High Resolution Reservoir Simulator Driven Custom Scripts as the Enabler for Solving Reservoir to Surface Network Coupling Challenges

2021 ◽  
Author(s):  
Kanat Aktassov ◽  
Dauletbek Ayaganov ◽  
Kanat Imagambetov ◽  
Ruslan Alissov ◽  
Said Muratbekov ◽  
...  
Keyword(s):  
High Resolution ◽  
Development Planning ◽  
Gas Condensate ◽  
Reservoir Modeling ◽  
Network System ◽  
Field Development ◽  
Pressure Losses ◽  
Custom Made ◽  
Surface Network ◽  
Reservoir Simulator

Abstract This paper presents a practical methodology of optimizing and building a detailed field surface network system by using the high-resolution reservoir simulator driven custom-made Python scripts to efficiently predict the future performance of the vast oil and gas-condensate carbonate field. All existing surface hydraulic tables are quality checked and lifting issue constraints corrected. Pressure losses at the wellhead chokes incorporated into the high-resolution reservoir simulator in the form of equation by using the custom scripts instead of a table format to calculate gas rate dependent pressure losses more precisely. Consequently, all 400+ surface production system manifolds, pipes and well chokes Horizontal Flow Performance (HFP) tables are updated and coupled to the reservoir simulator through Field Management (FM) controller which in turn generates Inflow Performance Relationship (IPR) tables for the coupled wells and passes them to solve the network. The methodology described in this paper applied for a complex field development planning of the Karachaganak. At present, reservoir management strategy requires constant balancing effort to uniformly spread gas re-injection into the lower Voidage Replacement Ratio areas in the Upper Gas-Condensate part of the reservoir due to reservoir heterogeneity. Additionally, an increase in field and wells gas-oil ratio and water-cut creates bottlenecks in the surface gathering system and requires robust solutions to decongest the surface network. Current simulation tools are not always effective due longer run times and simulation instability due to complex network system. As a solution, project-specific network balancing challenges are resolved by incorporating custom-made scripts into the high-resolution simulator. Faster and flexible integrated model based on hydraulic tables reproduced the historical pressure losses of the surface pipelines at similar resolution and generated accurate prediction profiles in a twice-quicker time than existing reservoir simulator. Overall, this approach helped to generate more stable production profiles by identifying bottlenecks in the surface network and evaluate future projects with more confidence by achieving a significant CAPEX cost savings. The comprehensive guidelines provided in this paper can aid reservoir modeling by setting up flexible integrated models to account for surface network effects. The value of incorporating Python scripts demonstrated to implement non-standard and project specific network balancing solutions leveraging on the flexibility and the openness of the modelling tool.

Integrated Field Development Modeling of Block in Giant Oil Reservoir

2021 ◽  
Author(s):  
Kirill Bogachev ◽  
Aleksandr Zagainov ◽  
Evgeny Piskovskiy ◽  
Iuliia Moshina ◽  
Aleksei Grishin ◽  
...  
Keyword(s):  
Field Model ◽  
Integrated Model ◽  
Base Case ◽  
Oil Reservoir ◽  
Network System ◽  
Physical Processes ◽  
Field Development ◽  
Innovative Method ◽  
Software Product ◽  
Surface Network

Abstract The creation and matching of an integrated field model including a model for part of a giant field, well models and surface network model is considered here. The integrated model was created using an innovative method of solving a unified system of equations that cover all the physical processes in the reservoir-well-surface network system; no integrator software was involved. The project involves a history-matched dynamic model covering part of a giant field, a surface network layout and well constructions with the subsurface equipment parameters. These data were fed to a single software product to create a digital twin which would allow simultaneous work with both the reservoir and the network. The approach enabled quick creation and matching of an integrated model with a lot of wells which can create forecasts for various operation modes and estimate the base case production for the infrastructure in place, as well as offers an option to connect new project wells to the current surface network.

