The Eocene C-Sup VLG3676 reservoir is one of the most important oil reservoirs of Western Venezuela. It has a high lateral sedimentological heterogeneity, some sand production issues due to low sandstone cohesion and high stress gradients, and asphaltene precipitation problems. This has lead to the construction of a compositional/geomechanical model in order to design a palliative strategy. The proposed modeling methodology includes nine phases: 1) Development of the 3D mechanical earth model (MEM) to simulate reservoir compaction; 2) Quality control of the static model, including the relative permeability values; 3) Development of a fluid model that predicts the onset of asphaltene precipitation; 4) Development of a rock-fluid interaction model; 5) Initialization and calibration of the compositional model; 6) Coupling of the compositional and geomechanics models; 7) History matching; 8) Analytical estimation of the onset of sand production; 9) Implementation of an opportunity index analysis for asphaltene precipitation and sand production. Based on this compositional/geomechanical model it has been possible to map the risk of asphaltene precipitation and sand production in the reservoir, therefore showing that such problems are critical in the Eocene Misoa C-2-Sup and C-3-Sup stratigraphic units, due to the energy depletion caused by the production.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders.
Decisions in E&P ventures are affected by Bias, Blindness, and Illusions (BBI) which permeate our analyses, interpretations and decisions. This one-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact. Bias refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion. Blindness is the condition where we fail to see an unexpected event in plain sight. Illusions refer to misleading beliefs based on a false impression of reality.
This paper reviews how the Rotary Steerable System (RSS) market has changed over the last two decades. It explores current market forces; specifically the shift in RSS philosophy resulting from ever-improving motor steerable technology. It describes how the need for longer laterals with minimal tortuosity, maximum drilling efficiency, reduced risk of unplanned events, and elimination of AFE overspend, along with the paradigm shift in the directional drilling market seen since 2014, drove the specification for a newgeneration RSS tool. The paper describes the development of a new RSS with a topology and control concept that allows full proportional control of bias from a fully rotating, push-the-bit tool, with the ability to "turn off" any bias during operations where side force is undesirable and to minimize potential tortuosity. It describes how the design team focused on modular design and rapid turn around of tools, in order to maximize utilization and efficiency. Field-test results are included, which demonstrate build and turn at up to 10 /100 ft. and the ability to drill accurate lateral sections. Field results also include the use of ultrasonic imaging while drilling to investigate hole quality.
Good perforating practices are equally important for water injectors as for producers to achieve effective and efficient reservoir pressure support, which, in turn, results in better field productivity. An aspect of good perforating practice is to achieve clean perforations so that the injection skin is minimized. Dirty perforations, whether due to perforation debris or crushed zones around the perforation tunnel can affect a well's injectivity. This problem is further compounded when well injection starts as particles in injection water quickly accumulate at the perforations, causing rapid injectivity drop. Therefore, clean perforations are important to deliver good well injectivity.
This is a case study of a wellbore implosion technique on perforations of injector wells in a field in Oman. Compared to perforating in a high-pressure reservoir, achieving clean perforations in a low-pressure reservoir is more difficult as perforating has less potential to breakdown the crushed zone and to purge the crushed material together with the debris from the perforation tunnels. This problem may be overcome by the wellbore implosion technique, using a dynamic underbalance system.
Various perforating systems were tried for injector wells in this field. Reactive liner shaped charge, propellant system, and post-perforating dynamic underbalance techniques were used in the same well. A dynamic underbalance gun that creates wellbore implosion was designed, and recorded pressure gauge data were matched to the simulated data. Reservoir properties of each well from the logs and from the well injectivities after applying the above-mentioned perforating systems were compared. As the principle in this case study is perforation cleanup, it is also relevant to producers. It is also relevant to other wells whether on land or offshore, both producers and injectors of any pressure regime that could be suffering from poor cleanup of perforations.
Integrated asset modeling (IAM) offers the oil industry several benefits. Next-generation reservoir simulators help achieve faster runtimes, offer insight into interaction between various components of a development, and can be used as an effective tool in detecting bottlenecks in a production system as well as a constant and more effective communication tool between various departments. IAM provides significant opportunities for the optimization of very large or complex infrastructures and life-of-field analyses of production optimization scenarios.
