Density Behavior of Drilling Fluids During High Pressure High Temperature Drilling Operations

1998 ◽  
Author(s):  
Eirik Karstad ◽  
Bernt S. Aadnoy
Keyword(s):  
High Pressure ◽  
High Temperature ◽  
Drilling Fluids ◽  
High Pressure High Temperature ◽  
Drilling Operations ◽  
Density Behavior

Prediction of High-Pressure/High-Temperature Rheological Properties of Drilling Fluids from the Viscosity Data Measured on a Coaxial Cylinder Viscometer

SPE Journal ◽  
2021 ◽  
pp. 1-22
Author(s):  
Sidharth Gautam ◽  
Chandan Guria ◽  
Laldeep Gope
Keyword(s):  
High Pressure ◽  
High Temperature ◽  
Shear Viscosity ◽  
Drilling Fluid ◽  
Viscosity Model ◽  
Drilling Fluids ◽  
Viscosity Data ◽  
Monitoring And Control ◽  
High Pressure High Temperature ◽  
Proposed Model

Summary Determining the rheology of drilling fluid under subsurface conditions—that is, pressure > 103.4 MPa (15,000 psi) and temperature > 450 K (350°F)—is very important for safe and trouble-free drilling operations of high-pressure/high-temperature (HP/HT) wells. As the severity of HP/HT wells increases, it is challenging to measure downhole rheology accurately. In the absence of rheology measurement tools under HP/HT conditions, it is essential to develop an accurate rheological model under extreme conditions. In this study, temperature- and pressure-dependence rheology of drilling fluids [i.e., shear viscosity, apparent viscosity (AV), and plastic viscosity (PV)] are predicted at HP/HT conditions using the fundamental momentum transport mechanism (i.e., kinetic theory) of liquids. Drilling fluid properties (e.g., density, thermal decomposition temperature, and isothermal compressibility), and Fann® 35 Viscometer (Fann Instrument Corporation, Houston, USA) readings at surface conditions, are the only input parameters for the proposed HP/HT shear viscosity model. The proposed model has been tested using 26 different types of HP/HT drilling fluids, including water, formate, oil, and synthetic oil as base fluids. The detailed error and the sensitivity analysis have been performed to demonstrate the accuracy of the proposed model and yield comparative results. The proposed model is quite simple and may be applied to accurately predict the rheology of numerous drilling fluids. In the absence of subsurface rheology under HP/HT conditions, the proposed viscosity model may be used as a reliable soft-sensor tool for the online monitoring and control of rheology under downhole conditions while drilling HP/HT wells.

Evaluating Precision of Annular Pressure Buildup (APB) Estimation Using Machine-Learning Tools

2021 ◽  
pp. 1-11
Author(s):  
Subhadip Maiti ◽  
Himanshu Gupta ◽  
Aditya Vyas ◽  
Sandeep D. Kulkarni
Keyword(s):  
Machine Learning ◽  
High Pressure ◽  
High Temperature ◽  
Small Error ◽  
Estimation Methods ◽  
Drilling Fluids ◽  
Pressure Buildup ◽  
Pvt Data ◽  
High Pressure High Temperature ◽  
Annular Pressure Buildup

Summary Annular pressure buildup (APB) is caused by heating of the trapped drilling fluids (during production), which may lead to burst/collapse of the casing or axial ballooning, especially in subsea high-pressure/high-temperature wells. The objective of this paper is to apply machine-learning (ML) tools to increase precision of the APB estimation, and thereby improve the fluid and casing design for APB mitigation in a given well. The APB estimation methods in literature involve theoretical and computational tools that accommodate two separate effects: volumetric expansion [pressure/volume/temperature (PVT) response] of the annulus drilling fluids and circumferential expansion (and corresponding mechanical equilibrium) of the well casings. In the present work, ML algorithms were used to accurately model “fluid density = f(T, P)” based on the experimental PVT data of a given fluid at a range of (T, P) conditions. Sensitivity analysis was performed to demonstrate improvement in precision of APB estimation (for different subsea well scenarios using different fluids) using the ML-basedmodels. This study demonstrates that, in several subsea scenarios, a relatively small error in the experimental fluid PVT data can lead to significant variation in APB estimation. The ML-based models for “density = f(T, P)” for the fluids ensure that the cumulative error during the modeling process is minimized. The use of certain ML-based density models was shown to improve the precision of APB estimation by several hundred psi. This advantage of the ML-based density models could be used to improve the safety factors for APB mitigation, and accordingly, the work may be used to better handle the APB issue in the subsea high-pressure/high-temperature wells.

An Innovative Design for Drillstring Testbed for High Pressure High Temperature Drilling

2020 ◽  
Author(s):  
Randall Tucker ◽  
Alan Palazzolo ◽  
Mohamed Gharib
Keyword(s):  
High Pressure ◽  
High Temperature ◽  
Simulation Software ◽  
Operating Conditions ◽  
Dynamics Simulation ◽  
Drilling Fluids ◽  
Test Rig ◽  
Stick Slip ◽  
Rock Interaction ◽  
High Pressure High Temperature

Abstract In this paper, a novel design for a full-scale, industrial-size, and high pressure high temperature (HPHT) drillstring test rig is presented. The test more accurately replicates the downhole environment with regards to bit performance limiters. The facility has a high-power drill string with side loading, reasonably sized mud pumps, a HPHT sample that generates a hot pressurized rock-bit interface and the ability to easily replicate specific drilling scenarios. This provides a step change in drilling research. Replicating down-hole HPHT conditions in a surface level drilling test rig is challenging but will deliver significant benefits for downhole tool and instrument development. The proposed test rig will provide these test conditions for developing longer lasting and more efficient bits, more effective drilling fluids, and lower friction tool joints to increase weight on bit (WOB) and rate of penetration (ROP). A secondary benefit is for identification of bit-rock interaction laws that will assist in implementing successful automated drilling (AD) approaches to reduce drillstring and bit failures from stick-slip, bit-bounce and other drilling anomalies. AD has the potential for increasing efficiency as well as reliability of drilling. The force and torque laws will also be utilized in drillstring dynamics simulation software for operator training and hardware development. The proposed test rig gives the industry a unique opportunity to couple experimental work that is representative of downhole conditions with actual industry problems and concerns. By using data sets from actual drilling operations, we will be able to replicate what is occurring downhole but in a controlled, measurable environment on the surface. The system will be highly automated with a remotely operated control room, to increase safety in the high temperature, pressure, force and torque environment of the test rig. The system is to be fully enclosed with an API rated pressure containment system. The description of the test rig here is intended to convey the complexity of the hardware needed to meet functionality requirements and operating conditions. The design is purposely configured to accommodate the inevitable small requirement modifications, with minimal delays in rig completion.

Sign in / Sign up

Export Citation Format

Share Document