A robust and detailed reservoir model is an essential requirement when a fast track approach drives the development of a green field. Such a tool can only be developed through the orchestration of Geological and Geophysical (G&G) and Reservoir Engineering disciplines. This integration effort is, first of all, aimed at identifying the key characteristics of the reservoir most impacting its dynamic behavior at different scale and, eventually, at capturing them with the proper modelling approach.
This paper decribes such approach to the case of a complex deep-water reservoir belonging to slope-toe of slope environment. A 3D integrated static model was built by incorporating core and log data, their petrophysical interpretation, a description of the depositional and architectural elements, a quantitative seismic reservoir characterization and the few dynamic information available at this early development stage.
The implemented geomodeling workflow focused on heterogenetiy that could affect reservoir performance such as structural-stratigraphic discontinuities that could act as hydraulic barriers. Facies in the interwell space were distributed by applying seismic-derived 3D trends. Facies distribution eventually provided the framework within which petrophysical properties modelling was performed. During the implementation of this integrated G&G and Reservoir workflow, continuous crosschecks of consistency and robustness of the model led to elaborate the final product.
The resulting reservoir model captured critical uncertainties (e.g. degree of reservoir heterogeneity including stratigraphic discontinuities) leading to an optimized development scheme, that allowed to minimize risks, despite the few data available.
Cerri, Riccardo (eni SpA Upstream and Technical Services) | Di Martino, Stefania (eni SpA Upstream and Technical Services) | Balossino, Piero (eni SpA Upstream and Technical Services) | Gioacchini, Luca (eni SpA Upstream and Technical Services) | Colombo, Ivan (eni SpA Upstream and Technical Services) | Spelta, Elisa (eni SpA Upstream and Technical Services) | Bartosek, Martin (eni SpA Upstream and Technical Services) | Bjorum, Matt (Als Corpro)
Shale gas reservoir quality evaluation is a technical challenge as conventional log interpretation methods and even core measurements may be inadequate or inaccurate. Only through a robust integration of core and logs data, a reliable estimation of the gas in place can be obtained and the interval with the best petrophysical and geomechanical characteristics (sweet spot) identified.
Total GIIP estimation is derived from core and log analyses and can be complemented by measuring desorbed gas from selected core samples. Total gas content is the combination of measured and estimated gas components: lost gas, measured gas and residual gas. Lost gas is the most critical component being usually extrapolated from desorbed data to time zero using USBM linear and/or polynomial curve fitting.
Total gas can now be directly measured by using a new controlled pressure coring technology able to capture a full sized core and retain all the hydrocarbons contained in the rock eliminating gasses and/or liquids lost during conventional coring techniques.
The characterization of the lower Barnett Shale described in this paper was achieved by coring the whole sequence: several samples from conventional cores were taken for desorption analysis and three pressure cores were placed to target the main facies identified from the integrated reservoir model.
Core gas data from both desorption and pressure coring were integrated for a more reliable total gas estimation; consistent relationships among handling time, free/adsorbed gas content and method used for deriving lost gas were also observed. Obtained total gas values were in good agreement with calculated gas volumes from logs.
In addition, the combined application of pressure coring and desorption analysis in the Barnett Shale has allowed to improve well site procedures for optimal core data acquisition and to define the best approach for a robust shale gas evaluation.
Proper reservoir characterization and sweet spots identification for unconventional reservoirs need to be performed considering both geomechanical and petrophysical properties.
This paper describes the integrated application of tools and technologies developed within eni internal research project on US Barnett shale gas.
eni shale gas reservoir modeling has been performed by using a geologic workflow to link the petrophysical characterization and the seismic data at wellbore scale and consistently distribute these properties at field scale by means of a seismic “trend”. This is the key to obtain a predictive geological model.
In addiction, an engineering workflow that merges hydraulic fracture treatment, microseismic survey and advanced production analysis (APA) was set up.
Thus the input parameters for dynamic simulation, focusing on the stimulated reservoir volume (SRV) estimation, may be obtained.
