... to generate the synthetic seismograms. These synthetic seismograms are then averaged to obtain a single noiseless synthetic seismic data, prior to addition of estimated field noise. 40,000 realizations of 1D synthetic datasets are generated for the training dataset. An equal distribution of 4000 realizations...

... in the future after history matching. Through sensitivity analysis of the observation duration, we find that extending the observational data collection duration enhances history-matching results consistently. Besides, the DNN-HM workflow has a descent tolerance of noise in the observational data...

.... The new enhancement to the monitoring workflow enables fast processing of the microseismic data, by filtering upwards of 94% of noise files from the daily dataset before the files are reviewed and analyzed. The software consists of a deep learning-based application trained to recognize noise files...

... Abstract Seismic data is vital in the petroleum industry, revealing subsurface structures and reservoir potential. However, this data frequently suffers from degradation due to noise and missing traces, necessitating denoising and interpolation tasks. Recently, diffusion models have gained...

... and provides field applications. Conventional bleed-off/build-up cycles are used to check the sustainability of the pressure build-up in the annuli. Once that pressure is confirmed to be sustainable, a slim downhole tool conveying high-definition spectral noise and temperature sensors is run to determine...

.... Under actual operating conditions, the identification of heterogeneity is more complex than under ideal conditions because of the presence of noise. This study investigates how the degree of heterogeneity and the level of noise in the data strike a balance in identifying heterogeneity. In this study...

... is well recognized in the industry, there is a debate about its general applicability because it is limited to a constant-rate flow period and is insensitive to flowrate and flow sequence, to gauge resolution or measurement noise level. This contrasts with operational experience, where a higher flowrate...

... to support the energy transition. From this, we learned that measurement accuracy requirements higher than 1 % because we are often imaging small anomalies. While there are always limits in acquisition set by industrial noise, we derived two ways of increasing the anomaly. One is by using, similar...

... Noise from sensor, electronics or well pressure can be estimated and quantified. Acknowledging the challenge of defining the SNR as an important standard to measure the quality of seismic data, Li et al. (2016) have defined the local SNR over a window to replace the instantaneous SNR for each...

... deep learning model conductivity interpretation fractured well noise machine learning upstream oil & gas accuracy fracture half-length algorithm parameter evaluation parameter inversion reservoir petroleum engineer interpretation model Well Testing Model The assumptions...

... was established that was undoubtedly a key success factor in the results obtained. The electromagnetic tool determined the depth of severe casing metal loss in 7-inch casing, also the acoustic tool detected the noise of fluid movement in the 7-inch annulus, and the pulsed-neutron tool showed the beginning...

... measurements, enable the optimization of the measurements in real-time to mitigate biased noise. By verifying the location of the dominant mode of the T 2 distribution, the NMR operator can determine whether more stacking of proton magnetization decays is needed to attain a high-quality estimation...

... experienced evaluator. It is fact to state that the current algorithms used in the industry often amplify noise and are inherently unstable in the presence of outliers. This work proposes to significantly improve data processing using modern algorithms for data filtering and statistical (Bayesian) methods...

... tester exhibition noise society of petroleum engineers injection test wellbore Introduction Background on DSTs and well testing Well testing is the only logging technology that provides conclusive evidence for the presence of petroleum deposits within a reservoir zone and the dynamic...

... Abstract Leaks in wellbore tubulars emit acoustic waves in the borehole, which can be captured by a hydrophone array. Processing the array data yields location and energy level of the wellbore leaks; however, the hydrophones may also capture other coherent noise propagating as guided waves...

... are carefully monitored, long-term pressure data is subject to abrupt changes in flow-rate, noise caused by hardware failures, missing data and physical changes in the reservoir. In this work, methodology to interpret long-term flow-rate and pressure data was developed using wavelet multiresolution analysis...

... measurements, production and geophysical well log data. The methodology involves: (1) building and calibrating a petro-elastic model; (2) forward modeling of each separate physical effect such as saturation, pressure, salinity and noise; (3) combining the effects according to simulated production scenarios...

... drilling fluids and materials nitrogen circulation visualization migration noise real time system production monitoring production logging annular pressure drilling injection line choke pressure acoustic data completion monitoring systems/intelligent wells enhanced recovery wellbore society...

... rate when back-tested against a historical data-set of known casing failures. False positives are adequately contained by preventing waveforms of electrical or mechanical noise from being processed. In a production environment, the event processing workflow is run on distributed servers and analyzes...

... to compute the optimal solution of T2 distribution with a unique optimal regularization factor for NMR logging data processing. This inversion method has no assumption about the white noise of a T2 echo train. A new supplementary nonlinear equality constraint was introduced to optimize the solution of T2...