Predictive Modelling of Drilling Fluid Rheology: Numerical, Analytical, Experimental and Statistical Studies of Marsh Funnel Flow

2020 ◽  
Author(s):  
Paul Ofoche ◽  
Samuel Noynaert
Keyword(s):  
Drilling Fluid ◽  
Predictive Modelling ◽  
Statistical Studies ◽  
Marsh Funnel ◽  
Funnel Flow ◽  
Fluid Rheology

Interdisciplinary Approach for Wellbore Stability During Slimhole Drilling at Volga-Urals Basin Oilfield

2021 ◽  
Author(s):  
Anna Vladimirovna Norkina ◽  
Sergey Mihailovich Karpukhin ◽  
Konstantin Urjevich Ruban ◽  
Yuriy Anatoljevich Petrakov ◽  
Alexey Evgenjevich Sobolev
Keyword(s):  
Drilling Fluid ◽  
Interdisciplinary Approach ◽  
Wellbore Stability ◽  
Vertical Wells ◽  
Wellbore Instability ◽  
Water Based ◽  
Chemical Studies ◽  
Fluid Rheology ◽  
Selection Of

Abstract The design features and the need to use a water-based solution make the task of ensuring trouble-free drilling of vertical wells non-trivial. This work is an example of an interdisciplinary approach to the analysis of the mechanisms of instability of the wellbore. Instability can be caused by a complex of reasons, in this case, standard geomechanical calculations are not enough to solve the problem. Engineering calculations and laboratory chemical studies are integrated into the process of geomechanical modeling. The recommendations developed in all three areas are interdependent and inseparable from each other. To achieve good results, it is necessary to comply with a set of measures at the same time. The key tasks of the project were: determination of drilling density, tripping the pipe conditions, parameters of the drilling fluid rheology, selection of a system for the best inhibition of clay swelling.

Scaling Formulae for the Wellbore Hydraulics Similitude with Drill Pipe Rotation and Eccentricity

2021 ◽  
Author(s):  
Thad Nosar ◽  
Pooya Khodaparast ◽  
Wei Zhang ◽  
Amin Mehrabian
Keyword(s):  
Power Law ◽  
Flow Rate ◽  
Annular Flow ◽  
Rotation Speed ◽  
Drilling Fluid ◽  
Drill Pipe ◽  
Flow Loop ◽  
Annular Flows ◽  
Fluid Rheology ◽  
Pipe Rotation

Abstract Equivalent circulation density of the fluid circulation system in drilling rigs is determined by the frictional pressure losses in the wellbore annulus. Flow loop experiments are commonly used to simulate the annular wellbore hydraulics in the laboratory. However, proper scaling of the experiment design parameters including the drill pipe rotation and eccentricity has been a weak link in the literature. Our study uses the similarity laws and dimensional analysis to obtain a complete set of scaling formulae that would relate the pressure loss gradients of annular flows at the laboratory and wellbore scales while considering the effects of inner pipe rotation and eccentricity. Dimensional analysis is conducted for commonly encountered types of drilling fluid rheology, namely, Newtonian, power-law, and yield power-law. Appropriate dimensionless groups of the involved variables are developed to characterize fluid flow in an eccentric annulus with a rotating inner pipe. Characteristic shear strain rate at the pipe walls is obtained from the characteristic velocity and length scale of the considered annular flow. The relation between lab-scale and wellbore scale variables are obtained by imposing the geometric, kinematic, and dynamic similarities between the laboratory flow loop and wellbore annular flows. The outcomes of the considered scaling scheme is expressed in terms of closed-form formulae that would determine the flow rate and inner pipe rotation speed of the laboratory experiments in terms of the wellbore flow rate and drill pipe rotation speed, as well as other parameters of the problem, in such a way that the resulting Fanning friction factors of the laboratory and wellbore-scale annular flows become identical. Findings suggest that the appropriate value for lab flow rate and pipe rotation speed are linearly related to those of the field condition for all fluid types. The length ratio, density ratio, consistency index ratio, and power index determine the proportionality constant. Attaining complete similarity between the similitude and wellbore-scale annular flow may require the fluid rheology of the lab experiments to be different from the drilling fluid. The expressions of lab flow rate and rotational speed for the yield power-law fluid are identical to those of the power-law fluid case, provided that the yield stress of the lab fluid is constrained to a proper value.

