scholarly journals Development of Statistical Models for Predicting Losses based on the Characteristics of Discontinuities

2021 ◽  
Vol 21 (3) ◽  
pp. 102-108
Author(s):  
Vladislav I. Galkin ◽  
Daria V. Rezvukhina
Keyword(s):  
Statistical Modeling ◽  
Drilling Fluid ◽  
Complex Model ◽  
Seismic Exploration ◽  
Well Drilling ◽  
Linear Discriminant ◽  
Fourth Level ◽  
Wide Range ◽  
Calculation Results ◽  
Level Model

A method for predicting losses over the area of the deposit to minimize the risks of accidents and gas and oil and water showings for the Permian-Carboniferous reservoir of the Usinskoye field was developed. In addition, the analysis of the influence of faults on the number of losses in wells during drilling was carried out. Based on the more than 250 wells drilling analysis, it was revealed that a significant problem during drilling was the loss of drilling fluid. This complication was found in 46% of drilled wells. The intensity of the studied losses was in a wide range: from insignificant losses to strong ones, with a complete loss of mud circulation. The faults identified both from well drilling data and from seismic data were characterized by a different number of wells with and without losses. Using the combination of various statistical methods, individual and complex models for predicting losses in wells depending on the distance from the fault were obtained. Using multilevel probabilistic-statistical modeling, the study of the influence of faults on losses was carried out: initially, based on the data of all wells, regardless of the methods for identifying faults - the first-level model; by the method of identifying faults (drilling / seismic exploration) - second-level models; according to the data of individual faults - the model of the third level. At the fourth level, a complex model was built, which takes into account the calculation results obtained at the previous levels of statistical modeling. The presence of direct and inverse dependences of the absorption probability from the shortest distance to the fault was established. Using linear discriminant analysis, the results of predicting the probability of absorption were checked.

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).

Pipe stick problems of deep well drilling

2021 ◽  
Vol 66 (05) ◽  
pp. 192-195
Author(s):  
Rövşən Azər oğlu İsmayılov ◽  
Keyword(s):  
Drilling Fluid ◽  
Drill Pipe ◽  
Drill String ◽  
Differential Pressure ◽  
Drilling Mud ◽  
Fluid Circulation ◽  
Well Drilling ◽  
Deep Well ◽  
Pressure Pipe ◽  
Bottomhole Pressure

The aricle is about the pipe stick problems of deep well drilling. Pipe stick problem is one of the drilling problems. There are two types of pipe stick problems exist. One of them is differential pressure pipe sticking. Another one of them is mechanical pipe sticking. There are a lot of reasons for pipe stick problems. Indigators of differential pressure sticking are increase in torque and drug forces, inability to reciprocate drill string and uninterrupted drilling fluid circulation. Key words: pipe stick, mecanical pipe stick,difference of pressure, drill pipe, drilling mud, bottomhole pressure, formation pressure

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 Modelling mechanical properties of the multilayer composite materials with the polyamide core

2018 ◽  
Vol 157 ◽  
pp. 02052 ◽  
Author(s):  
Krzysztof Talaśka ◽  
Dominik Wojtkowiak
Keyword(s):  
Mechanical Properties ◽  
Composite Materials ◽  
High Strength ◽  
Conveyor Belt ◽  
Complex Model ◽  
Multilayer Composite ◽  
Thermosetting Polymers ◽  
Wide Range ◽  
Belt Conveyors ◽  
Polyamide Film

Due to the wide range of application for belt conveyors, engineers look for many different combinations of mechanical properties of conveyor and transmission belts. It can be made by creating multilayer or fibre reinforced composite materials from base thermoplastic or thermosetting polymers. In order to gain high strength with proper elasticity and friction coefficient, the core of the composite conveyor belt is made of polyamide film core, which can be combined with various types of polymer fabrics, films or even rubbers. In this paper authors show the complex model of multilayer composite belt with the polyamide core, which can be used in simulation analyses. The following model was derived based on the experimental research, which consisted of tensile, compression and shearing tests. In order to achieve the most accurate model, proper simulations in ABAQUS were made and then the results were compared with empirical mechanical characteristics of a conveyor belt. The main goal of this research is to fully describe the perforation process of conveyor and transmission belts for vacuum belt conveyors. The following model will help to develop design briefs for machines used for mechanical perforation.

