Abstract

Introduction ATHEER's gas processing plant at Habshan, Abu Dhabi is one of the world'slargest gas processing facilities. It consists of two identical trains each of270 million standard cubic feet per day (mmscfd) for processing Thammama - "C"gas 30/40 and 31/41 respectively), two trains of 350 mmscfd each for mixture ofThammama - "B" and "C" gas (Unit 32/42 and 33/43 respectively) and one train of610 mmscfd for Thammama - "F" gas (Unit - 34/44). Thammama - "B" gas isassociated gas, whereas Thammama - "C" and "F" are nonassociated gas. Eachprocessing train consists of gas sweetening unit using MDEA solvent, Dehydration unit using molecular sieve and NGL Recovery unit havingturbo-expander- recompressor, demethanizer and debutanizer. Besides, each trainof Thammama - "C" and "F" has standalone condensate stabilizer unit (Unit - 20,21 and 24), whereas two trains of Thammama ’ "B/C" have common stabilizer unit(Unit - 22). The feed gas to the plant comes from three different onshore gas sourceswith different gas compositions. In let gas conditions are widely varying andstrong interactions between different units make control of the plant operatingconditions difficult. ATHEER decided that Advanced Process Control (APC) solutions at its Habshangas processing facilities would benefit its operation and allow greater naturalgas liquids (NGL) recoveries and reduced utility consumption. The objectives ofthe APC project were:Increased NGL and condensate recovery while meeting as demand for consumersand reinjection requirementsImproved quality control of NGL and condensate productsSmoother plant operation After considering various options, GE Continental Controls (GE CCI)'s MVC®was selected to provide the APC solutions at GP&PD. MVC® is GE CII'spatented model predictive multivariable controller/optimizer with nonlinearcapability. It uses predictive control models derived from plant dynamics andrigorous simulation results. Nonlinear mathematical solutions are used tocalculate the optimal controlled variables and issue the correspondingmanipulated variable set points on each execution cycle. Automatic bias servesto maintain the predictive integrity of control models in the face varyingplant conditions. In this project, eleven (11) multivariable controller modules, one (1)predictive nonlinear level control module and fifteen (15) inferential modelsto estimate condensate Reid Vapor Pressure (RVP), NGL C2 andC5+ compositions were implemented. Original Plant Conditions The feed gas to the plant is supplied from multiple sources and is subjectto widely varying feed conditions. Strong interactions exist between differentprocess units, making control of plant conditions difficult. Lack if analyzersmakes the closed-loop control of product quality impossible with traditionalcontrol strategies. Feed Complexity and Plant Operation Variation Each feed source is supplied from multiple gas wells and is subject todisturbances in pressure, flow and composition causing widely varying feedconditions. Thammama-"B" associated gas is compressed in an external facilityand mixed with Thammama-"C" non-associated as coming from the separators ofUnit 20/21/22 before feeding into Thammama- "B/C" processing trains. Thammama-"B" and "F" gases are typically heavy and contain higher percentage ofC3+ components as compared to Thammama-"C" gas. As such, anyinstability in the external compression facility causes severe disturbances inthe operation of the downstream processing units. Thus, both feed gascomposition and flow rate to all the units were varying separators, etc. werecontrolled tightly while their outlet flows varied. This resulted in continuousvariation in stabilizer operating conditions. Lack of Analyzers There are no on-line analyzers of RVP analysis of the condensate productfrom the condensate stabilizer and debutanizer bottoms. The NGL product fromunit 45 is not analyzed for C5+. The lack of analyzers makes itdifficult for closed loop control of these compositions that are important tomaintain the condensate and NGL product specifications.

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