Insights into application of acorn shell powder in drilling fluid as environmentally friendly additive: filtration and rheology

Davoodi, Shadfar; Rukavishnikov, Valeriy S.; Minaev, Konstantin M.

doi:10.1007/s13762-020-02880-0

Cited by 29 publications

(6 citation statements)

References 51 publications

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“…Te rheological properties and parameters of drilling fuid, including the PV, apparent viscosity (AV), YP, fow index (n), consistency index (k), density, fuid loss, gel strength, and regime of drilling fuids, are critical for efective hole cleaning during drilling operations [8,24,25]. PV is a measure of the internal friction in the fuid under fow.…”

Section: The Impact Of Rheological Properties and Parameters On Hole-...mentioning

confidence: 99%

Hole Cleaning during Drilling Oil and Gas Wells: A Review for Hole-Cleaning Chemistry and Engineering Parameters

Al-Rubaii,

Al-Shargabi,

Al-Shehri

2023

Advances in Materials Science and Engineering

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Efficient hole cleaning during drilling operations is critical to maintain a high rate of penetration and smooth drilling, leading to minimum drilling problems and economical drilling efficiency. This process involves several important factors, including pipe-sticking incidents, higher cuttings concentrations in the annulus, noisy vibration of the drill string, erratic equivalent circulating density, lost circulation incidents, well control incidents, geomechanical hole section instability, tight spots during tripping operations, and excessive usage of chemical additives for conditioning hole sections and mud. Various approaches, including correlations, methodologies, developments, algorithms, equipment, charts, field experience, chemicals, and studies involving experiments, can be used to enhance the efficiency of hole cleaning. The development of hole-cleaning models is important for use as hole-cleaning indicators to ensure optimized drilling efficiency. This paper presents a comprehensive overview of the complex field of hole cleaning in the oil and gas industry. It includes techniques, tools, models, and chemical additives. It also encompasses drilling engineering, operations, and chemistry. To facilitate the transit of drill cuttings, maintain hole section stability, cool and lubricate the drill bit, and transmit hydraulic horsepower, this article outlines the important roles of drilling fluids. The significance of chemical additives, including nanoparticles, natural and modified polymers, and synthetic polymers, in preserving wellbore stability, improving drilling efficiency, and lowering drill bit wear is also covered in the study. It concludes by making recommendations for further study to clarify hole cleaning for the reader to facilitate and boost drilling efficiency.

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Section: The Impact Of Rheological Properties and Parameters On Hole-...mentioning

confidence: 99%

Hole Cleaning during Drilling Oil and Gas Wells: A Review for Hole-Cleaning Chemistry and Engineering Parameters

Al-Rubaii,

Al-Shargabi,

Al-Shehri

2023

Advances in Materials Science and Engineering

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“…In this way, mechanized thinking methods have truly been used in different areas of the oil and gas industry, as shown under. Supplies (Ghorbani et al, 2017b); oil well wandering (Abdali et al, 2021); harm to the game plan (Mohammadian and Ghorbani, 2015), wellbore disparity (Darvishpour et al, 2019), rheology and ltration (Davoodi et al, 2019(Davoodi et al, , 2020, and development (Ghorbani and Moghadasi, 2014a; Ghorbani and other, 2014b;et al, 2017a) and 2019 entry uid). A geomechanical strategy and shear modulus-based check of bundling breakdown (Moradi, H.,2012).…”

Section: Introductionmentioning

confidence: 99%

Machine learning and Artificial Intelligence Techniques to Expect Drilling Fluid Density , Rate Infiltration and Loss Circulation Anticipation

Mahamadou,

Jun

2024

Preprint

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The success of drilling operations depends on several factors, including the drilling properties, and environmental and financial constraints. However, relying solely on lab testing is often insufficient due to limited resources and time. Drilling operations can result in significant costs due to loss of circulation. To address this issue, we propose using AI and machine learning techniques to predict drilling fluid density and prevent circulation loss using an intelligent approach. We conducted scientific evaluations of the rheological properties and mud components of polyacrylamide/polyethyleneimine (PAM) mud. Four distinct ML algorithms (the adaptive neuro-fuzzy inference system, particle swarm optimization-based adaptive neuro-fuzzy inference system, least squares support vector machine with a genetic algorithm, and radial basis function) were used to investigate the rheological qualities of various mud components at different concentrations and test conditions. In the LSSVM-GA model, we found that the linear equation for predicting fluid density was "y = 1.0041x + 0.0019", with a correlation coefficient (R2) of 0.9966. The RBF model was used to predict fluid density due to its superior performance over other conventional models. The linear equation for predicting fluid density was "y = 1.0009x + 0.0034", with a correlation coefficient (R2) of 0.9999. Based on our experience, we have found that by using an appropriate combination of materials, we can achieve satisfactory rheological properties, thereby avoiding circulation loss incidents

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“…These methods include drilling fluid characteristics, bit and bottom hole assembly (BHA) designs, hydraulics, and rig systems [7,10]. The properties of the drilling fluid, such as its rheology, inhibition, and colloidal solids, can affect hole cleaning efficiency, with rheology playing a particularly crucial role in determining the fluid's ability to transport cuttings out of the wellbore [11,12]. The design of the bit and BHA can also impact the rate of penetration, allowable revolution per minute (RPM) and reciprocation, and by-pass area, which in turn can affect the efficiency of cuttings removal from the wellbore [10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time

et al. 2023

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The drilling industry has evolved significantly over the years, with new technologies making the process more efficient and effective. One of the most crucial issues of drilling is borehole cleaning, which entails removing drill cuttings and keeping the borehole clean. Inadequate borehole cleaning can lead to drilling problems such as stuck pipes, poor cementing, and formation damage. Real-time drilling evaluation has seen significant improvements, allowing drilling engineers to monitor the drilling process and make adjustments accordingly. This paper introduces a novel real-time borehole cleaning performance evaluation model based on the transport index (TIm). The novel TIm model offers a real-time indication of borehole cleaning efficiency. The novel model was field-tested and validated for three wells, demonstrating its ability to determine borehole cleaning efficiency in typical drilling operations. Using TIm in Well-A led to a 56% increase in the rate of penetration (ROP) and a 44% reduction in torque. Moreover, the efficient borehole cleaning obtained through the use of TIm played a significant role in improving drilling efficiency and preventing stuck pipes incidents. The TIm model was also able to identify borehole cleaning efficiency during a stuck pipe issue, highlighting its potential use as a tool for optimizing drilling performance.

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Insights into application of acorn shell powder in drilling fluid as environmentally friendly additive: filtration and rheology

Cited by 29 publications

References 51 publications

Hole Cleaning during Drilling Oil and Gas Wells: A Review for Hole-Cleaning Chemistry and Engineering Parameters

Hole Cleaning during Drilling Oil and Gas Wells: A Review for Hole-Cleaning Chemistry and Engineering Parameters

Machine learning and Artificial Intelligence Techniques to Expect Drilling Fluid Density , Rate Infiltration and Loss Circulation Anticipation

A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time

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