... hammer is an oscillatory pressure signal generated as a result of an abrupt change in wellbore fluid velocity, for example at the end of a fracturing treatment when the pump rate is quickly dropped to zero. Authors developed an algorithm in python to automatically identify surface pressure and fluid...

.... The development of steps to harvest outliers and fuse adjacent fractures were conceived to utilize as much data as possible and to recognize the relative errors in event locations. With regards to the Datathon goal of achieving an automated processing sequence, the algorithm runs without manual intervention once...

... the normal emission rate to tell when the workers were being exposed to unsafe levels of greenhouse gas (GHG) and other noxious elements. Algorithms were also developed to check for fuel adulteration and equipment health, identifying low-performing assets that might have undergone wear and tear. The sensing...

... Abstract We developed a propagation algorithm that enables accurate calculation of hydraulic fracture geometry, even in the presence of thin layers and with a relatively coarse crack mesh. Conventionally, hydraulic fracture simulators either add one element at a time (less accurate) or require...

... with the high-resolution pressure gauge data for each sealed wellbore. The team developed machine learning algorithms to identify the key events required by a sealed wellbore pressure analysis: the start, end, and magnitude of each pressure response detected in the sealed wellbore while actively fracturing...

.... Forward geomechanical modeling has been the focus of current research efforts to better understand the LF-DAS signals. Moreover, LF-DAS provides the opportunity to quantify fracture geometry. Recently, Liu et al. ( 2020a; 2020b ) proposed an inversion algorithm to estimate hydraulic fracture width using...

... application. During this process, the team recognized that the problem stages had their own characteristic pressure signature - a sudden unexplained pressure increase in the absence of rate changes. A machine learning algorithm was then developed to automatically identify this type of signature. Additionally...

... well stimulation was developed in 2017. The method discussed here is a continuation and improvement of this method. It is based on an advanced signal processing algorithm used for detection and analysis of tube waves in a wellbore and on the data science approaches for further processing of tube wave...

... Acoustic Sensing (DAS) data. In the third section we have attempted to develop a process to quantify near-wellbore tortuosity, where machine learning (ML) algorithm(s) were utilized to estimate the friction pressure induced by near-wellbore tortuosity. The training, testing and validation needed...

... used to simulate the flow from the matrix into the fracture network is simple and well known, but it relies on the assumption of constant pressure in the fracture which can only be obtained with infinite fracture conductivity. An original feature of this model is an algorithm to extend the validity...

... spherical proppant rod-shaped proppant hydraulic fracturing segmentation spe 140448 fracturing materials fracturing fluid conductivity setup proppant pack fracture conductivity setup algorithm permeability conductivity coreholder tomography setup rod-shaped proppant pack fracture cleanup...

... solutions provided that the appropriate tip behavior is embedded in the algorithm. Through theoretical, experimental, and computational considerations, these results make it clear that advances in the accuracy and efficiency of fracture simulators critically depend on a sophisticated treatment of the near...