results, rheology of the fluid was best represented by both the Sisko and the Mizrahi-Berk models. Furthermore, it is also found that the viscosity of Saraline-based SLWCF was more dependent to temperature changes at low shear rate. The Arrhenius activation energy for the fluid to flow was also found to be decreasing with shear rate and their relationship can be expressed with a power law equation.

The Effects of Glass Bubbles, Clay, Xanthan Gum and Starch Concentrations on the Density of Lightweight Biopolymer Drilling Fluid

It is an open secret that currently oil and gas industry is focusing on increasing hydrocarbon production through underbalanced drilling (UBD) and finding ways to ensure the drilling process is less harmful to the environment. Water-based biopolymer drilling fluids are preferred compared to oil based drilling fluids owing to the fact that it causes less pollution to the environment. This paper investigates the effects of varying concentrations of environmentally safe raw materials, namely glass bubbles, clay, xanthan gum and starch concentrations on the density of the formulated biopolymer drilling fluid to ensure that it is suitable for UBD. As material concentrations were varied, the density for each sample was measured at ambient temperature and pressure. Results showed that the final fluid densities are within acceptable values for UBD (6.78 to 6.86 lb/gal). It is concluded that the formulated water-based biopolymer drilling fluid is suitable to be used in UBD operation.

An Optimization Study of Polyacrylamide-Polyethylenimine-Based Polymer Gel for High Temperature Reservoir Conformance Control

This paper presents optimization formulation of organically crosslinked polymer gel for high temperature reservoir conformance control using response surface methodology (RSM). It is always desirable to approach an optimal polymer gel formulation study with adequate performance information related to viscosity and gelation time to minimize excessive water production. In this paper, the effects of polymer and crosslinker concentrations and their influences on gelation time and viscosity were investigated. Central composite design (CCD) was used to determine the optimized organically crosslinked polymer gel formulation. Concentrations of two main raw materials, namely, polyacrylamide (PAM) and polyethylenimine (PEI), were varied in a suitable range. This was to obtain the formulation with the desirable two vital responses, which are viscosity and gelation time. It was found that the results fitted the quadratic equation. Statistically, the quadratic model is reliable and adequate perfectly the variability of the responses obtained from the experimental data. In addition, gelation time and gel viscosity may be controlled by adjusting both polymer and crosslinker concentrations. The optimum formulated organically crosslinked polymer gel with significant desirability factor conditions was achieved at 1.5% w/v of PAM and 0.3% v/v of PEI.

Viscosity prediction model optimization for Saraline-based super lightweight completion fluid at high pressure and temperature

Investigation and analysis of the viscosity variation of Saraline-based super lightweight completion fluid (SLWCF) at high pressure and temperature were reported, and the viscosity prediction model was optimized. Viscosity measurements were carried out at temperature and pressure ranging from 298.15 K to 373.15 K, and 0.10 MPa to 4.48 MPa respectively. The data analysis reveals that the reduction of viscosity as a function of temperature may be divided into two regions, i.e. significant viscosity reduction at low temperature and fairly slow viscosity reduction at high temperature; the viscosity of Saraline-based SLWCF is less affected by the changes of pressure. The experimental data were fitted to four different viscosity-temperature-pressure models. The results show that, the modified Mehrotra and Svrceks and Ghaderis models are able to satisfactorily predict the viscosity value and measured value and describe the viscosity property at high pressure and temperature. The comparison with the Sarapar-based SLWCF reveals that the viscosity of Sarapar-based SLWCF is more affected by temperature than the Saraline-based SLWCF; pressure seems to have negligible effect on Saraline-based SLWCF viscosity; the modified Mehrotra and Svrceks and Ghaderis models are able to give more reliable viscosity predictions for Saraline-based SLWCF than for Sarapar-based SLWCF.

Novel Lightweight Biopolymer Drilling Fluid for Underbalanced Drilling

This research centres on optimizing the formulation of a water-based lightweight biopolymer drilling fluid using Design Expert for underbalanced drilling (UBD). Response Surface Methodology (RSM) was selected as a viable means to obtain the optimized drilling fluid formulation. Concentrations of four main raw materials (glass bubbles, clay, xanthan gum and starch) were varied in a suitable range to obtain the formulation with the desirable density, plastic viscosity (PV) and yield point (YP) for UBD application. Based on the results, the optimized drilling fluid can be formulated with 24.46% w/v of glass bubbles, 0.63% w/v of clay, 0.21% w/v of xanthan gum and 2.41% w/v of starch. The desirability factor, d for this optimum condition selected is 0.628. The mathematical models generated by RSM were able to predict the three response parameters well, as the experimental values were found to be in good agreement with the predicted values. The error is less than 1.0, standard deviation less than 0.5 and the accuracy is more than 98.5%. All mathematical models were quadratic in nature. The model used to predict the PV has an inverse square root transform. This drilling fluid is considered to be less harmful to the environment as it is water-based and, at the same time, composed of natural polymers (xanthan gum and starch) which are biodegradable. With this novel formulation, we could expect to drill more wells in underbalanced conditions to improve production of oil.