Real-Time Measurement of Drilling Fluid Rheological Properties: A Review

On Improving Water-Based Drilling Mud Swelling Control Using Modified Poly(Vinyl Alcohol)s

One of the most challenging issues when drilling under high-temperature, high-pressure (HT/HP) conditions is wellbore instability caused by clay swelling and fluid loss of the drilling mud. One of the most difficult issues when drilling under high-temperature, high-pressure (HT/HP) conditions is wellbore instability caused by clay swelling and fluid loss in drilling mud. Two modified PVOHs, nonionic and cationic polymers made from sodium bentonite clay and deionized water at concentrations of 0.08, 0.28, and 0.49 wt.%, were introduced to WBM percent. A series of specific gravity and mud rheology experiments at 25, 55, and 85 °C indicated that both values drop monotonically with increasing temperature, regardless of PVOH addition or concentration. A temperature increase of 30 °C decreases the mud viscosity of WBM (without PVOH) by 18% from its starting value, on average. Only 0.1% of cationic and nonionic polymer reduces viscosity by 10% and 0%, respectively. Experimenting with mud samples for 5 h revealed that adding nonionic polymers enhances mud filtration by up to 34.7%, 1.25 times more than that achieved from cationic polymers under the same filtration circumstances. Increasing the filtration temperature moderately affects mud cake generation due to increased mud swelling index and preferential adsorption by nonionic polymer. The latter observation was corroborated by determining the polymer content of the filtrates. Therefore, it was shown that nonionic polymers adsorbed more (118.9 mg/g) than cationic polymers (84.51 mg/g). Increased filtration temperature moderately affects mud cake generation due to increased mud swelling index and preferential adsorption by nonionic polymer. The latter observation was corroborated by testing the filtrates for the polymer content. As a result, it was discovered that nonionic polymer adsorbed more (118.9 mg/g) than cationic polymer (84.51 mg/g). Thermogravimetry analysis (TGA) finally tested the thermal stability of polymers.

A Developed Robust Model and Artificial Intelligence Techniques to Predict Drilling Fluid Density and Equivalent Circulation Density in Real Time

When drilling deep wells, it is important to regulate the formation pressure and prevent kicks. This is achieved by controlling the equivalent circulation density (ECD), which becomes crucial in high-pressure and high-temperature wells. ECD is particularly important in formations where the pore pressure and fracture pressure are close to each other (narrow windows). However, the current methods for measuring ECD using downhole sensors can be expensive and limited by operational constraints such as high pressure and temperature. Therefore, to overcome this challenge, two novel models named ECD_effc.m and MW_effc.m were developed to predict ECD and mud weight (MW) from surface-drilling parameters, including standpipe pressure, rate of penetration, drill string rotation, and mud properties. In addition, by utilizing an artificial neural network (ANN) and a support vector machine (SVM), ECD was estimated with a correlation coefficient of 0.9947 and an average absolute percentage error of 0.23%. Meanwhile, a decision tree (DT) was employed to estimate MW with a correlation coefficient of 0.9353 and an average absolute percentage error of 1.66%. The two novel models were compared with artificial intelligence (AI) techniques to evaluate the developed models. The results proved that the two novel models were more accurate with the value obtained from pressure-while-drilling (PWD) tools. These models can be utilized during well design and while drilling operations are in progress to evaluate and monitor the appropriate mud weight and equivalent circulation density to save time and money, by eliminating the need for expensive downhole equipment and commercial software.

