Peering into the internal structure of cold pools and their interactions with a dense observational network

<p>Melting and evaporation of hydrometeors in and below convective clouds generates cold, dense air that falls through the atmospheric column and spreads at the surface like a density current, the cold pool. In modelling studies, the importance of cold pools in controlling the lifecycle of convection has often been emphasized, being through their organization of the cloud field or through their sheer deepening of the convection. Larger, longer-lived cold pools benefit convection, but little is actually known on the size and internal structure of cold pools from observations as the majority of cold pools are too small to be captured by the operational surface network.  One aim of the field campaign FESSTVaL was to peer into the internal structure of cold pools and their interactions with the underlying land surface by deploying a dense network of surface observations. This network consisted of 80 self-designed cold pool loggers, 19 weather stations and 83 soil sensors deployed in an area of 15 km around Lindenberg. FESSTVaL took place from 17 May to 27 August 2021.</p> <p>In principle, cold pool characteristics are affected both by the atmospheric state, which fuels cold pools through melting and evaporation of hydrometeors, and the land surface, which acts to destroy cold pools through friction and warming by surface fluxes. In this talk, the measurements collected during FESSTVaL will be used to shed light on these interactions.  We are particularly interested to assess how homogeneous the internal structure of cold pools is and whether heterogeneities of the land surface imprint themselves on this internal structure. The results will be compared to available model simulations.</p>

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

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.

Optimizing Gas Production from Giant Multi-Reservoir Onshore Abu Dhabi Gas Field by Introducing Wellhead Compressors and Reconfiguring the Surface Network Using an Integrated Asset Model IAM

The giant onshore gas field in this study consists of six stacked reservoirs and has been producing for over three decades. The field has more than 150 gas producing wells and has several wells which have low-intermittent gas production rates. The low production is attributed to weak wells sharing common trunk lines with prolific wells. This study investigates the impact of choke optimization, surface network reconfiguration and wellhead compression to improve the gas production from weak wells after performing detailed analysis of possible root causes from the surface network by using an Integrated Asset Model (IAM) as the digital twin of the field. The investigation begins by identifying weak producers and involves studying the integrated surface network and determining the root causes for backflow and unstable hydraulics. After surface network issues have been recognized, remedial modification will be implemented. The impact of different choke settings on the wells are studied. The final step will be to introduce wellhead compressors on the weak producers. Extensive sensitivity scenarios are performed to identify the optimum compressor inlet pressure for each individual wellhead compressors and the wells which benefit most from the application of wellhead compressors are ranked. The multi-reservoir gas field contains six stacked reservoirs which are producing under depletion mode and share a common surface network. Root causes of weak or shut-in wells due to backflow or hydraulic issues are successfully identified by using an IAM simulation tool. The investigated remediations were simple optimization of the choke settings, reconfiguration of the surface network, and application of wellhead compressors to improve the gas production from the problematic wells. It is observed that the addition of wellhead compressors resulted in the most significant increase and more sustainable production from the weaker wells. Furthermore, the final selection of candidate wells for wellhead compressors can be dictated according to the highest gain from the ranking. The study revealed that the implementation of wellhead compressors will significantly increase the cumulative gas production from the selected wells at the end of field life and will result in positive production acceleration from the field perspective. This study shows that adding wellhead compressors to weak producers can mitigate the production bottlenecks and backflow issues and that higher and more sustainable gas production can be achieved from the weak wells after understanding the primary causes for low/intermittent production from the IAM which is acting as the digital twin of the field.

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

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.

A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models

Full-physics subsurface simulation models coupled with surface network can be computationally expensive. In this paper, we propose a physics-based subsurface model proxy that significantly reduces the run-time of the coupled model to enable rapid decision-making for reservoir management. In the coupled model the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves which are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the CPU intensive reservoir simulation is replaced with an IPR database constructed from a data pool of one or multiple simulation runs. The IPR database captures well performance that represents subsurface reservoir dynamics. The proxy model can then be used to predict the production performance of new scenarios – for example new drilling sequence – by intelligently looking up the appropriate IPR curves for oil, gas and water phases for each well and solving it with the surface network. All necessary operational events in the surface network and field management logic (such as facility constraints, well conditional shut-in, and group guide rate balancing) for the full-coupled model can be implemented and honored. In the proposed proxy model, while the reservoir simulation component is eliminated for efficiency. The entirety of the surface network model is retained, which offers certain advantages. It is particularly suitable for investigating the impact of different surface operations, such as maintenance schedule and production routing changes, with the aim of minimizing production capacity off-line due to maintenance. Replacing the computationally intensive subsurface simulation with the appropriate IPR significantly improves the run time of the coupled model while preserving the essential physics of the reservoir. The accuracy depends on the difference between the scenarios that the proxy is trained on and the scenarios being evaluated. Initial testing with a complex reservoir with more than 300 wells showed the accuracy of the proxy model to be more than 95%. The computation speedup could be an order of magnitude, depending largely on complexity of the surface network model. Prior work exists in the literature that uses decline curves to replicate subsurface model performance. The use of the multi-phase IPR database and the intelligent lookup mechanism in the proposed method allows it to be more accurate and flexible in handling complexities such as multi-phase flow and interference in the surface network.

An Optimization-Based Facility Network Solver for Well Allocation in Reservoir Simulation

When coupling reservoir simulators to surface network solvers, an often used strategy is to perform a rule or priority-driven allocation based on individual well and group constraints, augmented by back-pressure constraints computed periodically by the network solver. The allocation algorithm uses an iteration that applies well-established heuristics in a sequential manner until all constraints are met. The rationale for this approach is simply to maximize performance and simulation throughput; one of its drawbacks is that the computed allocation may not be feasible with respect to the overall network balance, especially in cases where not all wells can be choked individually. In the work presented here, the authors integrate the well allocation process into the network flow solver, in the form of an optimization engine, to ensure that the solution conforms to the network rate and pressure balance equations. Results for three stand-alone test cases are discussed.

An Algebraic Approach to Find Some Topological Indices of Derived Graphs of the Benzene Ring

Topological indices play a vital role in understanding the chemical and structural properties of the chemical compounds and nanostructures. By finding the M-polynomial of a graph representing a chemical compound, one can obtain the closed forms of some of the commonly known degree-based topological indices of the compound, such as the Zagreb index, general Randic ́ Index and harmonic index. In this article, we obtain the expression for the M-polynomial of the derived graphs of the Benzene ring embedded in the P-type surface network in 2D, namely the line graph, the subdivision graph, and the line graph of its subdivision. Furthermore, some of the degree-based topological indices are obtained for these graphs using their M-polynomials.

New method for Handling of Infrastructural Constraints for Integrated Modeling in Steady Case

Recently, more and more reservoir flow models are being extended to integrated ones to consider the influence of the surface network on the field development. A serious numerical problem is the handling of constraints in the form of inequalities. It is especially difficult in combination with optimization and automatic control of well and surface equipment. Traditional numerical methods solve the problem iteratively, choosing the operation modes for network elements. Sometimes solution may violate constraints or not be an optimal. The paper proposes a new flexible and relatively efficient method that allows to reliably handle constraints. The idea is to work with entire set of all possible operation modes according to constraints and control capabilities. Let's call this set an operation modes domain (OMD). The problem is solved in two stages. On the first stage (direct course) the OMD are calculated for all network elements from wells to terminal. Constraints are handled by narrowing the OMD. On the second stage (backward course) the optimal solution is chosen from OMD.

Integrated Field Development Modeling of Block in Giant Oil Reservoir

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.