... in the laboratory, which in turn can be used to inform analysis of field data. fluid dynamics geologist permeability complex reservoir rock type reservoir surveillance production monitoring permeability heterogeneity heterogeneity clastic rock production forecasting core analysis plug...

... accurate and universally applicable production forecasting across different reservoir types. Our method involves segregating production data from different reservoir types into distinct domains. We employ a joint transformer model to project these domains into a unified representation space. Transformer's...

... assumptions. This study aims to develop reservoir models blending data-driven insights and physics-based constraints, utilizing routine data (rates and pressures) for pressure-aware production forecasting. We propose a novel approach for identifying rate-pressure relationships in unconventional reservoirs...

... geologist fluid dynamics clastic rock mudrock complex reservoir petroleum geology reservoir surveillance hydraulic fracturing modeling & simulation production control drillstem/well testing drillstem testing production forecasting basin mudstone permeability texas reservoir...

... the decreasing number of new wells unaffected by parent influences and the increasing total parent depletion amount each year. production forecasting configuration depletion parent child degradation midland basin wolfcamp staggered configuration artificial intelligence urtec delayed secondary...

... production forecasting proceedings seg unconventional resource technology conference rock type lee urtec doi probabilistic eur forecasting tlf mudrock artificial intelligence transition regime transition unconventional reservoir unconventional resource technology conference usa URTeC...

... Abstract This paper focuses on the application of a novel Generative AI (GPT) model for early-stage oil and gas production forecasting. The primary objective is to demonstrate the model's ability to provide accurate production estimates with minimal historical data, a challenge that has...

... the initial 3 years of production. We generated forecasts for all 2022+ wells using both TC and ML approaches for comparison. ML models maintain or improve predictive accuracy of production forecasts over the TC methodology. This study also analyzes the differences in standard TC Area definition versus a ML...

... in these methods. Our results highlight the importance of accounting for variable pressure effects in unconventional wells for accurate: production forecasting, NPV calculations, and optimization of fracture clusters and total number of fractures. The major contribution of this work is the implementation...

... values, and outliers. Additionally, each production forecasting method can represent a degree of ambiguity due to assumptions, limitations, and approximations. Reducing the uncertainty in production forecasts requires exploring different techniques with a range of outcomes. This paper will showcase...

... sources, such as well reports and communication documents. Machine learning models are employed for production forecasting based on historical data, geological characterization, and development strategies. This integrated workflow significantly improves the efficiency of numerous reservoirs engineering...

... economics arp bayesian 60 1 unconventional play petroleum play type production monitoring urtec bayesian maximum likelihood framework geologist production forecasting artificial intelligence machine learning regression engine geology modeling & simulation production control workflow...

... conventional reservoirs have well-established techniques for production forecasting, unconventional reservoirs present unique challenges due to their complex geological characteristics. Accurate prediction and forecasting of production from this unconventional reservoir are crucial for optimizing field...

... value to young well production. geologist forecast production forecasting artificial intelligence geology machine learning enhancing production forecasting accuracy basin unconventional resource technology conference complex reservoir history machine learning approach operator...

.... These key parameters were used to set up the RTA model for history matching and production forecast. By applying the in-house fracture conductivity calculation workflow and the measured pressure response, the calibrated fracture model results show that conductive fractures are aligned with the fracture...

... of machine learning and traditional models' capacities and limitations in forecasting EUR for unconventional reservoirs. geologist sedimentary rock clastic rock rock type production monitoring geology complex reservoir bakken reservoir surveillance deviation production forecasting eur...

... for structuring daily data for production forecasts, production actuals and type curves, and liberating that data in a consolidated dashboard. In organizations, the desire is to look at data that is aligned with the daily actuals coming from the field, however, monthly data is much more common as actuals...

... drilling production forecasting eur data mining machine learning unconventional resource technology conference completed ft geology shale gas geochemistry geochemical characterization paper fluid optimization technology conference decline curve analysis estimation seg unconventional...

... introduces statistical bias. This work proposes a parametric approach to the construction of TWPs. In doing so, the method obviates the need for subjective interpretation of averages of time-rate profiles and the biases inherent to that approach. First, it is required to create production forecasts...

... Abstract Production forecasting is crucial for field development. Machine Learning models have shown the potential to overcome limitations of conventional methods like Numerical simulations, reduced-order modeling, and decline curve analysis. This paper presents a newly developed machine...