Waterflooding is the main technic to recover hydrocarbons in reservoirs. For a given set of wells (injectors and producers), the choice of injection/production parameters such as pressures, flow rates, and locations of these boundary conditions have a significant impact on the operating life of the wells. As a large number of combinations of these parameters are possible, one of the critical decision to make is to identify an optimal set of these parameters. Using the reservoir simulator directly to evaluate the impact of these sets being unrealistic considering the required number of simulations, a common approach consists of using response surfaces to approximate the reservoir simulator outputs. Several techniques involving proxies model (e.g., kriging, polynomial, and artificial neural network) have been suggested to replace the reservoir simulations. This paper focalizes on the application of artificial neural networks (ANN) as it is commonly admitted that the ANNs are the most efficient one due to their universal approximation capacity, i.e., capacity to reproduce any continuous function. This paper presents a complete workflow to optimize well parameters under waterflooding using an artificial neural network as a proxy model. The proposed methodology allows evaluating different production configurations that maximize the NPV according to a given risk. The optimized solutions can be analyzed with the efficient frontier plot and the Sharpe ratios. An application of the workflow to the Brugge field is presented in order to optimize the waterflooding strategy.
Unexpected water accumulation (called perched water) can be present inside hydrocarbon bearing reservoirs. In case of limited or poor geophysical data, the prediction of this accumulation may be difficult.
In this paper, a real case is used to show how the presence of perched water was initially supposed and then verified through production data analysis.
During the development campaign of a deep water reservoir in West Africa, a water injector well found an unexpected shallower water table. To understand the nature of this water, the gas while drilling data of two oil producer drilled in the same area of the water injector were analysed. Based on this analysis the last meters of the open hole section of both oil producers were in water. The integration of gas while drilling data, stratigraphy, sedimentology and structural settings knowledge of the area suggested that this water was locally trapped during oil migration, most likely due to the presence of a structural barrier.
The two oil producer wells, located in the supposed perched water area, were successfully started-up. The behavior of both wells was daily monitored to understand and confirm the nature of perched water phenomenon. From day one, the two wells showed water production. After few weeks, the water cut of one well clearly started to reduce. For the other well, the water cut behavior was constant and only after one year of production the declining trend was appreciated. The observed declining trend of water production was the final confirmation that aquifer in this sector of the field is isolated and with limited extension. The water cut trend was also captured in the 3D dynamic reservoir model. In addition, tracers were implemented in the model to identify different water production sources (injected or perched) and to forecast their evolution during the field life.
The literature on perched water is quite limited and usually this kind of phenomenon is detected and described only on the geological side, but the production behavior of this water is rarely observed. This case study is integrating the geological and geophysical knowledge of the field with production data analysis to understand perched water behavior and can be considered a reference for other similar situation.
This challenging reservoir characterization case study is defined by the interaction between two reservoirs with different production mechanisms: a fractured basement reservoir and an overlying sandstone reservoir. The existing static geologic concept has been significantly enhanced by integrating pressure data from a unique three-year shut-in period to aid modeling of fractured reservoir connectivity. Previously, the seismic dataset was predominantly used to model the fault and fracture network and guide well planning. In the current approach, the full field data set, including all drilling parameters and new reservoir surveillance data were integrated to address uncertainty in the connected hydrocarbon volume and the relative importance of each production mechanism. The result is a reservoir management tool with which to test re-development concepts and effectively manage pressure decline and increasing gas/oil ratio (GOR) and water production.
To achieve a fully integrated history matched model, the first step was to make a thorough review of the existing detailed seismic interpretation, vintage production logging tool runs (PLT's), wireline logs (including borehole image logs (BHI)) and drilling data to find a causal link between hydraulically conductive fractures and well production behavior. In parallel, a material balance exercise was run to incorporate the new pressure data acquired during the field's shut-in period. The results of the material balance analysis were combined with seismic and well data to define the distribution of connected fractures across the field. Additionally, the material balance analysis was used to determine the connected hydrocarbon volume, the distribution of initial oil in-place and the relative hydrocarbon contribution from each production mechanism.
