Analysis of pipe sticking due to wellbore uncleanliness using machine learning.

Pipe sticking is a major problem that can result in significant downtime, lost productivity, and increased costs. The aim of this study is to develop an accurate and effective predictive model for pipe sticking due to wellbore uncleanliness using a range of classification algorithms. In this research work, the drilling data from two different reservoirs in India was pre-processed and eviscerated to ensure that it was suitable to process using classification algorithms. The data collected from two different reservoirs in India were analyzed using different machine learning algorithms to tackle the persistent challenges of pipe sticking during oil drilling operations. These algorithms were compared and evaluated based on their performance. The research finding indicates that the ensemble classifier algorithm performs better than a single classifier algorithm. It shows high generalization ability with an average accuracy of around 90 %. In addition to this, the ensemble classifier algorithm possesses good classification performance, and provides immunity from noisy data, offering strong support for real-time detection to prevent pipe sticking thereby reducing costly downtime.

The effect of lockdown during SARS-CoV-2 pandemic on maxillofacial injuries in a level I trauma centre: a comparative study.

INTRODUCTION: The SARS-CoV-2 pandemic forced many governments to impose nation-wide lockdowns. Government legislation forced limited travel on the population with restrictions on the normal way of life to limit spread of the SARS-CoV-2 virus. The aim of this study is to explore the effects of lockdown on the presentation of maxillofacial trauma in a level I trauma centre. METHODS: Comparative analysis was carried out using prospective and retrospective review of all consecutive patients admitted with any maxillofacial fracture in the lockdown period between 15th March and 15th June 2020 with the same period in 2019 to a Regional Trauma Maxillofacial Surgery Unit. Data included basic demographics and mechanism of injury including alcohol/drug influence, polytrauma, site of injury and treatment modality including escalation of care. RESULTS: Across both periods, there were a total of one hundred and five (n = 105) recorded episodes of traumatic fractures with fifty-three (n = 53) in the pre-lockdown cohort and fifty-two (n = 52) in the lockdown. Included patients were significantly (p = 0.024) older during lockdown (mean age 41.44 years SD 20.70, range 5-96) with no differences in gender distribution between cohorts (p = 0.270). Patients in lockdown were more likely to be involved in polytrauma (p < 0.05) and have sustained their injury by cycling/running or any outdoor related activity (p = 0.013). Lockdown saw a significant reduction in alcohol and drug related violence (p < 0.05). Significantly more patients required operative management (p = 0.038). CONCLUSION: Local lockdowns form part of the governments public health strategy for managing future outbreaks of SARS-CoV-2. Our study showed no significant reduction in volume of trauma during lockdown. It is vital that hospitals maintain trauma capacity to ensure that patients are treated in a timely manner.

Antimicrobial regimens used in the treatment of mandibular fractures in UK maxillofacial units: changes over 12 years.

In the case of most mandibular fractures, the prescription of antimicrobials for more than 24 hours postoperatively confers no clinical benefit. To establish the prescribing patterns for mandibular fractures in UK OMFS units, and to compare them with those used 12 years ago, we did a telephone and email survey of OMFS units in the UK. Antimicrobials were prescribed for more than 24 hours postoperatively by 76 units (65%) (considerably fewer than the 82 (87%) in 2005). The most commonly prescribed first-line antimicrobial was co-amoxiclav (75%). Although there has been some improvement since 2005, most units still prescribe antimicrobials for periods longer than 24 hours. National collaboration may improve their appropriate prescription.