The prediction of Estimated Ultimate Recovery (EUR) for a well or group of wells in a development project is critical to accurate reserves estimation. A number of techniques, many of which can be used deterministically or probabilistically, are employed in EUR prediction in mature and maturing unconventional gas and oil plays in North America. These include the use of geological and production data from analogous reservoirs, the use of volumetric methods and recovery factors, analytical models, numerical reservoir simulation and production decline curve analysis (DCA). Decline curve analysis is arguably the most commonly used method for forecasting reserves in unconventional reservoirs. This paper discusses its basic theory and application, together with the potential pitfalls of using simple empirical production forecasting methods in complex reservoirs. We analyse production data from several US unconventional oil and gas plays and carry out production forecasting using the traditional Arps' methods as a basis for comparison, and newer empirical solutions including the Power Law, Stretched Exponential Decline Model, Duong (and variations thereof). The range of production forecasts provided by these methods is examined, together with methodologies for developing statistically valid type wells in unconventional plays, and how best to determine valid input parameters for the various empirical solutions. The effect of the variable length of production history available in the various plays, and how it impacts the accuracy of the forecasts is also examined. The results of the analyses are compared with analytical models developed for each play to determine the suitability of each decline curve analysis method: in which plays and under which circumstances they can be applied, and suggest reasonable input parameters and data requirements for each method. Finally, the potential future use of the methods in emerging plays outside of North America is presented.
A major oilfield services provider was requested by a Russian national oil company to conduct a study of a tight, naturally fractured reservoir in Algeria. The goal was to integrate multiple data types (borehole images, wireline acoustic data, 360-degree core photographs) to generate a representative set of 3D static models describing the natural fracture network (with optimistic, basic and pessimistic cases) and then define fracture permeability. The reservoir is a tight Ordovician sandstone with intensive faulting, a complex facies pattern, and limited well data—all presenting significant challenges. Fracture interpretation was integrated from different sources, including borehole images, cross multipole acoustic data and 360-degree core photographs. The integration of fracture data from so many sources based on different physical principles enabled fracture modelling with much higher confidence, providing an input for further field development. The workflow for fracture density determination is divided into several stages: from borehole imaging (including definition of open, mixed and closed fracture types) and acoustic data fracture interpretation to 3D fracture density trend creation and calibration. Image interpretation results show good correlation to acoustic log interpretation results using Stoneley reflectivity and azimuthal anisotropy analysis. Combining acoustic, core and image logs data allowed organization of the wellbores into fracture classes. Fracture classes are zones of probability about the presence of natural fractures. These classes vary from very high probability (where all data types show presence of fractures) to zero probability (where all data types show no fractures or anisotropy). The 3D model of fracture density reflects a basic concept: the fracture density decreases away from fault cores, and within the fault cores the fracture density is at a maximum. This observation was supported by many field analogues (including some in Algeria). There were many intervals of intensive natural fracturing that were identified from images and core photographs. These zones might have contributed significantly to fracture permeability. This idea is supported by well test data analysis: the effective permeability from well tests significantly exceeds the matrix (core) permeability but is within the range of fracture permeability as defined by the continuous fracture network (CFN) modelling. Various data sets were integrated and calibrated to enable precise identification of fracture density distribution, fracture classes, and dip angle and aperture of natural fractures. These data sets provided input for fracture permeability calculations. Fracture density, fracture aperture and fracture dip angle 3D grids were prepared. Special equations, developed for tight, fractured Algerian sandstones, were applied to calculate fracture properties, e.g., fracture permeability. Through the close interaction of a multi-disciplinary team it was possible to successfully build a consistent 3D CFN model and to perform fracture uncertainty analysis to determine a variety of high-, mid- and low-fractured permeability cases. This model also supported further 1D and 3D geomechanical modelling studies. This CFN model provided a rapid workflow and robust model for further field development planning and new well placement.
A 3D geomechanical model is built for the XGS field, located in Sichuan province, onshore China. The field is in a faulted anticline consisting of three main reservoir layers. The main reservoirs are in the crest of an anticline structure bounded between major revers faults. The model captures all the structural complexities and the spatial variation of the geomechanical properties and parameters for the entire XGS field. The structural model is built using the interpreted horizons and faults form the surface seismic tied to the markers interpreted from the well data. The 3D grid is constructed for the entire field, extended to the ground level, to use as a framework for the 3D geomechanical model. The well-centric geomechanical models prepared for the 14 offset wells are used in combination to the surface seismic attributes to model the lithology and petrophysical properties for the entire grid. These data are then used to calculate and propagate the geomechanical properties and parameters. The 3D geomechanical model is designed to captures the spatial variation of pore pressure, in-situ stresses, the rock mechanical properties and parameters. The grid has higher resolution in the main target for the underground gas storage (UGS) operation and its immediate overburden caprock layer. This is done to capture and investigate the vertical and lateral variations in the vicinity of the UGS reservoir in more detail. The rock mechanical properties and parameters are dominantly governed by the lithology. This is while the pore pressure and the in-situ stresses are mainly governed by the geological structure. That has been said, a stress contrast is observed between the shale and carbonate layers. The model suggests that the field is in a strike-slip stress regime. The reservoir rock which consists of fractured dolomite is competent and stiff while the shale caprock is relatively weaker. A comprehensive approach is developed to capture the complexities of the structure and properties of the XGS field. A robust workflow is implemented to propagate the geomechanical properties and parameters to maintain their consistency for the entire studied area.
A 3D geomechanical model is built for the XGS field, located in Sichuan province, onshore China. The field is in a faulted anticline consisting of three main reservoir layers. The main reservoirs are in the crest of an anticline structure bounded between major revers faults. The model captures all the structural complexities and the spatial variation of the geomechanical properties and parameters for the entire XGS field. The structural model is built using the interpreted horizons and faults form the surface seismic tied to the markers interpreted from the well data. The 3D grid is constructed for the entire field, extended to the ground level, to use as a framework for the 3D geomechanical model. The well-centric geomechanical models prepared for the 14 offset wells are used in combination to the surface seismic attributes to model the lithology and petrophysical properties for the entire grid. These data are then used to calculate and propagate the geomechanical properties and parameters. The 3D geomechanical model is designed to captures the spatial variation of pore pressure, in-situ stresses, the rock mechanical properties and parameters. The grid has higher resolution in the main target for the underground gas storage (UGS) operation and its immediate overburden caprock layer. This is done to capture and investigate the vertical and lateral variations in the vicinity of the UGS reservoir in more detail. The rock mechanical properties and parameters are dominantly governed by the lithology. This is while the pore pressure and the in-situ stresses are mainly governed by the geological structure. That has been said, a stress contrast is observed between the shale and carbonate layers. The model suggests that the field is in a strike-slip stress regime. The reservoir rock which consists of fractured dolomite is competent and stiff while the shale caprock is relatively weaker. A comprehensive approach is developed to capture the complexities of the structure and properties of the XGS field. A robust workflow is implemented to propagate the geomechanical properties and parameters to maintain their consistency for the entire studied area.
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