Design and Calibration of Resistive Stress Sensors on 4H Silicon Carbide

2018 ◽  
Author(s):  
Richard C. Jaeger ◽  
Jun Chen ◽  
Jeffrey C. Suhling ◽  
Leonid Fursin
Keyword(s):  
Silicon Carbide ◽  
Integrated Circuits ◽  
Stress Sensitivity ◽  
Well Drilling ◽  
Deep Well ◽  
Stress Sensors ◽  
Wide Range ◽  
Higher Temperature ◽  
Van Der Pauw ◽  
Transverse Piezoresistance

Stress sensors have shown potential to provide “health monitoring” of a wide range of issues related to packaging of integrated circuits, and silicon carbide offers the advantage of much higher temperature sensor operation with application in packaged high-voltage, high-power SiC devices as well as both automotive and aerospace systems, geothermal plants, and deep well drilling, to name a few. This paper discusses the theory and uniaxial calibration of resistive stress sensors on 4H silicon carbide (4H-SiC) and provides new theoretical descriptions for four-element resistor rosettes and van der Pauw (VDP) stress sensors. The results delineate the similarities and differences relative to those on (100) silicon: resistors on the silicon face of 4H-SiC respond to only four of the six components of the stress state; a four-element rosette design exists for measuring the in-plane stress components; two stress quantities can be measured in a temperature compensated manner. In contrast to silicon, only one combined coefficient is required for temperature compensated stress measurements. Calibration results from a single VDP device can be used to calculate the basic lateral and transverse piezoresistance coefficients for 4H-SiC material. Experimental results are presented for lateral and transverse piezoresistive coefficients for van der Pauw structures and p- and n-type resistors. The VDP devices exhibit the expected 3.16 times higher stress sensitivity than standard resistor rosettes.

Assessment of Certainty of Ventilation Processes Mathematical Modeling

2015 ◽  
Vol 725-726 ◽  
pp. 1255-1260
Author(s):  
Tamara Daciuk ◽  
Vera Ulyasheva
Keyword(s):  
Mathematical Modeling ◽  
Turbulent Flows ◽  
Turbulence Models ◽  
Field Measurements ◽  
Heat Emission ◽  
Emission Sources ◽  
Wide Range ◽  
Calculation Results ◽  
Definition Of ◽  
Semiempirical Models

Numerical experiment has been successfully used during recent 10-15 years to solve a wide range of thermal and hydrogasodynamic tasks. Application of mathematical modeling used to design the ventilation systems for production premises characterized by heat emission may be considered to be an effective method to obtain reasonable solutions. Results of calculation performed with numerical solution of ventilation tasks depend on turbulence model selection. Currently a large number of different turbulence models used to calculate turbulent flows are known. Testing and definition of applicability limits for semiempirical models of turbulence should be considered to be a preliminary stage of calculation. This article presents results of test calculations pertaining to thermal air process modeling in premises characterized by presence of heat emission sources performed with employment of different models of turbulence. Besides, analysis of calculation results and comparison with field measurements data are presented.

scholarly journals Rapid prototyping of a complex model for the manufacture of plaster molds for slip casting ceramic

Cerâmica ◽  
2014 ◽  
Vol 60 (356) ◽  
pp. 465-470 ◽  
Author(s):  
D. P. C. Velazco ◽  
E. F. Sancet ◽  
F. Urbaneja ◽  
M. Piccico ◽  
M. F. Serra ◽  
...  
Keyword(s):  
Rapid Prototyping ◽  
New Technologies ◽  
Slip Casting ◽  
Complex Model ◽  
Computer Assisted ◽  
Plaster Mold ◽  
Digital Format ◽  
Wide Range ◽  
3D Scanners ◽  
Ceramic Manufacturing

