An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Hydrodynamic and hydromagnetic stability

CFD–DEM approach to investigate the effect of drill pipe rotation on cuttings transport behavior

Real time prediction of drilling fluid rheological properties using Artificial Neural Networks visible mathematical model (white box)

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Fundamentals of drilling engineering

Foam is one of the most frequently used drilling fluids for underbalanced drilling operations. This paper introduces a more accurate model than the existing models for estimating the pressure drop of foam flowing through the drill bit. The major difference between the proposed and existing models is that the proposed model includes the effect of foam expansion and velocity change as a function of pressure. It has been observed that pressure drop increases significantly as the upstream pressure and foam average velocity increases. For the same flow conditions, pressure drop decreases as the foam quality increases, and as the upstream pressure increases, pressure drop also increases. These events cannot be detected by existing models. In some cases, the pressure drop at the bit can be 10 times greater than the pressure drop predicted by existing models.

Drill Bit Pressure Drop During Foam Drilling Operations

Lightweight Hollow Glass Microspheres Drilling Fluid Flow Through Nozzles

Estimation of Cuttings Concentration and Frictional Pressure Losses During Drilling Using Data-Driven Models

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Evren Ozbayoglu

Papers

Drill Bit Pressure Drop During Foam Drilling Operations

Lightweight Hollow Glass Microspheres Drilling Fluid Flow Through Nozzles

Estimation of Cuttings Concentration and Frictional Pressure Losses During Drilling Using Data-Driven Models

Study of the performance of LCMs in fractured formations

Title: Advanced Cuttings Transport Study