Optimisasi Kondisi Operasi Pada Control Drilling Dengan Konsep Plant Wide Control

Drilling merupakan suatu kegiatan yang harus dilakukan untuk memproduksi sumber daya minyak dan gas dari dalam bumi. Pada proses drilling perlu memerhatikan berbagai hal demi menjaga kelancaran dan keamanan produksi. Optimisasi dan sistem kontrol dalam proses drilling ini menggunakan kesetimbangan massa untuk memaksimalkan rate of penetration (ROP) dan dipilih variabel-variabel yang memengaruhi untuk dioptimisasi. Pada kasus ini digunakan metode optimisasi algoritma stokastik seperti Duelist Algorithm (DA), Killer Whale Algorithm (KWA), dan Rain Water Algorithm (RWA). Optimisasi dilakukan pada 5 variabel, yaitu weight on bit (WOB), rotary speed, mud flow rate, pressure choke, dan mud density dengan hasil optimisasi DA berturut-turut sebesar 8,5447 ton, 105,3128 RPM, 49,4942 l/s, 0,4266 bar, dan 415,6926 km/m3 dengan nilai fungsi objektif 12,6741 m/jam. Pada optimisasi KWA dihasilkan nilai 5 variabel diatas berturut-turut sebesar 18,1253 ton, 147,4794 RPM, 50,0000 l/s, 0,0010 bar, dan 415,2012 km/m3 dengan nilai fungsi objektif 12,9367 m/jam. Pada optimisasi RWA didapatkan nilai fungsi objektif sebesar 6,1919e-6 m/jam. Berdasarkan nilai ROP yang telah dioptimisasi tersebut, nilai drilling cost minimal di dapat dengan menggunakan nilai ROP dari optimisasi KWA. Hasil rancangan PWC setelah penambahan kontroler feedforward mampu mengatasi gangguan akibat Pbit turun. =============================================================================================== Drilling is an activity that must be carried out to produce oil and gas resources from within the earth. The drilling. In the drilling process it is necessary to pay attention to various things in order to maintain smoothness and production. Optimization and control system in this drilling process uses mass equilibrium to maximize the rate of penetration (ROP) and variables that influence variables to be optimized. In this case, a stochastic algorithm optimization method such as duelist algorithm (DA), killer whale algorithm (KWA), and rain water algorithm (RWA) are used. Optimization was carried out on 5 variables, namely weight on bit (WOB), rotary speed, mud flow rate, pressure choke, and mud density with DA optimization results respectively 8,5447 tons, 105,3128 RPM, 49,4942 l / s, 0,4266 bar, and 415,6926 km/m3 with an objective function value of 12,6741 m/hour. In the KWA optimization, the values of the 5 variables above are 18,1253 tons, 147,4794 RPM, 50,0000 l/s, 0,0010 bar, and 415,2012 km/m3 respectively with an objective function value of 12,9367 m/hour. In the RWA optimization, the values of objective function is 6,1919e-6 m/hour. Based on the optimized ROP value, the minimum drilling cost value is obtained using the ROP value of DA optimization. The PWC design after the addition of feedforward controller are able to overcome the interface caused by downturn of Pbit