Achieving Practical Venue Recycle of Waste Oil-Based Drilling Fluids with Vacuum Distillation Technology

Drilling fluids are essential operating additives for extracting oil and shale gas. Thus, their pollution control and recycling utilization are significant to petrochemical development. Vacuum distillation technology was used in this research to handle waste oil-based drilling fluids and achieve reutilization. Briefly, recycled oil and recovered solids can be obtained from waste oil-based drilling fluids whose density is 1.24-1.37 g/cm³ by vacuum distillation under the condition of an external heat transfer oil temperature of 270 ± 5 °C and a reaction pressure below 5 × 10³ Pa. Meanwhile, recycled oil has excellent apparent viscosity (AV, 21 mPa·s) and plastic viscosity (PV, 14 mPa·s), which could be used as a substitute for 3# white oil. Furthermore, PF-ECOSEAL prepared by recycled solids exhibited better rheological properties (27.5 mPa·s AV, 18.5 mPa·s PV, and 9 Pa yield point) and plugging performance (32 mL V₀, 1.90 mL/min^1/2V_sf) than drilling fluids prepared with the conventional plugging agent PF-LPF. Our work confirmed that vacuum distillation is a valid technology in innocuity treatment and resource utilization of drilling fluids and has great value in industrial applications.

Data-Driven Framework for Real-time Rheological Properties Prediction of Flat Rheology Synthetic Oil-Based Drilling Fluids

Appropriate mud properties enhance drilling efficiency and decision quality to avoid incidents. The detailed mud properties are mainly measured in laboratories and are usually measured twice a day in the field and take a long time. This prevents real-time mud performance optimization and adversely affects proactive actions. As a result, it is critical to evaluate mud properties while drilling to capture mud flow dynamics. Unlike other mud properties, mud density (MD) and Marsh funnel viscosity (MFV) are frequently evaluated every 15-20 min in the field. The goal of this study is to predict the rheological properties of flat rheology synthetic oil-based mud (SOBM) in real time using machine learning (ML) techniques such as random forest (RF) and decision tree (DT). A proposed approach is followed to first predict the viscometer readings at 300 and 600 RPM (R ₆₀₀ and R ₃₀₀) and then estimate the other mud properties using the existing equations in the literature. A set of data contained MD, MFV, and viscometer readings (R ₃₀₀ and R ₆₀₀) for different samples from the same mud type. The mud samples were collected after going through a shale shaker. MD and MFV are measured by a mud balance and a Marsh funnel, respectively, while rheology is evaluated using a viscometer. The data were randomly split into training, testing, and validation data sets. The ML models' performance was evaluated through average absolute percentage error (AAPE) and correlation coefficient (R). The proposed models predicted the viscometer readings as a middle stage with a low AAPE that did not exceed 4.5% for both models. The suggested models forecasted the rheological properties with a good degree of accuracy, with an AAPE being less than 7% for most of the parameters. The proposed models can save costs and time since there is no need to include additional tools in the rig location. Furthermore, these models will significantly aid in avoiding serious problems and achieving better rig hydraulics and hole cleaning, which in turn will technically and economically enhance drilling operations.

Vom Berg and Hahn–Eyring Drilling Fluid Rheological Models

This article presents rheological models of fluids used in the drilling practice. It discusses the principles of determining drilling fluid rheological parameters based on data acquired from measurements by means of viscometers used in the drilling practice. The authors propose the application of the three-parameter Vom Berg and Hahn–Eyring models not used in the drilling industry so far. Necessary relationships have been developed for these models, which enable the determination of rheological parameters. In order to account for the influence of different flow conditions on the value of drilling fluid rheological parameters, the approach proposing the determination of rheological parameters of a given three-parameter model separately for low shear rates and high shear rates has been suggested. A practical application of the methodology proposed in this paper for determining the rheological parameters of the three-parameter Vom Berg and Hahn–Eyring models is presented using real drilling fluids as an example. Using the author’s methodology for determining the optimum rheological model, called Rheosolution, described earlier in the paper “Selection of Suitable Rheological Model for Drilling Fluid Using Applied Numerical Methods”, published in Energies 2020, 13, 3192, and laboratory tests performed for this work (for cement slurries according to API standards), a strong correlation of the Vom Berg model and, in particular, the Hahn–Eyring model for such drilling fluids was demonstrated.