Computer assisted designing (CAD) is well known for several decades and employed for ceramic manufacturing almost since the beginning, but usually employed in the first part of the projectual ideation processes, neither in the prototyping nor in the manufacturing stages. The rapid prototyping machines, also known as 3D printers, have the capacity to produce in a few hours real pieces using plastic materials of high resistance, with great precision and similarity with respect to the original, based on unprecedented digital models produced by means of modeling with specific design software or from the digitalization of existing parts using the so-called 3D scanners. The main objective of the work is to develop the methodology used in the entire process of building a part in ceramics from the interrelationship between traditional techniques and new technologies for the manufacture of prototypes. And to take advantage of the benefits that allow us this new reproduction technology. The experience was based on the generation of a complex piece, in digital format, which served as the model. A regular 15 cm icosahedron presented features complex enough not to advise the production of the model by means of the traditional techniques of ceramics (manual or mechanical). From this digital model, a plaster mold was made in the traditional way in order to slip cast clay based slurries, freely dried in air and fired and glazed in the traditional way. This experience has shown the working hypothesis and opens up the possibility of new lines of work to academic and technological levels that will be explored in the near future. This technology provides a wide range of options to address the formal aspect of a part to be performed for the field of design, architecture, industrial design, the traditional pottery, ceramic art, etc., which allow you to amplify the formal possibilities, save time and therefore costs when drafting the necessary and appropriate matrixes to each requirement.

A variety of surface waves in ocean-bottom DAS records

2021 ◽  
Author(s):  
Zack Spica ◽  
Loïc Viens ◽  
Jorge Castillo Castellanos ◽  
Takeshi Akuhara ◽  
Kiwamu Nishida ◽  
...  
Keyword(s):  
Surface Wave ◽  
Acoustic Waves ◽  
Fiber Optic ◽  
Acoustic Noise ◽  
Seismic Exploration ◽  
Ocean Bottom ◽  
Wide Range ◽  
Ocean Layer ◽  
Noise Cross Correlation ◽  
Low Amplitude

<p>Distributed acoustic sensing (DAS) can transform existing telecommunication fiber-optic cables into arrays of thousands of sensors, enabling meter-scale recordings over tens of kilometers. Recently, DAS has demonstrated its utility for many seismological applications onshore. However, the use of offshore cables for seismic exploration and monitoring is still in its infancy.<br>In this work, we introduce some new results and observations obtained from a fiber-optic cable offshore the coast of Sanriku, Japan. In particular, we focus on surface wave retrieved from various signals and show that ocean-bottom DAS can be used to extract dispersion curves (DC) over a wide range of frequencies. We show that multi-mode DC can be easily extracted from ambient seismo-acoustic noise cross-correlation functions or F-K analysis. Moderate magnitude earthquakes also contain multiple surface-wave packets that are buried within their coda. Fully-coupled 3-D numerical simulations suggest that these low-amplitude signals originate from the continuous reverberations of the acoustic waves in the ocean layer. </p>

The Practice of Structural Equation Modeling

2014 ◽  
pp. 2521-2530
Author(s):  
Ho Yin Wong ◽  
Jason Sit ◽  
Jia-Yi Hung
Keyword(s):  
Structural Equation Modeling ◽  
Statistical Modeling ◽  
Structural Equation ◽  
Sem Analysis ◽  
Modeling Technique ◽  
Equation Modeling ◽  
Business Analytics ◽  
Wide Range ◽  
Stage Process ◽  
Point Of Reference

The aim of this chapter is to act as a point of reference for researchers, especially new users, who would like to use structural equation modeling (SEM) to perform business analytics. SEM is a multipurpose statistical modeling technique that can be applied in various business disciplines and is a useful tool to conduct business analytics. This chapter explains some common terminologies in the SEM literature and states general steps of performing SEM analysis along with an integration of the wide range of views and empirical findings on the topic. The chapter discusses the assumptions of SEM analysis, followed by a three-stage process of conducting, which includes assumptions, specification, evaluation, and modifications.

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