Data Analytics into Hydraulic Modelling for Better Understanding of Well/Surface Network Limits, Proactively Identify Challenges and, Provide Solutions for Improved System Performance in the Greater Burgan Field

2021 ◽  
Author(s):  
Qasem Dashti ◽  
Saad Matar ◽  
Hanan Abdulrazzaq ◽  
Nouf Al-Shammari ◽  
Francy Franco ◽  
...  
Keyword(s):  
Production Management ◽  
Planning Process ◽  
System Optimization ◽  
Development Planning ◽  
Operating Conditions ◽  
Flow Assurance ◽  
Operational Parameters ◽  
Field Development ◽  
Hydraulic Models ◽  
Surface Network

Abstract A network modeling campaign for 15 surface gathering centers involving more than 1800 completion strings has helped to lay out different risks on the existing surface pipeline network facility and improved the screening of different business and action plans for the South East Kuwait (SEK) asset of Kuwait Oil Company. Well and network hydraulic models were created and calibrated to support engineers from field development, planning, and operations teams in evaluating the hydraulics of the production system for the identification of flow assurance problems and system optimization opportunities. Steady-state hydraulic models allowed the analysis of the integrated wells and surface network under multiple operational scenarios, providing an important input to improve the planning and decision-making process. The focus of this study was not only in obtaining an accurate representation of the physical dimension of well and surface network elements, but also in creating a tool that includes standard analytical workflows able to evaluate wells and surface network behavior, thus useful to provide insightful predictive capability and answering the business needs on maintaining oil production and controlling unwanted fluids such as water and gas. For this reason, the model needs to be flexible enough in covering different network operating conditions. With the hydraulic models, the evaluation and diagnosis of the asset for operational problems at well and network level will be faster and more effective, providing reliable solutions in the short- and long-terms. The hydraulic models enable engineers to investigate multiple scenarios to identify constraints and improve the operations performance and the planning process in SEK, with a focus on optimal operational parameters to establish effective wells drawdown, evaluation of artificial lifting requirements, optimal well segregation on gathering centers headers, identification of flow assurance problems and supporting production forecasts to ensure effective production management.

Integrated Field Development Planning for Enhanced Condensate Recovery ECR and Gas Storage in Mature Gas Condensate Fields

2018 ◽  
Author(s):  
Harshil Saradva ◽  
Siddharth Jain ◽  
Mark Sarssam ◽  
Masoud Al Hamadi ◽  
Matthew Robert
Keyword(s):  
Gas Storage ◽  
Development Planning ◽  
Gas Condensate ◽  
Field Development

Subsurface Appraisal and Field Development Planning of the Gas Condensate Field GVLA, Angola

2012 ◽  
Author(s):  
Sriram Balasubramanian ◽  
Ben Wang ◽  
Yan Li ◽  
Elliott Ginger ◽  
Baosheng Liang ◽  
...  
Keyword(s):  
Development Planning ◽  
Gas Condensate ◽  
Field Development

Subsurface Appraisal and Field Development Planning of the Gas Condensate Field GVLA

2013 ◽  
Author(s):  
David Maxwell McKay ◽  
William Wilcox ◽  
Anping Yang ◽  
Baosheng Liang ◽  
Joseph Patrick Brinkman ◽  
...  
Keyword(s):  
Development Planning ◽  
Gas Condensate ◽  
Field Development

Features of the Mongi oil-gas-condensate field development (Sakhalin Island)

2020 ◽  
pp. 104-108
Author(s):  
R.R. Haliulin ◽  
◽  
S.N. Zakirov ◽  
A.H. Kha ◽  
N.E. Vedernikov ◽  
...  
Keyword(s):  
Sakhalin Island ◽  
Gas Condensate ◽  
Field Development ◽  
Oil Gas

A Generalized Compositional Approach for Reservoir Simulation

1983 ◽  
Vol 23 (05) ◽  
pp. 727-742 ◽  
Author(s):  
Larry C. Young ◽  
Robert E. Stephenson
Keyword(s):  
Enhanced Recovery ◽  
Gas Condensate ◽  
Reservoir Modeling ◽  
Pressure Equation ◽  
Compositional Modeling ◽  
Fluid Property ◽  
Black Oil ◽  
Fluid Properties ◽  
Newton Raphson ◽  
Raphson Method

