Robello Samuel

To understand and quantify casing wear during drilling operations, an experimental setup with real drill pipe joints (DPJ) and casings was designed and used to carry out wear tests, simulating various operating conditions and environments. P110 steel casing samples were tested under dry and wet conditions. Actual field oil- and water-based fluids were utilized to lubricate the contact area at two different side loads (1000 N and 1400 N) and DPJ speeds (115 and 207 rpm). The results show that for the same testing conditions, the casing wear volume and wear factor under water-based lubrication were more than twice those obtained under oil-based fluid testing. As expected, the wear volume and wear factor were highest under dry conditions. Moreover, it was noticed that, as the normal load was increased at a constant rotational speed (rpm), the wear factor increased. On the other hand, raising the rotational speed at the same applied load reduced the casing wear factor, due to the observed absence of adhesive wear and possible localized softening effects at higher speeds. SEM analyses of the worn areas showed that under dry conditions, the main wear mechanisms were abrasion and delamination. However, both adhesive wear and abrasive wear mechanisms were observed under oil-based lubrication. The energy dispersive spectroscopy (EDS) analysis of the worn surface revealed that at higher loads and speeds, a heavy transfer of particles from the oil-based lubricant took place. On the other hand, some contaminants of the water-based lubricant were observed on the worn surfaces.

Drilling activities are very risky and costly, especially when performed offshore. Safety and efficiency are the primary concerns. In order to ensure safe and efficient operations, the process needs to be carefully monitored and analyzed in real time. Some of the undesirable scenarios or anomalies during drilling activities include stuck pipe, buckling, loss of circulation,

Annular fluid expansion (AFE) analysis is a critical step in designing an oil/gas well or a geothermal well. Traditionally, AFE analysis is typically performed between a drilling operation (initial condition) and a production operation (final condition). However, well design engineers would like to perform AFE analysis between any two operations. The objective of this work is to

The lithology of the formation is known to affect the drilling operation. Litho-facies help in the quantification of the formation properties, which optimizes the drilling parameters. The proposed work uses the artificial neural network algorithm and an optimizer to develop a working model for predicting the lithology of any formation within the study area in real-time. The proposed model is trained using the formation data comprising 15-dependent variables from the Eagleford region of the United States of America. It builds a method for measuring or forecasting litho-facies in real-time when drilling through a formation. It uses general drilling parameters for better precision, including Rate of Penetration, Rotation per minute, Surface Torque, Differential Pressure, Gamma Ray Correlation, and a d-exponent correlation function. The proposed model compares and assesses various first-order optimization algorithm's efficiency, such as Adaptive Moment Estimation, Adaptive Gradient, Root Mean Square Propagation, and Stochastic Gradient Descent with traditional artificial neural network in quantitative litho-facies detection. The model can predict the complex lithology for vertical/inclined/horizontal wellbores in real-time, making it a novel algorithm in the industry. The developed algorithm illustrates an accuracy of 86 % using Adam optimizer when tested with the existing data and improves as the model is trained with more data.

Drill-bit vibrations and bit wear have been identified as the two major causes for premature polycrystalline diamond-compact (PDC) bit failure and difficulty in accurately predicting PDC bit performance. The objective of this paper is to present a new approach to drilling optimization by developing an algorithm that defines and generates a constrained stable rotary speed (RPM)–weight-on-bit (WOB) working domain for a given system as opposed to the traditional RPM–WOB charts. The algorithm integrates the dynamic-stability model for bit vibrations with the bit-performance model for degraded bits. This study addresses the issues of dynamic-bit stability under torsional and lateral vibrations coupled with bit wear. The approach presented in this paper involves performing two separate analyses: vibration stability and bit-wear performance analysis. The optimum operating conditions are estimated at each depth of the drilling interval, taking into consideration the effect of bit wear and bit vibrations. Because the bit wears continuously while penetrating the rocks, discretization of depth is necessary for effective simulation. Discretization is done by dividing the drilling interval into subintervals of the desired length. Vibration-stability analysis and bit-wear performance analysis are preformed separately at every subinterval and then integrated over the discrete interval. For every subinterval, a WOB–RPM domain is determined within which the given system is dynamically stable (for vibrations), and the bit wear does not exceed the maximum allowable wear (MAW) for the section of the drilling interval selected. A unique concept to relate the fractional change in hydromechanical specific energy (HMSE) to the fractional change in bit wear has also been put forward that further constraints the WOB–RPM stable working domain. The new coupled vibration-stability chart, including the maximum rate of penetration (ROP), narrows down the conventional chart and provides different regions of operational stability. It has also been found that as the compressive strength of the rock increases, the bit-gauge friction factor also increases, which results in a compressed or reduced allowable working domain, both from the vibration-stability analysis and bit-performance analysis. Simple guidelines have been provided using the new stability domain chart to estimate the operating range for real-time optimization.

