Total Sand Management Solution For Guaranteed Flow Assurance In Subsea Development

Abstract

Subsea development with long tieback to the beach is becoming the most economic cost effect method for deepwater development. In such deepwater environments multiphase fluid production accompanied by sand production is inevitable. Subsea developments/tiebacks are risk averse to sand/multiphase production for effective flow assurance. The major challenges for the asset teams in the development of such fields are in how to: Provide inputs into the subsea and topsides design in terms of possible quantity and particle size distribution of sand, and frequency of sand produced and transported through the wellbore into the subsea and topside facilitiesOptimise the well design that is fit-for-purposeMaximize the individual wells production and field development performanceEffectively manage the sand and multiphase fluid production as well as the facilities integrityDeploy appropriate sand management strategy that is fit for purpose including Critical evaluation of appropriate sand control method – Surface Control vs SubsurfaceMinimise the impact of sand production on the wells and subsea production facilitiesMinimize operational cost and non-productive time and guarantee flow assurance end-to end across the entire composite production system from reservoir through the wellbore to the topside and flow linesManage the waste disposal including the environmental impact assessment arising thereof. Achieving these objectives is the driver for our unique integrated engineering service and solutions strategy presented in this paper. The paper presents the step by step total sand management solution strategy that can enable managers of the subsea installations and complex fields to improve intervention and production efficiency through continuous process optimisation, reducing non-productive time and also guaranteeing flow assurance that can reduce lifting costs per barrel. The systematic approach is supported with the case study of a recent subsea development project study in the Gulf of Guinea field characterised by stacked volatile oil/condensate heterogeneous sand pools in 5000ft of water depth supported by detailed illustration of how the key geology and geophysics (G&G) and engineering data have been harvested for the integrated risk assessment. The reservoirs are being developed and produced via subsea flowlines, production manifolds, pipelines and risers to an FPSO. Pattern waterflood is also incorporated using seawater as injection source. The paper for the first time introduces the SMARTSAND Cum SMARTMULTIPHASE - two unique technology products that allow the planning team provide end to end solutions that clearly answered the following key questions: Will each of the wells produce sand?; when and how much sand will be produced?; How can the sand production be prevented or reduced without compromising fluid production?; How are the sand producers and the multiphase transportation managed as well as enhance production? The case study has detailed out the risk assessment steps that are an essential process to minimise the impact of sand production in deepwater/subsea environment. Results from the example case study in this work confirm that log based data and corresponding over and above core data provide the best approach to detailed reservoir characterization defined by reservoir quality index (RQI) and flow zone indicator(FZI) required for sand production rate prediction and transport analysis. The paper ends with how charging the reservoir with water injection can be an effective sand control method by extending the sand failure envelop and extensively prolong the onset of sand production.

Machine Learning-Based Models for Basic Sediment & Water and Sand-Cut Prediction in Matured Niger Delta Fields

“…oil and gas) [4]. Most times, the cost of producing, handling, and disposing of the produced BS&W and sand is a serious concern to the operating companies [5].…”

Optimal design for real-time quantitative monitoring of sand in gas flowline using computational intelligence assisted design framework

“…Operators in the industry have now structured an integrated sand management strategy which is a multi-discipline approach targeted to improve production efficiency through continuous sand production optimisation [13]- [16]. It involves exploring knowledge of the reservoir rock strength through characterisation of the geomechanical and petrophysical properties of the geological formation.…”

“…Following the rock failure, sand prediction models are then developed to provide a prediction for the onset of sand failure and quantitative prediction for a mass of sand that would be produced. These models are evolved from field observation, numerical, analytical and probabilistic assumptions and porosity petro-physical property of the rock is central to their development [16], [19]. The next element of the strategy is the selection of sand control completion designs as a technique for mitigating the production of sand.…”