Throughout the past 10 years, the oil & gas industry has drilled offshore fields that lie in increasingly deeper water. As we go deeper, there is an inherent need for considerable investments to develop these fields and execute complex Field Development Plans (FDP) [1]. These developments of fields with differing reservoir fluids and pressures are brought together with complicated gathering networks. Most important to note is that the various system components have an impact on one another; for example, the backpressure applied to one reservoir drives its production rate and its ultimate recovery. This depends on the pressure drop for a given set of flowlines and processing facility location, and vice versa. Commonly however, the location and sizing of these facilities is optimised for field production profiles developed using different assumptions to the final implementation. Although Capex and Opex are provided for the topsides, an integrated economics optimisation is usually required to enable investment decisions and maximise value. Creating and configuring a multi-faceted system of this nature can be complex and indeed its optimisation can constitute a Wicked Problem [2].
A holistic skillset, including the reservoir and subsurface, facilities, marine, subsea and drilling, is required to understand the dynamics of the system. Incorporation of economic modelling, and commercial and advisory strategies, can expand the conversation to risk and investment decision optimisation. The end-goal is to deliver an FDP that gives due attention to the technical constraints and, also harnesses strategic commercial decisions.. Traditional design and pre-FEED Field Development Plans (FDP) operate in a more baton-passing fashion that simplifies or ignores these crucial interdependencies altogether, which ultimately destroys project value.
Joining the dots
The common thread that runs through these integrated reservoir and facility simulation models are the production fluids. Whether producing a dry gas, light or heavy oil, condensate, or a hybrid of these, developing a consistent fluid Pressure Volume Temperature (PVT) model to be used consistently for the entire system is vital. Depending on the fluids present and the phase envelope across the reservoir/production system conditions, this may require a more complex compositional fluid model rather than a simpler blackoil fluid PVT model. Consistency checks across different modelling platforms for fluid correlations and fluid flash calculations must be performed by relevant experts in those tools and domains as part of the integrated model.
Aside from the complexity in configuring these integrated models, the runtimes of the models can also pose a challenge. Even with high-specification CPU/GPU clusters or cloud-based hardware, the simulation times can become impractical to run more than a few permutations of these integrated reservoir and surface facilities models. However, if the whole model of the subsurface/surface system is configured by the respective domain experts in a collaborative manner, its design can be streamlined without compromising its accuracy. For example, part of the reservoir system can be simplified with a sector or coarse model; or the number of common timesteps between the surface and subsurface system can be reduced. Alternatively, steady-state rather than transient analyses may be applicable for all or part of the flowlines; or the use of flow performance correlations can be considered for parts of the surface network and facilities. It may be possible to include more components of the reservoir system in the surface model or vice versa. All of these possibilities can be considered to target a faster run-time of the full system model; they all require consideration by an integrated multidisciplinary team.
In the past, a key problem with these combined models is that they have often been created in isolation by a single skillset, e.g. a reservoir or production engineer. However, the task of linking a static geological model, reservoir dynamic model, wells, completions, flowlines, facilities and economics is multidisciplinary.
Numbers in action
An integrated reservoir surface facility model was created for a licence block operated by a mid-sized operator in West Africa. The fields were spread over an area of approximately 20km by 60km and contained a mix of oil, gas and condensate fluids; however, the order of development, ramp-up and the apportioning of production capacity to each of the fields, reservoirs and wells was not immediately clear. One of the development scenarios being considered contained a common FPSO for the block and utilised excess gas from one of the fields to enhance recovery in another field through gas lift and gas injection. The goal was to maximise the Net Present Value (NPV) of the project, which required a holistic model of the system, incorporating production of sufficient gas; processing and sizing gas lift facilities; maintaining reservoir energy of the respective fields; water handling/injection requirements; etc. The complex mix of fluids in place and the initial pressure of the reservoir close to the bubble point called for a compositional PVT fluid model. The potential for gas liberation within the system meant the pressure throughout could significantly affect the facilities and flow assurance requirements, as well as the ultimate field recovery. In this case, if the facilities and network components had been designed and optimised in isolation of the reservoir model, there could have been significant variation in the field production, which in turn would have made the final FDP a non-optimum and possibly obsolete solution.
Another example of a client utilising an integrated reservoir-gathering network model involved consideration of a tie-back of an offshore satellite field to an existing facility. The capacity of the facility to accept further production and associated upstream pressure at the completion could have impacted the field production rates and the ability of the field to maintain a production plateau. A key unknown was the size of flowlines, as well as the compression capacity and amount of fluid handling. The scope of this study looked at the economic advantage of a larger gas compressor over a smaller one with associated impacts on production plateau. Also explored were various options in pipeline sizes and costs, resulting backpressure effects and their impact on the overall profitability of the system with modified field production rates.
Harness integration and collaboration
Applications of integrated models and simulations have the potential to improve the quality of both reservoir and surface modelling, which can be crucial in optimising complex gathering networks for FDPs covering fields with differing fluids and pressures. The configuration of such integrated subsurface-surface facilities models, as well as economic modelling and optimisation of these models, requires a multidisciplinary skillset and a holistic perspective starting with the end in mind.
io has an in-house multidisciplinary team including reservoir & subsurface, drilling, subsea, marine, facilities, economic modelling and commercial and advisory. Our clients benefit from our integration across technical and commercial capabilities, which uses best practices, techniques, tools and processes. io works closely and collaborates with clients in domains where they might not have ingrained expertise or experience. This is particularly useful for these kinds of integrated studies as multiple specialist disciplines are required. When framing the goals of an FDP, our holistic approach enables recognition of technical, commercial and strategic objectives and limitations of the asset or project overall.
To find out how io can help you understand your reservoir and production facility system with a fully integrated mindset, contact us at hello@ioconsulting.com.
[1] Ghouri, S.A., Banoori, S., Topini, C. and Rametta, D., 2015, June. Practical Alternate Integrated Asset Models. In Offshore Mediterranean Conference and Exhibition. Offshore Mediterranean Conference.