Analytical approaches are primary reservoir engineering techniques for understatingreservoir/well performance and reservoir characterization which creates additional value on top of comprehensive geological models. Different techniques such as Pressure Transient Analysis (PTA), Rate Transient Analysis (RTA), and analytical models provide good understating on reservoir extension and properties, reservoir connectivity and well interference signatures. For complex carbonate reservoir models, relying solely on petrophysical properties from core and LOG and calibrated is not enough. Several case studies are published where the static model is guided by seismic driven Acoustic Impedance(AI) which matched the porosity at the wellbore. These methods significantly enhance the reservoir property distribution if a reliable seismic data is available. Nevertheless, the permeability map and reservoir connectivity analysis still require detail investigation of well performances and production data. This paper discusses the application of production data analysis to characterize the reservoir in larger scale and reveal the reservoir connectivity and flow barriers in the prevailing heterogeneity. Authors addressed the integrated production data analysis including RTA/PTA, 2D numerical simulation and deconvolution technique in gas cases (Ataei et al 2017). The basic equations of RTA which requires single phase condition are still applicable in the current case study which involve oil above bubble point pressure. Simple 2D numerical simulation were used to address the challenges and the provides a solution to have better understanding of reservoir continuity, a reliable permeability map for upscaling core data and incorporating in the model into large (field scale). The calculated KH from PTA data was also integrated with that of estimated from RTA and evaluated by 2D model before integrating in into full field reservoir simulation model for future forecasting.

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Rate Transient Analysis (RTA) has been used in gas reservoirs as a proven method for reserve estimation, well diagnostic and production performance evaluations. The authors have demonstrated several case studies showing the application of production analysis (PA) for reservoir characterization in gas and single phase oil reservoirs previously (Motaei, 2017, Ghanei and Ataei 2017, Ataei 2018). The adopted method for Integrated Production Analysis (IPA) works well in those case studies after combining the available data from RTA, PTA, or Material balance and basic reservoir engineering tools. The RTA found to be completing those is based on simple production data analysis using flowing data rather than limited shut in and less accurate ones. With benefit of continuous monitoring of FBHP using PDG, it is possible to evaluate the interferences and boundary in distance beside conventional reservoir properties like permeability and skin. These methods were found to be extremely powerful and popular particularly with the high resolution data from pressure downhole gauges (PDG). In this paper we have analyzed the available production data from a gas reservoir in offshore environment in South East Asia. It has been developed with five high PI wells and smart completion and monitored closely with PDG and other surveillance data to understand the contact movement during the production history. Due to the complexity of the field, different methods of production data analysis were used to understand the production performances. The recent advances in RTA allows us to apply the classical single well analysis method to a multiple well and multiple phase flow using Generalized Pseudo Pressure (GPP). The previously published workflow by the authors (Ghanei and Ataei, 2017) is used for this case study. We evaluate this technique for a multi well gas field with advancing aquifer. The connected volumes as estimated by single well analysis will be used for a group of wells which are communicating and have interference. We have also used a simple reservoir modelling approach to define scenarios which fit the production data and can be used for forecasting which can potentially save study teams time when deciding on the potential value and defining the targets of a major infill drilling project.

Material balance analysis, a primary engineering technique, is an indispensable tool used for understanding the production performance and field management of mature gas reservoirs. Compilation and analysis of pressure-production data together with acomprehensive geological understanding including in-place hydrocarbon volumes and inter-block communication are prerequisites for material balance analysis. Deviation of observed P/Z data away from a straight idealised line necessitates further study, as it often indicates erroneous estimates of participating in-place volumes, aquifer support or reserves. Lack of pressure measurements, questionable stratigraphic correlations and uncertainty surrounding aquifer propertiesor reservoir connectivity highlight the requirement for further evaluation. The objective of study is to develop a multi-tank material balance modelfor a mature, heterogeneous and compartmentalised carbonate gas field. Ultimately, the model must besufficiently robust to elucidate the field's production mechanism and optimise future field-development opportunities. In this field, the pressure production behavior can be divided into two trends, an early rapid declining pressure trend, followed by a stabilised gradual pressure decline. Owing to higher drawdown in the field's early production life and insufficient recharging, the quick pressure decline underestimates the initial in-place gas volume. This volume is not adequate to support the sustained gas production rates observed in later years. This observation required further detailed analysis regarding the nature of zonal communication across adjacent reservoir intervals to better understand the production behavior of development wells during the design of the material balance model. This paper discusses a study in which material balance analysis is coupled with multi-field network models. Implementation of this workflow can be usedto drive subsurface developmentsin a relatively short period.

Production Data Analysis (PDA) has been widely accepted as a valuable analytical tool for well performance evaluation, production forecasting and reservoir characterization. It is fast, practical, and inexpensiveand it can answer many questions about the connected volume to the well, flow regime, average permeability and skin, as well as any boundary within the radius of investigation of the well. It becomes even more important in the case of complex systems such as finely laminated sand reservoirs, or highly heterogeneous multi-stacked reservoirs where sometimes numerical simulation model miscarries in predicting the reservoir performance. Analytical approaches for PDA are variants and require different levels of details in the input. Each is established based on certain assumptions and concepts, and comes with specific limitations. Despite overlap amongst the various methods, each has an advantage in particular application over the others. Therefore, one must be vigilant to use each method for the right purposes in addition to confirm the results and unveil possible uncertainties through using several different methods. This paper integrates basic production and reservoir data through different platforms and methods. Diagnostic plots, General Material Balance (GMB), Pressure Transient Analysis (PTA), deconvolution, nodal analysis, Rate Transient Analysis (RTA), and Flowing Material Balance (FMB) are extensively used to explain the reservoir behavior through PDA. It validates RTA and FMB as an approach for reservoir characterization and reserve estimation without the need to shut-in the well, and defer the production. The benefit of continuously monitoring Flowing Bottom Hole Pressure (FBHP) using Permanent Downhole Gauge (PDG) and applying deconvolution to detect well interference and reservoir boundaries is also discussed. We have also looked at the limitation and advantage of each method and how the integration of those can provide a full picture and enhance the results. We have studied several gas fields. The results of analysis provided an accurate perception and understanding of reservoir behavior and characteristics, well interaction and interference, potential for infill wells, production issues and well constraints, estimation of the connected volume, and eventually led to generation of a reliable analytical reservoir model for the production forecast. The estimated connected volume was tested and proved to be reliable based on infill drilling. The workflow focuses on examining the data quality, confirming the validity of work, and achieving the maximum possible insight through integration of different analytical methods. An integrated workflow is introduced for PDAand successfully applied on different cases of highly heterogeneous conventional gas reservoirs with huge complexities. The paper demonstrates one of the case study as example. The proposed workflow shows to be very powerful particularly when large volume of data from pressure downhole gauges (PDG) is available. It saves significant time for the study team in determining the potential value of a project.