Managed pressure drilling (MPD) was developed as a group of technologies to more precisely control the annular pressure profile for which accuracy of the estimation of the bottomhole pressure is important. Particularly, under severe wave heaves in deepwater environments, the estimation based on static state pipe movement models can result in underestimation/overestimation of bottomhole pressures. The purpose of this study is to investigate the dynamic axial response of the drillstring with friction to applied heaving velocity, with particular interest to the effect at the bottomhole pressure. The paper presents an efficient and accurate method for solving the dynamic axial drillstring with friction and it allows it to be applied to heave velocity at the surface. The model that couples the pipe motion solves the full balance of mass and balance of momentum for pipe and annulus flow, considering the compressibility of the fluids, the elasticity of the system, and the dynamic motions of pipes and fluids. Also considered are surge pressures related to fluid column length below the moving pipe, compressibility of the formation, and axial elasticity of the moving string. Fluid properties are adjusted to reflect the effects of pressure and temperature on the fluids. The modeling takes into account the pipe elasticity under different combinations of heave and pipe velocities. Furthermore, the real-time torque and drag models are calibrated to actual hole conditions in real-time using survey, temperature, pressure, and downhole tool data to calculate friction factors in a wellbore. It has been observed that different conditions exist, some resulting in velocity reversal; thus causing surge or swab pressures. It has also been observed that heave amplitude has significant influence on bottomhole pressure. The different conditions observed for periodic or time function of displacements include (1) surface pipe velocity attributed to wave heave is in phase with the bottom movement of the string; (2) surface velocity of the pipe is out of phase with the bottom velocity of the pipe; (3) wave velocity and surface pipe velocity can be out of sync, and the bottom pipe velocity can be in phase with the surface velocity; and (4) wave velocity and surface pipe velocity can be out of sync, and the bottom pipe velocity can be out of phase with the surface velocity. The results of these calculations can be coupled to a real-time hydraulics model to determine a setpoint pressure for the MPD choke system. (SPE 173|005)

The increasing complexities of wellbore geometry imply an increasing well cost. It has become more important than ever to achieve an increased rate of penetration (ROP) and, thus, reduced cost per foot. To achieve maximum ROP, an optimization of drilling parameters is required as the well is drilled. While there are different optimization techniques, there is no acceptable universal mathematical model that achieves maximum ROP accurately. Usually, conventional mathematical optimization techniques fail to accurately predict optimal parameters owing to the complex nature of downhole conditions. To account for these uncertainties, evolutionary-based algorithms can be used instead of mathematical optimizations. To arrive at the optimum drilling parameters efficiently and quickly, the metaheuristic evolutionary algorithm, called the “shuffled frog leaping algorithm,” (SFLA) is used in this paper. It is a type of rising swarm-intelligence optimizer that can optimize additional objectives, such as minimizing hydromechanical specific energy. In this paper, realtime gamma ray data are used to compute values of rock strength and bit–tooth wear. Variables used are weight on bit (WOB), bit rotation (N), and flow rate (Q). Each variable represents a frog. The value of each frog is derived based on the ROP models used individually or simultaneously through iteration. This optimizer lets each frog (WOB, N, and Q) jump to the best value (ROP) automatically, thus arriving at the near optimal solution. The method is also efficient in computing optimum drilling parameters for different formations in real time. The paper presents field examples to predict and estimate the parameters and compares them to the actual realtime data.

Microhole coiled tubing drilling is a new technology that provides many added advantages but at the same time poses numerous operational challenges. This manifests itself in a number of ways, all of which adversely affect the efficiency of the drilling process. These problems include increased wellbore friction, poor hole-cleaning, tubular failures, and associated problems during tripping operations. Presently conventional torque and drag models are used to calculate drag forces and surface loads during microhole coiled tubing drilling. However, these estimates might be under conservative. Therefore, an improved model and more comprehensive analysis are required. Conditions expected during microhole coiled tubing drilling are completely different from those encountered during conventional drilling. Further complexity is added when the wellbore is undulated. This paper describes a new analytical model for estimating drag forces by assuming that pipe in the horizontal portion follows a sine function wave due to residual bends and snubbing force. In addition, the model takes into account when the wellbore is also tortuous. Fluid viscosity (an important force in the microhole) is also included so we can calculate appropriate surface loads in addition to drag. This study concludes that besides wellbore inclination, curvature, and wellbore torsion, parameters such as wavelength and contact area also influence the results. This paper documents the comparison between the predicted mathematical simulation results with actual data from wells describing the accuracy and applicability of the model. The analysis results and comparison are presented along with three examples (Zhang et al., 2013, “Analytical Model to Estimate the Drag Forces for Microhole Coiled Tubing Drilling,” Society of Petroleum Engineers, Paper No. SPE 163480.).

In high-risk, high-cost environments, such as ultra-deep waters, refining advanced technologies for the successful completion of wells is paramount. Challenges are still very much associated with complex bottomhole assemblies (BHAs) and with the vibration of the drillstring when used with hole enlarging tools. These tools with complex profiles and designs become additional excitation sources of vibration. The more widespread use of downhole tools for both directional telemetry and logging-while-drilling (LWD) applications, as part of the front line data acquisition system within the drilling process, has made reliability a prime area of importance. This paper presents and validates an existing model to predict severe damaging vibrations. It also provides analysis techniques and guidelines to successfully avoid the vibration damage to downhole tools and to their associated downhole assemblies when using hole enlarging tools, such as hole openers and underreamers. The dynamic analysis model is based on forced frequency response (FFR) to solve for resonant frequencies. In addition, a mathematical formulation includes viscous, axial, torsional, and structural damping mechanisms. With careful consideration of input parameters and the judicious analysis of results, we demonstrated that drillstring vibration can be avoided by determining the three-dimensional vibrational response at selected excitations that are likely to cause them. In addition, the analysis provides an estimate of relative bending stresses, shear forces, and lateral displacements for the assembly used. Based on the study, severe vibrations causing potentially damaging operating conditions that had been a major problem in nearby wells were avoided. Steps required to estimate the operating range of the drilling parameter such as weight on bit and rotational speeds to mitigate and avoid the downhole tool failures due to vibration are given. Extensive simulations were performed to compare the data from the downhole vibration sensors; this paper includes severe vibration incidence data from three case studies in which the model estimated, predicted, and avoided severe vibration (Samuel, R., et al., 2006, “Vibration Analysis Model Prediction and Avoidance: A Case History,” Paper SPE 102134 Presented at the IADC India Conference, Mumbai, India, Oct. 16–18; Samuel, R., 2010, “Vibration Analysis for Hole Enlarging Tools” SPE 134512, Annual Technical Conference, Florence, Italy).