Eni—the Italian oil and gas company—has implemented the
INTERSECT high resolution reservoir simulator across its most complex global
assets to drive computational efficiencies and improve model accuracy. In many
cases the simulator has been introduced to overcome project limitations imposed
by existing technologies, as the company seeks to understand increasingly
complex reservoirs and optimize decision making.
Impressive results have been obtained thanks to the combination of
high-resolution simulation technology delivered by the INTERSECT
simulator, and the strong technical competencies of the Eni team.
In the Baker field, USA, Eni had used an existing simulator for history
matching and depletion scenarios for the field's 117 wells. However, the
simulator did not have the power to model the effects of down-dip aquifer CO2
injection. Eni's existing simulator was unable to undertake the required
simulations, in a reasonable timeframe. The INTERSECT simulator allowed the
asset team to model the CO2 injection in a faster, more economic, timeframe and
obtain viable results.
Eni introduced the technology to correctly model similar effects in the
Cormorant field—a recently discovered West African, deepwater,
turbidite-channelized reservoir. The INTERSECT simulator allowed the team to
capture permeability contrasts associated with a large degree of heterogeneity,
in the context of a water-alternating gas (WAG) injection strategy
characterized by countercurrent flow—a result impossible to achieve with
the former simulator.
This was also the case in the Norma field, West Africa—an offshore
heterogeneous, tight oil reservoir featuring turbiditic currents. Eni's
development plan required local grid refinements (LGR) for all development
wells to optimally represent the hydraulic fracturing plans. Here, an
impressive reduction in simulation runtimes was achieved—from the 20
hours required by the former reservoir simulator to only 26 minutes.
The company used the INTERSECT simulator for a number of development
studies around the super-giant Tango field, a large heavy and high-viscosity
oil reservoir in South America. The reference development strategy was primary
depletion by means of a very large number of horizontal
wells—approximately 1,600. The INTERSECT simulator emphasized the impact
of improved grid resolution on simulation results. The team observed an
enhanced description of the phases interplay, highlighting the detailed
dynamical behaviour in interwell regions caused by the difference in mobility
between oil and water, which has an important impact in production performance.
The impact on the simulation results clearly indicated that detailed grids were
needed to correctly manage future production activities.
For the deepwater Mango field, offshore West Africa, Eni used the
INTERSECT simulator on a simulation model covering 15 years of water
flooding. The highly faulted, channelled, heterogeneous reservoir was
characterized by a complex structural framework in a flowerfault setting.
This model would not run in an economic timeframe using the
reference simulator, so the INTERSECT simulator was introduced to achieve
the finalization of the integrated reservoir study within project
deadlines. It also delivered performance improvements—the power of
the INTERSECT simulator made upscaling unnecessary, saving further
providing more accurate forecast results.
Long-term simulation excellence
Eni will continue using the INTERSECT simulator globally to overcome the
technical challenges of running efficient and detailed simulations for large
and complex fields, including the implementation of unstructured gridding and
proprietary workflows. A strong focus will be placed on the simulation of
enhanced oil recovery (EOR) techniques in order to increase field recovery
factors. Advanced simulation process and workflows will leverage the
outstanding computational performance of the Eni HPC2 High Performance
Computing Cluster, featuring 30,000 computational cores and 3,000 tesla
accelerators. Using HPC2, Eni is currently running INTERSECT models with
hundreds of millions of active cells. This new reservoir modeling strategy will
improve decision making through more detailed geological descriptions, and
accelerated subsurface development plan screening.