Tribological properties of rock-bit journal bearings tribo-pair with micro-dimples under contaminated grease lubrication

2021 ◽  
pp. 135065012110700
Author(s):  
Lin Zhong ◽  
Guirong Kang ◽  
Guorong Wang ◽  
Gang Wei ◽  
Zixuan Wang ◽  
...  
Keyword(s):  
Rheological Properties ◽  
Failure Modes ◽  
Adhesive Wear ◽  
Drilling Fluid ◽  
Area Ratio ◽  
Fluid Volume ◽  
Grease Lubrication ◽  
Friction Performance ◽  
Micro Dimples ◽  
Rock Bit

The failure of bit bearings is one of the main factors that restrict the life of a bit, and studies revealed that sealing and adhesive wear failure are common failure modes of bit bearings. To study the adaptability of the optimal textures to anti-wear and anti-friction performance of an 8 1/2” rock bit journal bearingunder sealing leakage conditions, the rheological properties of grease in the range of 0%–50% of the water-based drilling fluid volume in the compound lithium-based grease (rock bit grease) were tested. For the cylindrical dimples (diameter: 300 μm; depth: 40 μm, area ratio: 5%) and elliptical dimples (major and minor axis of 720 and 360 μm, respectively; depth: 40 μm, area ratio: 10%), the experimental study on the wear resistance of the optimized texture tribo-pairs was carried out as the grease invaded different drilling fluid contents based on the pin-disk pair. Results showed that the drilling fluid volume in the rock bit grease significantly affected the rheological properties of the grease. Furthermore, the cylindrical and elliptical dimples still had good anti-wear and anti-friction effects. Especially when the drilling fluid volume ratios in the grease reached 50%, the elliptical dimples can still reduce the friction coefficient and wear amount of the pair by 19.88% and 56.99%, respectively. With the increase of drilling fluid invasion into grease, the wear morphology of the un-textured tribo-pairs showed that the wear form changed from abrasive to adhesive wear, while that of the preferred textured tribo-pairs indicated slight abrasive wear.

scholarly journals Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1377
Author(s):  
Musaab I. Magzoub ◽  
Raj Kiran ◽  
Saeed Salehi ◽  
Ibnelwaleed A. Hussein ◽  
Mustafa S. Nasser
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Nearest Neighbor ◽  
Drilling Fluid ◽  
Gradient Boosting ◽  
K Nearest Neighbor ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Drilling Operations

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can be further used for hydraulic calculations. Overall, the experimental study presented in this paper, together with the proposed ML-based framework, adds valuable information to the design of PAM/PEI-based mud. The ML models allowed a wide range of rheology assessments for various drilling fluid formulations with a mean accuracy of up to 91%. The case study has shown that with the appropriate combination of materials, reasonable rheological properties could be achieved to prevent loss circulation by managing the equivalent circulating density (ECD).

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

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3592
Author(s):  
Naipeng Liu ◽  
Di Zhang ◽  
Hui Gao ◽  
Yule Hu ◽  
Longchen Duan
Keyword(s):  
Decision Making ◽  
Rheological Properties ◽  
Real Time ◽  
Drilling Fluid ◽  
Time Measurement ◽  
Decision Making Process ◽  
Rate Of Penetration ◽  
The Real ◽  
Real Time Measurement ◽  
Fluid Properties

The accurate and frequent measurement of the drilling fluid’s rheological properties is essential for proper hydraulic management. It is also important for intelligent drilling, providing drilling fluid data to establish the optimization model of the rate of penetration. Appropriate drilling fluid properties can improve drilling efficiency and prevent accidents. However, the drilling fluid properties are mainly measured in the laboratory. This hinders the real-time optimization of drilling fluid performance and the decision-making process. If the drilling fluid’s properties cannot be detected and the decision-making process does not respond in time, the rate of penetration will slow, potentially causing accidents and serious economic losses. Therefore, it is important to measure the drilling fluid’s properties for drilling engineering in real time. This paper summarizes the real-time measurement methods for rheological properties. The main methods include the following four types: an online rotational Couette viscometer, pipe viscometer, mathematical and physical model or artificial intelligence model based on a Marsh funnel, and acoustic technology. This paper elaborates on the principle, advantages, limitations, and usage of each method. It prospects the real-time measurement of drilling fluid rheological properties and promotes the development of the real-time measurement of drilling rheological properties.