A procedure for solving compositional model equations is described. The procedure is based on the Newton Raphson iteration method. The equations and unknowns in the algorithm are ordered in such a way that different fluid property correlations can be accommodated leadily. Three different correlations have been implemented with the method. These include simplified correlations as well as a Redlich-Kwong equation of state (EOS). The example problems considered area conventional waterflood problem,displacement of oil by CO, andthe displacement of a gas condensate by nitrogen. These examples illustrate the utility of the different fluid-property correlations. The computing times reported are at least as low as for other methods that are specialized for a narrower class of problems. Introduction Black-oil models are used to study conventional recovery techniques in reservoirs for which fluid properties can be expressed as a function of pressure and bubble-point pressure. Compositional models are used when either the pressure. Compositional models are used when either the in-place or injected fluid causes fluid properties to be dependent on composition also. Examples of problems generally requiring compositional models are primary production or injection processes (such as primary production or injection processes (such as nitrogen injection) into gas condensate and volatile oil reservoirs and (2) enhanced recovery from oil reservoirs by CO or enriched gas injection. With deeper drilling, the frequency of gas condensate and volatile oil reservoir discoveries is increasing. The drive to increase domestic oil production has increased the importance of enhanced recovery by gas injection. These two factors suggest an increased need for compositional reservoir modeling. Conventional reservoir modeling is also likely to remain important for some time. In the past, two separate simulators have been developed and maintained for studying these two classes of problems. This result was dictated by the fact that compositional models have generally required substantially greater computing time than black-oil models. This paper describes a compositional modeling approach paper describes a compositional modeling approach useful for simulating both black-oil and compositional problems. The approach is based on the use of explicit problems. The approach is based on the use of explicit flow coefficients. For compositional modeling, two basic methods of solution have been proposed. We call these methods "Newton-Raphson" and "non-Newton-Raphson" methods. These methods differ in the manner in which a pressure equation is formed. In the Newton-Raphson method the iterative technique specifies how the pressure equation is formed. In the non-Newton-Raphson method, the composition dependence of certain ten-ns is neglected to form the pressure equation. With the non-Newton-Raphson pressure equation. With the non-Newton-Raphson methods, three to eight iterations have been reported per time step. Our experience with the Newton-Raphson method indicates that one to three iterations per tune step normally is sufficient. In the present study a Newton-Raphson iteration sequence is used. The calculations are organized in a manner which is both efficient and for which different fluid property descriptions can be accommodated readily. Early compositional simulators were based on K-values that were expressed as a function of pressure and convergence pressure. A number of potential difficulties are inherent in this approach. More recently, cubic equations of state such as the Redlich-Kwong, or Peng-Robinson appear to be more popular for the correlation Peng-Robinson appear to be more popular for the correlation of fluid properties. SPEJ p. 727

scholarly journals Incremental and acceleration production estimation and their effect on optimization of well infill locations in tight gas reservoirs

2021 ◽  
Author(s):  
Atheer Dheyauldeen ◽  
Omar Al-Fatlawi ◽  
Md Mofazzal Hossain
Keyword(s):  
Transient Flow ◽  
Development Planning ◽  
Main Role ◽  
Gas Reservoirs ◽  
Type Curves ◽  
Field Development ◽  
Drilling Performance ◽  
Well Location ◽  
Infill Drilling ◽  
Tight Formations

AbstractThe main role of infill drilling is either adding incremental reserves to the already existing one by intersecting newly undrained (virgin) regions or accelerating the production from currently depleted areas. Accelerating reserves from increasing drainage in tight formations can be beneficial considering the time value of money and the cost of additional wells. However, the maximum benefit can be realized when infill wells produce mostly incremental recoveries (recoveries from virgin formations). Therefore, the prediction of incremental and accelerated recovery is crucial in field development planning as it helps in the optimization of infill wells with the assurance of long-term economic sustainability of the project. Several approaches are presented in literatures to determine incremental and acceleration recovery and areas for infill drilling. However, the majority of these methods require huge and expensive data; and very time-consuming simulation studies. In this study, two qualitative techniques are proposed for the estimation of incremental and accelerated recovery based upon readily available production data. In the first technique, acceleration and incremental recovery, and thus infill drilling, are predicted from the trend of the cumulative production (Gp) versus square root time function. This approach is more applicable for tight formations considering the long period of transient linear flow. The second technique is based on multi-well Blasingame type curves analysis. This technique appears to best be applied when the production of parent wells reaches the boundary dominated flow (BDF) region before the production start of the successive infill wells. These techniques are important in field development planning as the flow regimes in tight formations change gradually from transient flow (early times) to BDF (late times) as the production continues. Despite different approaches/methods, the field case studies demonstrate that the accurate framework for strategic well planning including prediction of optimum well location is very critical, especially for the realization of the commercial benefit (i.e., increasing and accelerating of reserve or assets) from infilled drilling campaign. Also, the proposed framework and findings of this study provide new insight into infilled drilling campaigns including the importance of better evaluation of infill drilling performance in tight formations, which eventually assist on informed decisions process regarding future development plans.

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