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.
The purpose of the study was to quantify and evaluate the impact of geological heterogeneities on connectivity in channelized turbidite reservoirs. The main technical objectives of the project were: the identification of the architectural elements of the deep-water system under analysis, the development of different geological models, the quantification of reservoir heterogeneity and the evaluation of reservoir connectivity and the outline of an early appraisal strategy.
An integrated approach was applied, using different frameworks, to two eni's deep-water assets: the first, an exploration asset in the Mediterranean, and the second, a West African field in development. This methodology was based on an earth models construction phase (reservoir characterization and reservoir modeling) and on a dynamic simulations phase (streamline simulations and well test simulations).
Reservoir characterization was performed by interpreting 3D seismic data using a high precision 3D seismic interpretation software. Key surfaces were interpreted in the reservoir interval. Furthermore, deep-water elements and architectures, mainly stacked channels and distal lobes, were duly identified through the interpretation of seismic sections and amplitude maps.
Reservoir modeling consisted of Object-Based and Multi-Point Facies Simulation (MPFS) approaches. A sensitivity analysis was carried out to define critical parameters and their ranges in order to fully capture geological uncertainties and realize different static models. The selected parameters were: seismic conditioning in the MPFS (amalgamation), facies volume fraction, channels shape and shale drapes content.
To quantify heterogeneity and analyze connectivity, streamline simulations were carried out using a Streamline Simulator. For each geological model, a Dynamic Lorenz plot (storage capacity vs. flow capacity) and its related coefficient (standard measure of heterogeneity) were determined using an in house code. It resulted that all the selected parameters, except channels shape, impacted considerably on connectivity.
To outline an early appraisal strategy, well test simulations were performed using an hypothetical exploration well and a standard Dynamic Simulator. Well test simulation was found to be an interesting qualitative tool to identify heterogeneities, especially shale drapes content, and condition further appraisal decisions.
Considering the promising results, this approach will be further developed to effectively reduce the range of uncertainties, mitigate the associated risks and guide appraisal strategies in future deep-water prospects.