The field is covered by multi-azimuth 3D seismic and 43 vertical to highly deviated development wells, providing significant static and dynamic data for characterizing the distribution of connected fractures. Despite this high quality, diverse and field-wide dataset, prior modeling iterations struggled to sufficiently describe the production behavior seen at the well level. This has resulted in a major challenge to predicting the production behavior of new development wells and planning for reservoir management challenges. Capturing the complex interaction between production variables (including lithology, matrix versus fracture network, geomechanical stresses, reservoir damage and pressure depletion) at a field level instead of at an individual well level resulted in a unified static and dynamic model that reconciles all scales of observation.
This oilfield represents a unique reservoir characterization opportunity. The result is a key example of how iterative, integrated geological and engineering driven reservoir modeling can be used to inform the development in a complex, mature field. This case study provides an excellent analogue for the reservoir characterization of other fractured Basement fields and/or Basement-cover reservoir couplet fields in the early to late phases of their development.
Weijermans, Peter-Jan (Neptune Energy Netherlands B.V.) | Huibregtse, Paul (Tellures Consult) | Arts, Rob (Neptune Energy Netherlands B.V.) | Benedictus, Tjirk (Neptune Energy Netherlands B.V.) | De Jong, Mat (Neptune Energy Netherlands B.V.) | Hazebelt, Wouter (Neptune Energy Netherlands B.V.) | Vernain-Perriot, Veronique (Neptune Energy Netherlands B.V.) | Van der Most, Michiel (Neptune Energy Netherlands B.V.)
The E17a-A gas field, located offshore The Netherlands in the Southern North Sea, started production in 2009 from Upper Carboniferous sandstones, initially from three wells. Since early production history of the field, the p/z plot extrapolation has consistently shown an apparent Gas Initially In Place (GIIP) which was more than 50% higher than the volumetric GIIP mapped. The origin of the pressure support (e.g. aquifer support, much higher GIIP than mapped) and overall behavior of the field were poorly understood.
An integrated modeling study was carried out to better understand the dynamics of this complex field, evaluate infill potential and optimize recovery. An initial history matching attempt with a simulation model based on a legacy static model highlighted the limitations of existing interpretations in terms of in-place volumes and connectivity. The structural interpretation of the field was revisited and a novel facies modeling methodology was developed. 3D training images, constructed from reservoir analogue and outcrop data integrated with deterministic reservoir body mapping, allowed successful application of Multi Point Statistics techniques to generate plausible reservoir body geometry, dimensions and connectivity.
Following a series of static-dynamic iterations, a satisfying history match was achieved which matches observed reservoir pressure data, flowing wellhead pressure data, water influx trends in the wells and RFT pressure profiles of two more recent production wells. The new facies modeling methodology, using outcrop analogue data as deterministic input, and a revised seismic interpretation were key improvements to the static model. Apart from resolving the magnitude of GIIP and aquifer pressure support, the reservoir characterization and simulation study provided valuable insights into the overall dynamics of the field – e.g. crossflows between compartments, water encroachment patterns and vertical communication. Based on the model a promising infill target was identified at an up-dip location in the west of the field which looked favorable in terms of increasing production and optimizing recovery. At the time of writing, the new well has just been drilled. Preliminary logging results of the well will be briefly discussed and compared to pre-drill predictions based on the results of the integrated reservoir characterization and simulation study.
The new facies modeling methodology presented is in principle applicable to a number of Carboniferous gas fields in the Southern North Sea. Application of this method can lead to improved understanding and optimized recovery. In addition, this case study demonstrates how truly integrated reservoir characterization and simulation can lead to a revision of an existing view of a field, improve understanding and unlock hidden potential.