Simultaneous modeling of surface and subsurface components helps reduce time and enhances efficiency during the decision-making process, which eliminates the requirement for tedious, time-consuming work and iterations between separate solutions of reservoir and surface networks. Beyond this convenience, this technology makes it possible to reach more robust results more quickly using surface-subsurface coupling. The objective of this study is to outline the advantages and the challenges in using next-generation simulators for the simulation of multiple reservoirs in integrated asset management.
Simultaneous simulation of multiple reservoirs adds another dimension of complexity to the process of integrated asset modeling. Several sub-reservoir models can be simulated simultaneously in large fields comprising sub-reservoirs with complex surface systems, which could otherwise become very tedious to handle. In this study, a next-generation reservoir simulator is coupled with an optimization and uncertainty tool that is used to optimize the net present value of the entire asset. Several constraints and bottlenecks in such a large system exist all connected to one another. IAM proves useful in debottlenecking to increase the efficiency of the total system. The strengths and difficulties associated with simultaneous simulation and optimization of multiple reservoirs are compared to the more conventional way of simulating the assets separately, thus illustrating the benefits of using next-generation reservoir simulators during the optimization of multiple reservoirs.
The results show that a simultaneous solution of the surface-subsurface coupling gives significantly faster results than that of a system that consists of separate solutions for surface and subsurface. The speed difference becomes more significant when the number of reservoirs simulated is greater than one. This study outlines the workflow in setting up the model, the CPU time for each component of the simulation, and the explanation of each important item in this process to illustrate the incremental benefits of the use of next-generation reservoir simulators in simulating multiple reservoirs with surface facilities taken into account.
Although the use of next-generation simulators is becoming more common, solid examples that illustrate the benefits of simultaneous simulation of multiple reservoirs with surface facilities under several different constraints, like this study, are important to prove the use of such tools to carry out the optimization in a system that handles decision parameters and constraints simultaneously.
Reservoir simulation history matching is one of the most complex and time consuming process, however, it ensures that the model developed is useful for forecasting and management decisions. By nature, an Integrated Asset Modeling model can be made up of hundreds of nodes, making it complex and difficult to manage if a proper methodology is not implemented to allow an effective history matching, especially when developing all the components of the IAM model. The purpose of this paper is to share lessons learned from a methodology that allows the development of reservoir models via material balance, proper matching of wellbore models and wellbore tests; calibration of the surface network and ultimately, history matching of an Integrated Asset Model, following rigorous quality assurance and quality check procedures. Issues addressed include: characterization of the reservoir-wellbore system, knowledge of main drive mechanisms, aquifer uncertainty, tubing flow assessment. The methodology enabled production history matching of 15 producing gas wells; ensuring that the IAM model developed is therefore a reliable forecasting tool. In addition, Simulation run time reduction was achieved by switching from a rate dependent constrained system to a pressure drop dependant system. Production history matching should precede any numerical simulation study, as it provides useful knowledge of the properties and characteristics of the reservoir-wellbore-surface network, leaving little room for adjustments, which constitutes an excellent starting point for numerical models; hence an IAM approach represents basis for the construction and quality check of more rigorous multi cells numerical reservoir simulation models.
Tinoco, Jose (Schlumberger) | Celis, Criss (Schlumberger) | Lopez, Luis (Schlumberger) | Rodriguez, Ernesto (PDVSA) | Coronel, Gustavo (PDVSA) | Lopez, Jose (a Schlumberger company) | Bits, Smith (a Schlumberger company)
The history of La Ceiba field began 10 years ago when six exploration wells were drilled to assess the potential of this field. The wells were drilled with several incidents of stuck pipe and the resulting necessary sidetracks to reach the final depth. Until last year no further attempt had been made to drill in this field. With little information available from the exploration wells concerning drilling practices, the drilling campaign began with the goal of improving the previous performance, making the drilling of the complete wells faster and safer than in the previous drilling. An engineering process was begun to find the best drilling solution for the field, starting with proven technologies such as positive displacement motors (PDM) and drill bits used in similar fields; however, this methods alone were not sufficient to meet the challenges of the field. New technologies were used for the different challenges and applications through coordinated work between the drilling engineering departments of the different parties involved in this field and using all the information available in the drill bit selection database, including logs and stability data for the tools selected to drill each phase of the wells. With evolution of the learning curve, drilling progressed from initial drilling involving 12 runs with time-consuming trips to surface to change either the drill bit or PDM, to drilling the same interval in 5 runs with the time on bottom increasing compare to previous experiences due to the introduction of tools more suitable to the environment requirements a rotary steerable systems (RSS) in combination with a specially designed drill bit. Problems commonly faced in the upper sections were, the trajectory was not strictly followed, were solved with the introduction of the RSS in this section; use of the tool saved 10 days of rig time and set a bench mark for the field and similar wells in western Venezuela.