Annular Frictional Pressure Losses During Drilling—Predicting the Effect of Drillstring Rotation

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Arild Saasen
Keyword(s):  
Rheological Properties ◽  
Pressure Loss ◽  
Drilling Fluid ◽  
Axial Flow ◽  
Drilling Fluids ◽  
Unstable Flow ◽  
Pressure Losses ◽  
Shear Dependent Viscosity ◽  
Water Based ◽  
Dependent Viscosity

Controlling the annular frictional pressure losses is important in order to drill safely with overpressure without fracturing the formation. To predict these pressure losses, however, is not straightforward. First of all, the pressure losses depend on the annulus eccentricity. Moving the drillstring to the wall generates a wider flow channel in part of the annulus which reduces the frictional pressure losses significantly. The drillstring motion itself also affects the pressure loss significantly. The drillstring rotation, even for fairly small rotation rates, creates unstable flow and sometimes turbulence in the annulus even without axial flow. Transversal motion of the drillstring creates vortices that destabilize the flow. Consequently, the annular frictional pressure loss is increased even though the drilling fluid becomes thinner because of added shear rate. Naturally, the rheological properties of the drilling fluid play an important role. These rheological properties include more properties than the viscosity as measured by API procedures. It is impossible to use the same frictional pressure loss model for water based and oil based drilling fluids even if their viscosity profile is equal because of the different ways these fluids build viscosity. Water based drilling fluids are normally constructed as a polymer solution while the oil based are combinations of emulsions and dispersions. Furthermore, within both water based and oil based drilling fluids there are functional differences. These differences may be sufficiently large to require different models for two water based drilling fluids built with different types of polymers. In addition to these phenomena washouts and tool joints will create localised pressure losses. These localised pressure losses will again be coupled with the rheological properties of the drilling fluids. In this paper, all the above mentioned phenomena and their consequences for annular pressure losses will be discussed in detail. North Sea field data is used as an example. It is not straightforward to build general annular pressure loss models. This argument is based on flow stability analysis and the consequences of using drilling fluids with different rheological properties. These different rheological properties include shear dependent viscosity, elongational viscosity and other viscoelastic properties.

Thermal energy storage technology to control rheological properties of drilling fluid

2021 ◽  
pp. 116931
Author(s):  
Marcus Vinicius Gomes Paixão ◽  
Rafael da Silva Fernandes ◽  
Elessandre Alves de Souza ◽  
Rosangela de Carvalho Balaban
Keyword(s):  
Energy Storage ◽  
Rheological Properties ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Drilling Fluid ◽  
Storage Technology ◽  
Energy Storage Technology

Comparative Analysis of the Rheological Behaviour of Irvingia Gabonensis Ogbono and Foreign Polymer for Bentonite Formulated Mud.

2021 ◽  
Author(s):  
Emmanuel Ayodele ◽  
David Ekuma ◽  
Ikechukwu Okafor ◽  
Innocent Nweze
Keyword(s):  
Rheological Properties ◽  
Oil And Gas ◽  
Drilling Fluid ◽  
Research Work ◽  
Rheological Behaviour ◽  
Oil And Gas Industry ◽  
Drilling Mud ◽  
Gas Industry ◽  
Local Product ◽  
Irvingia Gabonensis

Abstract Drilling fluid are complex fluids consisting of several additives. These additives are added to enhance and control the rheological properties (such as viscosity, gel strength and yield point) of the mud. These properties are controlled for effective drilling of a well. This research work is focused on determining the rheological behavior of drilling mud using industry-based polymer and Irvingia Gabonensis (ogbono) as viscosifiers. Water based muds were formulated from the aforementioned locally sourced viscosifier and that of the conventional used viscosifier (Carboxylmetyl cellulose, CMC). Laboratory tests were carried out on the different muds formulated and their rheological properties (such as yield stress, shear stress, plastic viscosity and shear rate) are evaluated. The concentration of the viscosifiers were varied. The expected outcome of the research work aims at lowering the total drilling cost by reducing the importation of foreign polymer which promotes the development of local content in the oil and gas industry. The research compares the rheology of mud samples and the effect of varying the concentration (2g, 4g, 6g, 8g, and 10g) of both CMC and Ogbono and determining the changes in their rheological properties. The total volume of each mud sample is equivalent to 350ml which represent one barrel (42gal) in the lab. From the result, at concentration of 2g, the ogbono mud has a better rheology than the CMC mud, but at a concentration above 2g, CMC mud shows a better rheology than ogbono mud, that is, as the concentration of CMC is increased, the rheological properties of the mud increased while as the concentration of ogbono is increased the rheological properties decreased. The viscosity of the drilling fluid produced from the ogbono were lower than that of CMC, it could be used together with another local product such as cassava starch, offor or to further improve the rheology and then be a substitute to the conventional viscosifiers.

Development of Digital Twins for Drilling Fluids: Local Velocities for Hole Cleaning and Rheology Monitoring

2021 ◽  
Author(s):  
Mehrdad Gharib Shirangi ◽  
Roger Aragall ◽  
Reza Ettehadi ◽  
Roland May ◽  
Edward Furlong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Drilling Fluid ◽  
Training Data ◽  
Drilling Fluids ◽  
Hole Cleaning ◽  
Digital Twins ◽  
Wide Range ◽  
Drilling Operations ◽  
Cuttings Bed

