In the past several decades, machine learning has gained increasing interest in the oil and
gas industry. This paper presents a comprehensive review of machine learning studies for …

Drilling wells in challenging oil/gas environments implies in large capital expenditure on
wellbore's construction. In order to optimize the drilling related operation, real-time decisions …

Rate of Penetration (ROP) can be considered as a crucial factor in optimization and cost
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …

Rate of penetration (ROP) prediction is crucial for the optimization and control in drilling
process due to its vital role in maximizing the drilling efficiency. This paper proposes a novel …

Data-driven models are widely used to predict rate of penetration. However, there are still
challenges on real-time predictions considering influences of formation properties and bit …

Rate of penetration (ROP) management is a matter of importance in drilling operations and it
has been considered in different studies. Different machine learning methods such as …

Large-scale cluster extended reach wells (ERWs) are usually drilled from one platform to
target distant multiple reservoirs in offshore oil & gas development. Due to the complicated …

Optimizing the drilling process for cost and efficiency requires faster drilling with a higher
rate of penetration (ROP). A high ROP usually indicates fast and cost-efficient drilling …

Accurate coal identification is critical in coal seam gas (CSG)(also known as coalbed
methane or CBM) developments because it determines well completion design and directly …

Drilling optimization has been studied extensively given its impact on an oil and gas project–
especially in a low-price environment. This is generally approached by optimizing the rate of …