Application of R/S Rheometer in Low Temperature Drilling Fluid Rheology Determination

2012 ◽  
Vol 490-495 ◽  
pp. 3114-3118
Author(s):  
Xiao Ling Jiang ◽  
Zong Ming Lei ◽  
Kai Wei
Keyword(s):  
Shear Stress ◽  
Shear Rate ◽  
Low Temperature ◽  
High Speed ◽  
Drilling Fluid ◽  
Drilling Fluids ◽  
Rheological Parameter ◽  
Fluid Temperature ◽  
Fluid Rheology ◽  
Rotary Viscometer

With six-speed rotary viscometer measuring the rheology of drilling fluid at low temperature, during the high-speed process, the drilling fluid temperature is not constant at low temperature, which leads to the inaccuracy in rheological measurement. When R/S rheometer is used cooperating with constant low-temperature box , the temperature remains stable during the process of determining the drilling fluid rheology under low temperature. The R/S rheometer and the six-speed rotational viscometer are both coaxial rotational viscometers, but they work in different ways and the two cylindrical clearance between them are different.How to make two viscometer determination result can maintain consistent?The experimental results show that, The use of R/S rheometer, with the shear rate for 900s-1 shear stress values instead of six speed rotary viscometer shear rate for 1022s-1 shear stress values.Then use two-point formula to calculate rheological parameters.The R/S rheometer rheological parameter variation with temperature has a good linear relationship,Can better reflect the rheological properties of drilling fluids with low temperature changerule

Development of New Models to Determine the Rheological Parameters of Water-based Drilling Fluid Using Artificial Intelligence

2021 ◽  
Author(s):  
Farqad Hadi ◽  
Ali Noori ◽  
Hussein Hussein ◽  
Ameer Khudhair
Keyword(s):  
Rheological Properties ◽  
High Performance ◽  
Drilling Fluid ◽  
Gel Strength ◽  
Solid Content ◽  
Rheological Parameters ◽  
Water Based ◽  
Fluid Properties ◽  
Drilling Operations ◽  
Marsh Funnel

Abstract It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works present valid and reliable results, they are expensive and time consuming. On the other hand, continuous and regular determination of the rheological mud properties can perform its essential functions during well construction. More uncertainties in planning the drilling fluid properties meant that more challenges may be exposed during drilling operations. This study presents two predictive techniques, multiple regression analysis (MRA) and artificial neural networks (ANNs), to determine the rheological properties of water-based drilling fluid based on other simple measurable properties. While mud density (MW), marsh funnel (MF), and solid% are key input parameters in this study, the output functions or models are plastic viscosity (PV), yield point (YP), apparent viscosity (AV), and gel strength. The prediction methods were demonstrated by means of a field case in eastern Iraq, using datasets from daily drilling reports of two wells in addition to the laboratory measurements. To test the performance ability of the developed models, two error-based metrics (determination coefficient R2 and root mean square error RMSE) have been used in this study. The current results of this study support the evidence that MW, MF, and solid% are consistent indexes for the prediction of rheological properties. Both mud density and solid content have a relative-significant effect on increasing PV, YP, AV, and gel strength. However, a scattering around each fit curve is observed which proved that one rheological property alone is not sufficient to estimate other properties. The results also reveal that both MRA and ANN are conservative in estimating the fluid rheological properties, but ANN is more precise than MRA. Eight empirical mathematical models with high performance capacity have been developed in this study to determine the rheological fluid properties based on simple and quick equipment as mud balance and marsh funnel. This study presents cost-effective models to determine the rheological fluid properties for future well planning in Iraqi oil fields.

scholarly journals Newly Developed Correlations to Predict the Rheological Parameters of High-Bentonite Drilling Fluid Using Neural Networks

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2787
Author(s):  
Ahmed Gowida ◽  
Salaheldin Elkatatny ◽  
Khaled Abdelgawad ◽  
Rahul Gajbhiye
Keyword(s):  
Rheological Properties ◽  
Drilling Fluid ◽  
Rheological Parameters ◽  
Percentage Error ◽  
Cleaning Efficiency ◽  
Periodic Monitoring ◽  
Data Points ◽  
Ann Models ◽  
Artificial Neural Network Ann ◽  
Marsh Funnel

High-bentonite mud (HBM) is a water-based drilling fluid characterized by its remarkable improvement in cutting removal and hole cleaning efficiency. Periodic monitoring of the rheological properties of HBM is mandatory for optimizing the drilling operation. The objective of this study is to develop new sets of correlations using artificial neural network (ANN) to predict the rheological parameters of HBM while drilling using the frequent measurements, every 15 to 20 min, of mud density (MD) and Marsh funnel viscosity (FV). The ANN models were developed using 200 field data points. The dataset was divided into 70:30 ratios for training and testing the ANN models respectively. The optimized ANN models showed a significant match between the predicted and the measured rheological properties with a high correlation coefficient (R) higher than 0.90 and a maximum average absolute percentage error (AAPE) of 6%. New empirical correlations were extracted from the ANN models to estimate plastic viscosity (PV), yield point (YP), and apparent viscosity (AV) directly without running the models for easier and practical application. The results obtained from AV empirical correlation outperformed the previously published correlations in terms of R and AAPE.

Assessment and prediction of cement paste flow behavior; Marsh-funnel flow time and mini-slump values

2021 ◽  
Vol 301 ◽  
pp. 124072
Author(s):  
Ali Mardani-Aghabaglou ◽  
Hasan Tahsin Öztürk ◽  
Murat Kankal ◽  
Kambiz Ramyar
Keyword(s):  
Cement Paste ◽  
Flow Behavior ◽  
Flow Time ◽  
Marsh Funnel ◽  
Funnel Flow
Sign in / Sign up

Export Citation Format

Share Document