... superiority with Convolutional Neural Network (CNN), Long Short-term Memory (LSTM), Bidirectional Long Short-term Memory (BiLSTM), and CNN-LSTM. Our proposed model achieves the highest accuracy with the same datasets. The CNN-BiLSTM outperforms other models owing to 1) its capacity to process image-based...

... consideration thermal method blockage threshold chemical treatment candidate selection field linear regression accuracy Introduction Maintaining high productivity of oil wells is economically important for operating companies. Typically, an oil well loses produced barrels per day gradually over...

... prediction scatter for mixing rules using mole fractions. However, it is unlikely to result in significantly degraded accuracy. It is noted that molecular weights are somewhat arbitrary for highly asphaltic oils (such as bitumens) since accurate experimental measurements of asphaltene molecular weights...

... the wellbore wall. Additionally, we analyze the effect of controllable variables on the accuracy of the distance calculation. upstream oil & gas algorithm imaging sensor fingerprint drilling operation artificial intelligence criterion sensor 1 directional drilling accuracy sensor image...

... with 93.5% accuracy during the hanger landing operation. The hardware prototype was deployed on two different rigs and successfully detected and confirmed the correct landing of wellhead components during all operations. The digital position sensing solution provides cost savings to operators by reducing...

.... Computer vision applied at the shaker will increase overall ROP, greatly improve the speed and accuracy of wellbore instability detection, reduce the exposure in a hazardous zone and improve the detection of pending downhole problems. neural network upstream oil & gas annular pressure drilling...

... corrosion artificial intelligence frequency defect voltage transmitter inductance scenario simulation inspection flowline corrosion prediction sensor coil subsystem well integrity coil machine learning diameter coupling dimension defect depth defect location algorithm pixel accuracy...

... optimization algorithm that is designed specially to promote the accuracy of a kernel-based proxy model for robust production optimization. In our study, we consider a least-squares support vector regression (LS-SVR) which is also briefly reviewed here. Stochastic Simplex Approximate Gradient (StoSAG)-Based...

... corrected surveys. However sometimes the 0.1 degrees SAG correction limit is too high for the required TVD accuracy on a given well. This is the case for a large number of horizontal ERD wells where as you are near or at horizontal for the majority of the wellbore the SAG correction is driving the TVD error...

... maintaining the accuracy of numerical simulations and completing simulations fast enough for sensitivity analyses. In this work, we describe how we addressed all these challenges in building our proprietary hydraulic fracturing and geomechanics simulator. We solve the single phase porous flow equations along...

... transforms established on the well data play an important role in predicting seismic rock properties. However, a data-driven approach, such as machine learning, can also estimate the targeted outputs from the well data. This study aims at comparing the accuracy of rock physics and machine learning analyses...

..., and continuous inclination DLS filter Improvement of accuracy and robustness for MSA, BHA sag, and Stockhausen effect corrections: the calculation of the geomagnetic reference along the trajectory, novel MSA with a priori and steering control information utilization, input smoothing for BHA sag correction...

... reserves evaluation reservoir simulation reservoir characterization information porosity pvt measurement log analysis workflow multiphysic inversion composition saturation estimation accuracy reservoir petrophysical characterization knowledge quantifying petroleum engineer co 2...

... accuracy Introduction Traditionally, a specific field's wax management and operating philosophy are developed by conducting a rigorous Flow Assurance (FA) study during the design phase. The study includes limited sample collections and delivery (based on the exploration and appraisal drilling...

... into two classes (high scaling or low scaling) with good accuracy. Though existing physical and chemical methods can be used to analyze scale deposition, the methods are often applied after considerable production decrease has already occurred. By using deep learning algorithms, our study came up...

... a new level of risk avoidance and safety factor. well planning pressure data pressure transducer drilling fluid management & disposal upstream oil & gas absolute pressure array sensor petroleum engineer drilling fluids and materials accuracy wdp network fluid density sensor...

..., decreasing the accuracy in gas wells. In order to predict the pressure gradient in horizontal gas wells, an experimental investigation of gas-water flow has been conducted. The experimental test matrix was designed to cover all the flow patterns. The experiment was conducted in a 5-m long pipe. The liquid...

... category presented non-integral well confusion matrix exhibition integrity well integrity well integrity anomaly ml model accuracy prediction feature description evaluation metric Introduction When oil and gas assets mature, well-integrity assurance becomes more necessary to ensure...

... was able to accurately and stably predict the production performance of multi-fractured horizontal CBM wells in a fast manner. Compared with Simple Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM), the proposed GRU-MLP had the highest accuracy and stability...

..., Random Forest (RF) shows the best accuracy with the given dataset, and Differential Evolution (DE) was used for optimization. Using recursive feature elimination (RFE), the final master dataset was reduced to 50 parameters to feed into the machine learning model. After hyperparameter tuning, reasonable...