Abstract In this work, we present our advances to develop and apply digital twins for drilling fluids and associated wellbore phenomena during drilling operations. A drilling fluid digital twin is a series of interconnected models that incorporate the learning from the past historical data in a wide range of operational settings to determine the fluids properties in realtime operations. From several drilling fluid functionalities and operational parameters, we describe advancements to improve hole cleaning predictions and high-pressure high-temperature (HPHT) rheological properties monitoring. In the hole cleaning application, we consider the Clark and Bickham (1994) approach which requires the prediction of the local fluid velocity above the cuttings bed as a function of operating conditions. We develop accurate computational fluid dynamics (CFD) models to capture the effects of rotation, eccentricity and bed height on local fluid velocities above cuttings bed. We then run 55,000 CFD simulations for a wide range of operational settings to generate training data for machine learning. For rheology monitoring, thousands of lab experiment records are collected as training data for machine learning. In this case, the HPHT rheological properties are determined based on rheological measurement in the American Petroleum Institute (API) condition together with the fluid type and composition data. We compare the results of application of several machine learning algorithms to represent CFD simulations (for hole cleaning application) and lab experiments (for monitoring HPHT rheological properties). Rotating cross-validation method is applied to ensure accurate and robust results. In both cases, models from the Gradient Boosting and the Artificial Neural Network algorithms provided the highest accuracy (about 0.95 in terms of R-squared) for test datasets. With developments presented in this paper, the hole cleaning calculations can be performed more accurately in real-time, and the HPHT rheological properties of drilling fluids can be estimated at the rigsite before performing the lab experiments. These contributions advance digital transformation of drilling operations.

scholarly journals Comparative Analysis of the Effect of Barite and Hematite on the Rheology of Water-Based Drilling Mud

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Osei H
Keyword(s):  
Rheological Properties ◽  
Drilling Fluid ◽  
Attrition Rate ◽  
Drilling Mud ◽  
Cleaning Efficiency ◽  
Drilling Operation ◽  
Water Based ◽  
Petroleum Resources ◽  
Drilling Muds ◽  
The Impact

High demand for oil and gas has led to exploration of more petroleum resources even at remote areas. The petroleum resources are found in deeper subsurface formations and drilling into such formations requires a well-designed drilling mud with suitable rheological properties in order to avoid or reduce associated drilling problems. This is because rheological properties of drilling muds have considerable effect on the drilling operation and cleaning of the wellbore. Mud engineers therefore use mud additives to influence the properties and functions of the drilling fluid to obtain the desired drilling mud properties especially rheological properties. This study investigated and compared the impact of barite and hematite as weighting agents for water-based drilling muds and their influence on the rheology. Water-based muds of different concentrations of weighting agents (5%, 10%, 15% and 20% of the total weight of the drilling mud) were prepared and their rheological properties determined at an ambient temperature of 24ᵒC to check their impact on drilling operation. The results found hematite to produce higher mud density, plastic viscosity, gel strength and yield point when compared to barite at the same weighting concentrations. The higher performance of the hematite-based muds might be attributed to it having higher specific gravity, better particle distribution and lower particle attrition rate and more importantly being free from contaminants. The water-based muds with hematite will therefore be more promising drilling muds with higher drilling and hole cleaning efficiency than those having barite.

Nanoemulsion with Controlled Rheology under Different Temperature for Effective Removal of Oil-based Drilling Fluid in Offshore Drilling

2021 ◽  
Author(s):  
Renzhou Meng ◽  
Chengwen Wang ◽  
Xiliang Dong ◽  
Chao Xiong
Keyword(s):  
High Temperature ◽  
Low Temperature ◽  
Rheological Properties ◽  
Drilling Fluid ◽  
Offshore Drilling ◽  
Emulsion Droplets ◽  
Effective Removal ◽  
Engineering Requirement ◽  
Important Means ◽  
The Stability

Abstract Oil-based drilling fluid (OBDF) is an important means for offshore drilling, but it would affect the cementing quality. Nanoemulsions shows potential for OBDF removal, but how to prepare nanoemulsion meeting the engineering requirement is lack of good understanding. Moreover, nanoemulsions usually behave badly under low/high temperature, which would restrict the application. Revealing removal mechanisms of nanoemulsion and improving nanoemulsion stability at different temperature are of great significance. The nanoemulsion could rapidly spread on the wellbore surfaces, cause the adhering OBDF to curl into little droplets, and solubilize the removed OBDF. The removal efficiency can reach more than 98%. Low temperature and higher concentration of dispersed phase both increased the viscosity of nanoemulsions stabilized by surfactants. PEGs can induce the bridging of emulsion droplets at low temperature, leading to significant increase of nanoemulsions viscoelasticity at low temperature (around 5°C). To control the rheological properties of nanoemulsions, a hydrophobic association polymer, HAAP, was proposed. Nanoemulsions containing HAAP does not gel at low temperature (< 15°C). And the viscoelasticity of nanoemulsions increased slightly when the temperature is higher than 70°C because of the thermoassociating behavior of polymer, which can ensure the stability of the nanoemulsions at high temperature. This paper is helpful to establish a generic route for preparing nanoemulsions with controlled rheological properties under different temperature, which is benefit for their applications in offshore.

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.

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