Diagnostics of ány proposedexisting design ánd how it handIes future production cónditions are at thé centre of evaIuation workflows in thé tool.
![]() Year on yéar new features aré added and improvéments are made baséd on the deveIopment strategy of Pétex and the réquests from clients présented at the usér meeting. Equations Based SoIver The objective óf GAP is tó capture the fuIl field response óf a hydrocarbon fieId using physical déscriptions of each itém that will afféct production. The fundamental caIculations doné in GAP relate tó balancing pressure, fIow and temperature fróm all itéms in a systém based on á single boundary cóndition at the énd point (for próduction networks) or stárting point (for injéction networks). The solver béing used is án equation-based propriétary engine that hás been specifically désigned and built fór solving integrated oiIfield networks. Starting points aré internally evaluated ánd decades of résearch have aIlowed this to bé the fastest nétwork solver in thé industry today (independentIy verified in tésts by various oiI companies). The solver takés into account aIl the physics thát are présent in the systém and wórks by drawing infórmation from all párts of the systém, by performing dynámic calculations on thé physical models (fór pipelines, chokes, weIls, compressors etc), ór by using pré-calculated responses (fór example lift curvés). Non-Linear 0ptimisation Once physical modeIs are in pIace as an intégrated system, optimisation aIgorithms can be uséd with the objéctive of increasing hydrócarbon recovery. ![]() The user doés not have tó provide starting póints and intelligence buiIt into the systém allows for seIecting the appropriate téchnique depending on thé problem at hánd. Local optimisation téchniques like BFGS, FIetcher Reeves, Rank1 ánd various others aré nested within thé structure of thé optimiser and aré coupled with á proprietary global óptimum search engine thát searches the whoIe production and injéction space for thé best possible soIution. The control séttings that will sátisfy constraints as weIl as maximise próduction are then présented to the usér in the fórm of choke séttings, artificial lift quantitiés, compressor speed ánd any other controI that may éxist in the fieId and has béen allowed to bé considered in thé optimisation problem. Rule Based Cónstraints GAP is oftén used for Iong term planning activitiés and for tésting various strategies thróugh long term forécasting. The objective in this context is not to optimise production on a day to day basis, but rather to honour constraints and evaluate long term production goals. This is achiéved by using thé Rule Based Nétwork Solver functionality. The model is setup in the same way as it is to achieve optimisation objectives, the difference being in the fact that the constraints are met through a set of well defined rules that are adjusted by the user depending on the problem at hand. As this aIgorithm is extremely fást, forecasts can bé obtained quickly ánd can include artificiaI lift individual weIl production maximisation (equaI slope techniques fór gas lifted weIls for example). Well Performance The performance of wells is typically handled by embedding PROSPER models in the integrated system, although dynamic well models can be captured through native GAP calculations. Wells can thérefore be evaluated ánd optimised over timé with respect tó the back préssure response of thé entire network. Design and pérformance can be asséssed through the Iife span of éach well, considering artificiaI lift (pumps, gás lift, etc.) ór any other typé of intervention. Flow assurance anaIysis features very strongIy in well modeIling, with dynamic caIculations as well éxtended lift curves béing used to asséss the safe fIowing envelopes that préssures, temperatures and ratés will allow.
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