Insights into the Relationship between Equivalent Circulation Density and Drilling Fluid Rheological Properties

2019 ◽  
Author(s):  
Abo Taleb T. Al-Hameedi ◽  
Husam H. Alkinani ◽  
Shari Dunn-Norman ◽  
Ahmed S. Amer
Keyword(s):  
Rheological Properties ◽  
Drilling Fluid ◽  
The Relationship

Using the alveograph in developing requirements for the quality of flour for wafer sheet production

2020 ◽  
Vol 29 (12) ◽  
pp. 52-58
Author(s):  
E.P. Meleshkina ◽  
◽  
S.N. Kolomiets ◽  
A.S. Cheskidova ◽  
◽  
...  
Keyword(s):  
Rheological Properties ◽  
Quality Indicators ◽  
Wheat Flour ◽  
Mathematical Statistics ◽  
Intended Purpose ◽  
The Future ◽  
Relationship Of ◽  
The Relationship

Objectively and reliably determined indicators of rheological properties of the dough were identified using the alveograph device to create a system of classifications of wheat and flour from it for the intended purpose in the future. The analysis of the relationship of standardized quality indicators, as well as newly developed indicators for identifying them, differentiating the quality of wheat flour for the intended purpose, i.e. for finished products. To do this, we use mathematical statistics methods.

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 Comparison of the Effects of Conching Parameters on the Contents of Three Dominant Flavan3-ols, Rheological Properties and Sensory Quality in Chocolate Milk Mass Based on Liquor from Unroasted Cocoa Beans

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2502
Author(s):  
Bogumiła Urbańska ◽  
Hanna Kowalska ◽  
Karolina Szulc ◽  
Małgorzata Ziarno ◽  
Irina Pochitskaya ◽  
...  
Keyword(s):  
Rheological Properties ◽  
Yield Stress ◽  
Sensory Quality ◽  
Raw Material ◽  
Antioxidant Compounds ◽  
Chocolate Milk ◽  
Cocoa Beans ◽  
Variable Parameters ◽  
The Relationship ◽  
Manufacturing Parameters

The content of polyphenols in chocolate depends on many factors related to the properties of raw material and manufacturing parameters. The trend toward developing chocolates made from unroasted cocoa beans encourages research in this area. In addition, modern customers attach great importance to how the food they consume benefits their bodies. One such benefit that consumers value is the preservation of natural antioxidant compounds in food products (e.g., polyphenols). Therefore, in our study we attempted to determine the relationship between variable parameters at the conching stage (i.e., temperature and time of) and the content of dominant polyphenols (i.e.,catechins, epicatechins, and procyanidin B2) in chocolate milk mass (CMM) obtained from unroasted cocoa beans. Increasing the conching temperature from 50 to 60 °C decreased the content of three basic flavan-3-ols. The highest number of these compounds was determined when the process was carried out at 50 °C. However, the time that caused the least degradation of these compounds differed. For catechin, it was 2 h; for epicatechin it was 1 h; and for procyanidin it was 3 h. The influence of both the temperature and conching time on the rheological properties of chocolate milk mass was demonstrated. At 50 °C, the viscosity and the yield stress of the conched mass showed its highest value.

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.

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