... individual flow regime flow regime log-log plot onepetro production data unconventional reservoir URTeC: 3722861 New Model Improves Secondary Phase Production Forecasts Himanshu Shekhar Jha*1, W. John Lee2, 1. The Berg-Hughes Center for Petroleum and Sedimentary Systems at Texas A&M University, 2...

... production and PVT data. We present complete details of its derivation along with its application to both synthetically generated and actual field data sets. We also compare results of our analysis to results obtained from interpreting multiphase production data using single-phase techniques. We show...

... significance of the initial production period by showing how model matches to initial production data are used to seed models for EUR estimation. Linear flow analysis is one of the most common methods for analyzing well performance in unconventional reservoirs. One of the key insights presented in this paper...

..., the calibration of the numerical RTA model for multi-phase wells requires production data after reaching dew or bubble point. To evaluate the performance of the wells in early production time and in absence of production data below saturation pressure, a diagnostic term is presented that combines the fractional...

... to significantly increase the number of analog wells used to construct the type well, increasing the statistical significance of the final product. We present our proposed workflow and illustrate its application to a 130-well data set from the DJ basin. In our workflow, the analyst first matches production data...

... in the presence of outliers. In essence, we apply a weighted least-squares (WLS) approach which, with simple mathematical manipulation is shown to be equivalent to LAV minimization. The proper identification of the BDF or PSSF exhibited by the production data is crucial for accurately estimating OGIP, EUR, and RF...

... a hindcast (backtesting) case study for a set of 197 Barnett shale gas wells. We compared the impact of not updating the estimates (base case) with updating estimates using new production data and externally adjusting them using calibration data. At 12 months of production data, the externally adjusted...

... forecasting deep learning dca model proceedings urtec 5418 production data time series 1 URTeC: 5418 Application of Bayesian Optimized Deep Bi-LSTM Neural Networks for Production Forecasting of Gas Wells in Unconventional Shale Gas Reservoirs Y. Kocoglu*, S. Gorell, and P. McElroy, Texas Tech...

... of fracture interference. In addition to possible problems posed for development, fracture communication that persists during production complicates rate-transient analysis (RTA) because models/methods for RTA have mostly been applied to single-well production data. Availability of RTA methods specifically...

... depth was observed in the West River, Geneseo, and upper Marcellus indicative of thermal maturity. The liquids distribution across the Marcellus fits within expectations from production data showing a trend of increasing content moving westward from northcentral WV towards the Ohio River; liquid...

... and microseismic events. The ML inverse model takes the form of an artificial neural net that can predict site parameters based on short term production data. We demonstrate the workflow using data from the DOE-sponsored Marcellus Shale Energy and Environment Laboratory (MSEEL-1). Introduction The Science-informed...

... multiple flow regimes further complicate forecasting. An important goal for field operators is to obtain a fast and reliable forecast with minimal historical production data. The abundance of wells drilled in fractured tight formations and continuous data acquisition effort motivate the use of data-driven...

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... a full-field development plan. Even though satisfactory history matching for completion and production data can be achieved for wells at one location, it is difficult to directly apply the results to other areas in the same region. This is especially true in complex thick pay zone reservoirs...

... executed fracturing designs. Users also leverage the economic model and input individual variable costs to get an overall completion cost per 12-month BOE or corresponding NPV. Validating the model with an operator’s completion and production data in the Permian helps to provide the feedback needed...

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