Designing and optimizing deviated wellbore trajectories using novel particle swarm algorithms

Finding the shortest path in direction effective is essential. To solve this shortest path problem, we usually using Dijkstra or A* algorithm. These two algorithms are often used in routing or road networks. This paper's objective is to compare those two algorithms in solving this shortest path problem. In this research, Dijkstra and A* almost have the same performance when using it to solve town or regional scale maps, but A* is better when using it to solve a large scale map.

https://iopscience.iop.org/article/10.1088/1742-6596/1566/1/012061/pdf

Analysis of Dijkstra’s Algorithm and A* Algorithm in Shortest Path Problem

Due to a variety of possible good types and so many complex drilling variables and constraints, optimization of the trajectory of a complex wellbore is very challenging. There are several types of well such as directional wells, horizontal wells, redrilling wells, complex structure wells, cluster wells, and extended reach wells etcetera. Over the past few years, the number of unconventional well including deviated well, highly deviated well is steadily increasing. Directional drilling has some advantages over vertical drilling though it is more expensive. In drilling engineering optimization of wellbore plays an important role, which can be optimized based on the minimization of the length of wellbore, minimization of mud pressure, critical pressure etcetera. Till today so many approaches or methods used to optimize this wellbore trajectory. From those methods here in this study we focused on metaheuristic approaches that used to optimize wellbore trajectory. This reduction of the wellbore length helps to establish cost-effective approaches that can be utilized to resolve a group of complex trajectory optimization challenges. For efficient performance (i.e.; quickly locating global optima while taking the smallest amount of computational time) we have to identify flexible control parameters. Later this parameter can be effectively fixed to tune different algorithms. This research will develop a review of the various algorithm used to optimize deviated wellbore trajectories. In the environment of challenging commodity prices, engineers and commercial firms bound to utilize technology to find out a low-cost solution. Technology is also helpful for the automatic solution of a complex problem, which also allows for the better utilization of resources. This review paper helps to find out optimal wellbore trajectory optimization algorithms that can close the technology gap by giving a useful method. This method can generate a solution automatically. Before establishing a different algorithm, those previous authors considered a number of factors and limitations. Safety is one of them. Before drilling depleted zones should be well studied, otherwise, it may be the reason for so many problems. The heuristic approach builds up solutions through the trial and error method. Those methods take a decent amount of time for solving a complex problem. For a single known problem, different metaheuristic approaches take a different amount of time to find the optimal solution. Among different metaheuristic algorithm which was used to find minimum true measured depth (TMD), we try to make a review where we focused on their computational time, minimization of length, method, etcetera.

A Review of Metaheuristic Algorithms for Optimizing 3D Well-Path Designs

In the mobile ad-hoc network (MANET) frameworks towards the route revealing techniques; there exists route disappointment in entire route identification methods delivery regarding information loss and Communication overheads. Thus, the routing improvement should be made as per the mobility character that belongs to the network. In this work, a particle swarm optimization (PSO)-based approach utilizing expected transmission count (ETX) metrics for MANET has been planned. The prevailing approach demonstrates that the supply ought to choose the best path when the repetition of computation that relates to the load within the network. So it whole affects the performance of the system as a result of an unusual quantity of transmissions. To boost the trail choice, PSO approach is introduced by combining the ETX metrics. PSO based approach uses ETX metric values to scale back the communications that area unit utilized to deliver the packets with efficiency to the chosen destinations. A complete range of transmissions area unit foreseen by ETX solely when the choice of the best path by PSO. From the simulation result, it’s verified that PSO-ETX approach shows higher performance compared to the MAREERP regarding the delivery ratio, time delay, and throughput.

Optimal route selection in MANET based on particle swarm optimization utilizing expected transmission count

Fault-tolerance is one of the major issues in ad hoc networks. Failure probability is greater because of limited energy level of mobile nodes and dynamic topology constraints. Whenever a node is dubious to be attacked, checkpointing of data is done on some reliable and trustworthy node. So, evaluation of trust factor of a node is an important aspect that largely influences the recovery process. This paper compares the proposed dynamic node recovery technique with an existing base approach. The proposed research work ensures successful retrieval of checkpoints in case of node failures, thereby reducing the recovery time considerably. As an outcome, this improves throughput of the system. Trust factor of a cluster, in the proposed work, has significant impact on the count variable maintained by each node. The two are inversely proportional to each other. Count variable is kept track of so as to carry out the checkpointing task. When the count exceeds pre-specified threshold value, checkpointing is done. In addition, genetic algorithms are used to find an optimal path between the recovery node and checkpointing node as reliable transmission of data is of important concern. Performance analysis clearly depicts how proposed approach outperforms the existing base approach.

Dynamic node recovery for improved throughput in MANET

Routing is a process of forwarding the data from a known source to the destination. In this process, the data may travel through several intermediate paths, and there exist a need to select the best possible optimal nodes to forward the data. This optimal selection of nodes will enable to achieve a high performance in the network. Large amount of worked has been carried out to find the optimal path in the network routing to improve its efficiency and to remove congestion problems. A good routing algorithm should be able to find an optimal path and it must be simple. It also must have low overhead, and be robust and stable, converging rapidly, and must remain flexible. There exists a lot of routing algorithm which have been developed for specific kind of network as well as for general routing purpose. In this paper, I studied some of the best optimal path techniques.

https://www.longdom.org/open-access/study-of-optimal-path-finding-techniques-0976-4860-4-124-130.pdf

Parveen Sharma

Papers

Study of Optimal Path Finding Techniques

Enhanced security using proxy signcryption technique for wireless mesh networks