... Abstract In this paper, we present an automated data-driven workflow using Machine Learning (ML) for gas lift optimization in unconventional fields. This workflow integrates a ML model that accurately forecasts the Gas Lift Performance Curve, and a Bayesian Optimization Framework to solve...

... with reduced completion intensity achieved $21.47 MM. The optimal parent-child well spacings are recommended for different parent well depletion durations. In addition to demonstrating our comprehensive workflow, the results of this paper provide valuable insights into the interactions between parent well...

... tracking for production logging in multiphase horizontal wells. The methodology, along with its advantages over existing methods, is thoroughly explained and explicitly provided in a step-by-step workflow. We also acknowledge and demonstrate the limitations of the method, especially those associated...

... sensing over the past decade, quantitative production profiling using data acquired from distributed fiber optics (DFO) has gained momentum. In this work, an integrated workflow to analyze the distributed temperature and acoustic signals during production is presented, along with two case studies...

... unconventional resource technology conference fracture conductivity productivity pressure transient analysis depletion mechanism phase 2 workflow URTeC: 4033310 A Physics-Based Approach to Characterize Productivity Loss in the Haynesville Shale Chad Jongeling1, Jerrod Ryan1, Christopher Ponners*2...

... Abstract The scope of this paper is to introduce a non-invasive simplified workflow that estimates perforation efficiency utilizing raw stimulation data. The paper illustrates how results from this simplified workflow were accurately and successfully benchmarked against industry-known...

... are often simplistic, while numerical models are computationally inefficient and require inputs for rock and fluid characterization that are not commonly available at scale. This paper aims to introduce a novel workflow that addresses these limitations, offering a refined approach to model hydraulic...

... duration and increased the reliability of the measurement. The introduced workflow enables (a) relative permeability and absolute permeability measurements performed in significantly shorter times compared to conventional techniques, (b) fluid-flow measurements in tight rock samples without the need...

.... Numerical RTA is applied to approximately 100 wells to match actual production data. The primary objective is to minimize errors in predicted rates of oil, gas and water vs. actual production by adjusting reservoir parameters. The ultimate goal is an optimized, semi-automated RTA workflow requiring minimal...

... seismic data and integrating with other reservoir properties is crucial for any quantitative reservoir characterization workflow which further aids in defining landing zones for optimal fracture stimulation. In this case study, we describe a workflow that integrates petrophysical data with a machine...

... especially challenging for operators to scale to many wells and in a fast cadence to accommodate the rapid speed in shale and tight asset development. In this paper, we present a workflow that combines probabilistic modeling and deep learning models trained on an ensemble of physics models to improve...

... lack logging data due to poor borehole conditions. This leads to the well performances being uncertain on account of the imprecise completion design without logging data. The scope of this paper is to show a comprehensive shale reservoir evaluation workflow based on novel cased-hole measurements...

... and significantly eliminates uncertainty associated with conventional approach. This novel workflow deliverables are critical in budget planning, asset tiering and completion design. In this paper, a new hybrid hydraulic fracture optimization and field development workflow will be demonstrated, which will utilize...

... allocation based on the DAS signal was done using standard workflow for different frequency bandwidths. The proppant allocation based on the estimates of eroded perforation diameter was done with the Monte Carlo simulations that account for uncertainty of the initial hole diameter. The developed Monte Carlo...

... the forecasting accuracy of RGNet models. The proposed workflow was applied to both a synthetic and a field example. In the synthetic benchmarking example, the sparsity-constrained history-matching successfully identified key inter-well connections while matching the data. In contrast to alternate methods...

... Abstract Often considered as the ground truth, wireline logs that are acquired along wells and are sensitive to formation properties serve as the foundation for reservoir characterization workflows. Effectively utilizing these well logs necessitate integrated geological, petrophysical...

... experimentation on the assumptions built into inventory planning. The result is a workflow for teams to explore an enormous number of realizations of various training data and feature sets in hours instead of months. With these tools, engineers can create accurate forecasts for future wells to better inform...

... of the treatment well may exceed slip tolerances in critical stress states. The shear slip of fractures in turn could lead to casing deformation events. In this study, a numerical simulation workflow was setup, based on the comprehensive modeling of a time lapse stress field, hydraulic fracturing simulation...

... simulations. The objective is to develop a fit-for-purpose integrated asset model by combining a reduced-physics reservoir model called reservoir graph network (RGNet) with a novel surface network optimization workflow for integrated optimization from the reservoir to the separator. Traditionally, reservoir...

... of the horizontal well landing window in the pilot well. The objective of this study is to characterize the vertical heterogeneity of the shale oil reservoir and optimize the landing window to maximize productivity. This paper proposed an integrated workflow by combining gamma-ray spectroscopy, 2D nuclear magnetic...