A sector model was extracted from the full field geological model for dynamical simulation purposes.
A “single porosity-like” approach was adopted to couple the advantage of dual permeability and single porosity models.
As a first step, the History Match (HM) of gas production data and flowback water rates, was performed both at single well and pad scale. This allowed the tuning of SRV extension and permeability of the induced fractures. In addition, a comparison of gas reserves obtained by decline curve analysis and simulation model was performed.
Moreover, by using the calibrated sector model, a series of sensitivities was carried out focusing on well landing and spacing in order to achieve an optimal pad design.
The strength of this study lies on the integrated model approach. It is an efficient tool to drive and optimize the field development plan, allowing the definition of optimal wells spacing and lateral length, positively affecting economics. Finally, it is a robust approach to reduce uncertainties in gas reserves assessment.
The largest part of global discovered hydrocarbon resources is stored in so called Unconventional reservoirs, that need advanced technologies, such as horizontal wells, multistage completion and hydraulic fracturing, to be successfully exploited at economic rate.
This work focuses on unconventional gas shale reservoirs that are present worlwide. Nowadays, many efforts are ongoing in order to better understand their nature and the complex physical phenomena involved in the production, thus improving field development strategies.
A fully integrated static and dynamic workflow for shale gas modeling was internally developed by eni. The aim was to deliver a more structured and business oriented technology to build a reliable and predictive model able to support and optimize management decisions in such complex systems (e.g. sweet spot definition, well positioning, completion,
Both static and dynamic conventional workflows had to be tailored on unconventional context. In static simulation, differences are related to facies characterization and hydrocarbon volume in place calculation; dynamic simulation had to be adapted and improved to reproduce the hydraulic fracture explicitly, to model the frac fluid flowback, to consider gas desorption and multiscale fluid flow.
During the last years, oil Majors have been struggling trying to make the unconventional business profitable. Indeed, the strategy to build an unconventional portfolio by means of merges and acquisitions is not giving enough return of investment. This is mainly due to internal processes, which contrary to Independents, are customized on a very different business model.
In addition, it is becoming clear that unconventional resources cannot be considered and developed as “statistical” ones. Nowadays, several publications are stating that only a small percentage of fractured wells is generating positive return. Even though unconventional reservoirs are considered more complex than conventional ones, less efforts are unjustifiably applied for their understanding. Hence, there is a need to switch from a “drill baby drill” to a “more from less” approach. This implies to address several issues such as: a better understanding of shale gas production mechanism at nano-scale, sweet spots identification, proper fracture placement and treatment, realistic full field simulation of fractured wells.
This paper describes how seismic-reservoir integration, advanced production analysis, accurate nano-scale and 3D full field simulations may address the above issues and help oil Companies to be more efficient in developing their unconventional portfolio. This new approach, based on placing and fraccing wells only where needed, is already providing interesting results in mature plays like the Barnett Shale and will be even more crucial for sustainable unconventional developments outside US.
While during 2008-2011 Independents were building and developing their US unconventional portfolio, Majors were trying to enter the same business by multi-billion merges and acquisitions. Obviously, Majors were not fast enough and able to repay the premium for entering the game, as a consequence of the combination of a low margin profit type of business and hydrocarbon price evolution. Some authors pointed out two interesting considerations on this initial disappointing participation (Sprunt E., 2014). First, Majors are essentially process driven organizations in which processes are tailored on totally complete different projects (large scale projects, high risk high remunerative), thus they are not structured for a fast “micro-decision” kind of approach. Second, they quickly aligned to the general concept of thinking about unconventional plays like statistical ones. It is unjustifiable that, even if unconventional reservoirs are considered more complex than conventional ones, the use of advanced workflows was initially not considered. The main effort was essentially made for unit cost reduction, while now technology innovation has become a principal focus.
Key plays have experienced an impressive production growth (eia, 2014) (Fig. 1 and Fig. 2). If, on one side, the system is improving its efficiency, on the other one the incremental production is also associated to a huge increase in the average number of frac stages per well.