Natural gas suppliers and recipients are typically connected via a large-scale, high-pressure, integrated transmission pipeline network. These transmission systems are the most cost-effective way to transmit fluid products over long distances [1], and are typically powered by multiple sources and use in-line compression units to deliver the gas to end users. Adaptation to varying customer demands plays an important role, and it is the responsibility of gas transmission network dispatchers to supply adequate quantities of natural gas to meet consumer requirements and to maintain the pressure level at above the minimum required values. The safe operation of transportation pipeline systems despite load changes is an important topic and requires the assessment of the current and future state of the system. Lack of reliable information on many streams and instrumentation errors create additional challenges in assessing current status. of the transport network. Other distribution networks such as electricity networks, nitrogen/oxygen and hydrogen networks also suffer from this problem[2]. Considering several hundred to several thousand variables of a GTN model, it is possible to measure only a fraction of these variables from a cost and feasibility perspective and there are many unmeasured variables. Therefore, it is essential to use an online estimator to obtain unknown variables using available measurements and smooth the measured variables. GTN is an example of a process with frequent changes, due to ever-changing fluctuations in customer demands and unnotified load changes of natural gas-fired power plants [3]. Real-time optimization (RTO) of gas pipelines under transient conditions is considered a challenging problem. For a process with frequent disturbances, dynamic RTO can be an effective replacement for steady-state RTO [4], while successful implementation of Dynamic-RTO also requires a dynamic data reconciliation module. The quantity of gas contained in a given pipeline segment is defined as the line-pack [5], [6], which is a very important parameter. in gas transportation systems [7], given its use in compensating sudden load changes. As a result, state estimation techniques play a key role in several problems related to the gas industry such as dynamic data reconciliation, determination of pipe bundle of pipelines, appropriate calculation corresponding to gas transactions natural [8], leak detection, demand estimation, optimal sensor placement [9] and as an aid to optimal system control or design. Pipe pack and demand estimation estimates are essential in assessing the current condition of a network and can be useful for reliable planning for the future.