A fully compositional integrated subsurface-surface model for the Production Unit Carito was develop to support a future exploitation plan that considers the maintaining of the oil production plateau and an aggressive infill drilling for the next 3 years. These issues make imperative an integrated asset modeling that conduct and help the reservoir management, decision making and accurate estimation of additional facilities capabilities.
The Production Unit Carito comprises two of the most important fields located to the east of Venezuela: El Carito and Mulata. These fields present deep and complex reservoirs with an unconventional column of fluids, showing a marked compositional gradient which cover from an initially undersaturated gas condensate at the top of the structure to an undersaturated black oil zone toward the base. The OOIP is about 7, 000 MMSTB and the current oil production rate reaches 230 MSTB/D. A secondary recovery process was implemented over 12 years ago, based on the injection of approximately 1, 000 MMSCF/D of natural gas.
Because of prevailing reservoir pressure conditions, the increasing volumes of produced gas has led that some points of the surface facilities reach their operational limits. Furthermore, the first of all, 187 well models in compositional format were built, performing sensitivities to define the multiphase flow correlations for vertical pipe and for critical/subcritical flow in chokes, considering dynamic gradients and production tests. A network model, which comprises more than 800 Km of lines, was also built in compositional mode honoring line sizes, lengths, elevation changes and connection points, reducing the number of nodes to decrease computing time. The robust numerical simulation model comprises more than 300, 000 active cells, and represents the most reliable characterization of the reservoirs. Each model was firstly initialized and isolated run to discard internal inconsistency. Finally, the full integration was done considering the sand face on the wells as the coupling point.
The integrated subsurface-surface simulation allowed predicting the behavior of reservoir production taking into account the constraints of the surface facilities. In this way, it was reduced the uncertainty of forecasts, and were identified limitations at surface facilities. It was also possible to determine accurately the details of the hydrocarbons streams at different pressure stages of the network, with an excellent matching with the oilfield production data.
Pérez, F. (PDVSA) | Albarracin, R. (PDVSA) | Jazzan, W. (PDVSA) | Valera, A. (PDVSA) | Llavaneras, A. (PDVSA) | Arguello, V. (PDVSA) | Griborio, G. (Halliburton) | Novaes, K. (Halliburton) | Acosta, I. (Halliburton) | Luján, L. (Independent Consultant)
Generating an integrated conceptual probabilistic model forecast for exploration of hydrocarbon fields is essential to the decision-making process when developing a strong portfolio of exploration prospects. It is important not only when considering the potential volume that could be discovered within each prospect, but also when considering drilling plans for extracting these reserves. It is important to both define the best strategies for achieving strong growth and sustainable profit over time and to consider possible risks and uncertainties that could impact such results.
Southeast of Lake Maracaibo, the most important axis of production growth is located within the western part of Venezuela, formed by the Ceiba, Tomoporo and Franquera fields, where a set of exploratory prospects comprise 36 potential reservoirs. Exploratory wells are planned to validate the estimated reserves of the development to help increase oil production. The optimization and prioritization of exploration prospects provides the foundation for creating an interactive workflow that is automated, versatile, and innovative to help optimize the portfolio of the defined prospects.
This workflow provides a strategy based on the generation and use of a probabilistic conceptual reservoir model based on information from neighboring fields and exploratory studies. Using this approach, the initial potential for each well and each of the prospects' different production profiles can be probabilistically calculated based on the development strategy. This allows visualization of how many wells should be drilled, the capabilities of the surface facilities, the number of personnel required to operate the field, and other additional important aspects.
This conceptual probabilistic model forecast (prospects—wells—surface) is connected to an economic-risk-uncertainty model, creating fully integrated modeling. When new information is gained, automated adjustments can be made, thus achieving quick optimal viewing of opportunities within the portfolio of prospects and improving decision making.