Efficient Drilling Sequence Optimization Using Heuristic Priority Functions

Summary Drilling sequence optimization is a common challenge faced in the oil and gas industry, and yet it cannot be solved efficiently by existing optimization methods due to its unique features and constraints. For many fields, the drilling queue is currently designed manually based on engineering heuristics. In this paper, we combined the heuristic priority functions (HPFs) with traditional optimizers to boost the optimization efficiency at a lower computational cost to speed up the decision-making process. The HPFs are constructed to map the individual well properties such as well index and interwell distance to the well priority values. As the name indicates, wells with higher priority values will be drilled earlier in the queue. The HPFs are a comprehensive metric of interwell communication and displacement efficiency. For example, injectors with fast support to producers, or producers with a better chance to drain the unswept region, tend to have high scores. They contain components that weigh the different properties of a well. These components are then optimized during the optimization process to generate the beneficial drilling sequences. Embedded with reservoir engineering heuristics, the priority function (PF) helps the optimizer focus on exploring scenarios with promising outcomes. The proposed HPFs, combined with the genetic algorithm (GA), have been tested through drilling sequence optimization problems for the Brugge Field and Olympus Field. Optimizations that are directly performed on the drilling sequence are used as reference cases. Different continuous/categorical parameterization schemes and various forms of HPFs are also investigated. Our exploration reveals that the HPF including well type, constraints, well index, distance to existing wells, and adjacent oil in place (OIP) yields the best outcome. The proposed approach achieved a better optimization starting point (∼5 to 18% improvement due to more reasonable drilling sequence rather than random guess), a faster convergence rate (results stabilized at 12 vs. 30 iterations), and a lower computational cost [150 to 250 vs. 1,300 runs to achieve the same net present value (NPV)] over the reference methods. Similar performance improvement was also observed in another application to a North Sea–type reservoir. This demonstrated the general applicability of the proposed method. The use of HPFs improves the efficiency and reliability of drilling sequence optimization compared with the traditional methods that directly optimize the sequence. They can be easily embedded in either commercial or research simulators as an independent module. In addition, they are also an automatic process that fits well with iterative optimization algorithms.

Efficient Drill Sequence Optimization Using a Heuristic Priority Function

Drill sequence optimization is a common challenge faced in the oil and gas industry and yet it cannot be solved efficiently by existing optimization methods due to its unique features and constraints. For many fields, the drill queue is currently designed manually based on engineering heuristics. In this paper, a heuristic priority function is combined with traditional optimizers to boost the optimization efficiency at a lower computational cost to speed up the decision-making process. The heuristic priority function is constructed to map the individual well properties such as well index and inter-well distance to the well priority values. As the name indicates, wells with higher priority values will be drilled earlier in the queue. The heuristic priority function is a comprehensive metric of inter-well communication & displacement efficiency. For example, injectors with fast support to producers or producers with a better chance to drain the unswept region tend to have high scores. It contains components that weigh the different properties of a well. These components are then optimized during the optimization process to generate the beneficial drill sequences. Embedded with reservoir engineering heuristics, the priority function helps the optimizer focus on exploring scenarios with promising outcomes. The proposed heuristic priority function, combined with the Genetic Algorithm (GA), has been tested through drill sequence optimization problems for the Brugge field and Olympus field. Optimizations that are directly performed on the drill sequence are employed as reference cases. Different continu- ous/categorical parameterization schemes and various forms of heuristic priority functions are also investigated. Our exploration reveals that the heuristic priority function including well type, constraints, well index, distance to existing wells, and adjacent oil in place yields the best outcome. The proposed approach was able to achieve a better optimization starting point (∼5-18% improvement due to more reasonable drill sequence rather than random guess), a faster convergence rate (results stabilized at 12 vs. 30 iterations), and a lower computational cost (150-250 vs. 1,300 runs to achieve the same NPV) over the reference methods. Similar performance improvement was also observed in another application to a North Sea type reservoir. This demonstrated the general applicability of the proposed method. The employment of the heuristic priority function improves the efficiency and reliability of drill sequence optimization compared to the traditional methods that directly optimize the sequence. It can be easily embedded in either commercial or research simulators as an independent module. In addition, it is also an automatic process that fits well with iterative optimization algorithms.

Analysis of Performance of 433 MHz Telemetry Devices for Data Transmission in Unmanned Aerial Vehicle (UAV)

Abstract—Telemetry systems are a method of distance measurement that utilizes telecommunications facilities and computer systems for access control. The telemetry system on unmanned aerial vehicles is used to provide information such as position (coordinate point), altitude, direction, and some information that shows the condition of the aircraft in real time when the air vehicle operates. Telemetry systems in UAVs consist of hardware and software. Hardware in the form of IMU flight controllersand sensors. While the software used is a ground control station that is used to receive and process data. In software equipped with aircraft instrumentation systems. This paper examines the use of the 433 MHz radio system as a remote device link. In the test results, the telemetry device can send data from the aircraft to the ground control station, and vice versa well. Index Terms—Telemetry, 433 Mhz, Baudrate, LOS Data

Pendidikan Karakter Anak Usia Dini Sebagai Salah Satu Jawaban Dalam Mempersiapkan Generasi Muda Untuk Menggapai Bonus Demografi

Pendidikan karakter memegang peranan yang sangat penting bagi anak usia dini. Pendidikan karakter merupakan salah satu alternatif dalam menghadapi bonus demografi. Indonesia akan menghadapi bonus demografi di tahun 2045. Sehingga, untuk mempersiapkkan generasi pada tahun 2045, maka fokus pendidikan diarahkan pada Pendidikan Anak Usia Dini. PAUD merupakan The Starting Well Index, karena disinilah karakter anak dibentuk. Pembentukan karakter akan menjadi modal utama bagi kualitas sumber daya manusia pada bonus demografi. Pembentukan karakter sangat penting untuk ditanamkan sejak dini karena merupakan suatu habit (kebiasaan) yang harus terus menerus dipraktikkan serta memerlukan keterlibatan berbagai pihak (stakeholder).