Gas injection is a proven EOR method in the oil industry with many well-documented successful field applications spanning a period of more than five decades. The injected gas composition varies between projects, but is typically hydrocarbon gas, sometimes enriched with intermediate components to ensure miscibility, or carbon dioxide in regions such as the Permian Basin, where supply is available at an attractive price.
Miscible nitrogen injection into oil reservoirs, on the other hand, is a relatively uncommon EOR technique because nitrogen often requires a prohibitively high pressure to reach miscibility. Unlike other injection gases, the minimum miscibility pressure for nitrogen decreases with increasing temperature. In fact, in deep, hot reservoirs containing volatile oil, nitrogen may develop miscibility at a pressure similar to the MMP for hydrocarbon gas or carbon dioxide. The phase behavior is more complicated than what can be captured by correlations and hence requires equation-of-state calculations.
Results from a recent EOR screening study in ADNOC indicate that a couple of high-temperature oil reservoirs in Abu Dhabi may be potential targets for miscible nitrogen injection. This paper discusses key aspects of the EOS modeling. Advanced gas injection PVT data are available to enable a fair comparison between nitrogen, carbon dioxide and lean hydrocarbon gas. In this work, we have modelled and analyzed the phase behavior of two volatile oil systems with respect to nitrogen, hydrocarbon gas, and carbon dioxide injection, as part of a reservoir simulation study, which will be covered in a subsequent publication; see
Video images have traditionally provided intuitive visual analysis in a wide range of wellbore diagnostic situations. Step changes in computer vision techniques and image processing have led to the ability to make measurements from images (visual analytics). This paper demonstrates several applications where the application of this new data analytics source, combined with state-of-the-art acquisition technology, have further improved understanding of complex well issues while reducing operational time, risk and cost. Examples include hydraulic fracturing, well integrity, erosion, restrictions and leaks. The paper will describe the methods and process of this visual analytics technique through discussion of the three main work flow stages from data acquisition to final analytical product, including the innovative developments in sensor, system and computer vision applications that support each step: 1. Acquisition of full circumferential, depth-synchronized video data of the wellbore. An array of four orthogonally positioned cameras, pointing directly at the pipe wall, concurrently record overlapping images, enabling a continuous full-well video dataset to be obtained.
A Digital Twin is a software representation of a facility which can be used to understand, predict, and optimize performance to help to achieve top performance and recover future operational losses. The Digital twin consists of three components: a process model, a set of control algorithms, and knowledge.
Usually the time for commissioning a project exceeds the initial estimations, therefore delays in project completion are quite common. This is often because ICSS testing is done on a static system which does not account for how the system will react dynamically to certain scenarios such as start-ups and shutdowns. Issues such as configuration errors, loop behaviors, start-up over-rides, dead-lock inter-trips and sequence logic are difficult to predict and are impossible to anticipate during static testing. Such delays lead to higher costs and therefore reduced revenue.
This paper aims to describe the most innovative approach to Project & Operational Certainty, which addresses these issues by using a Digital Twin for commissioning support and training. One successful use of this approach was in the Culzean project, an ultra-high-pressure high temperature (UHP/HT) gas condensate development in the UK sector of the Central North Sea. A high-fidelity process model was built and fitted to the actual plant performance based on equipment data sheets. This was connected to ICSS database and graphics, offering a realistic environment, very close to the one offshore, which had the same look and feel for the operators.
Dynamic tests conducted on the Digital Twin predicted issues on the real system, which enabled potential solutions to be tested, leading to a significant decrease in the time spent and cost during commissioning. All the operating procedures were dynamically tested, which enabled us to correct errors, saving time before First Gas. Additionally, all CRO (Control Room Operators) and field technicians were trained and made familiar with the system months in advance, aiming to avoid future unnecessary trips during First Gas.
Finally, all the control loops were fine tuned in the Digital Twin and parameters were passed to off shore, to be used as first starting point. It is expected that these parameters will be very close to fine operational points, as the model used is high fidelity model and very close to real system offshore.
Recently two multilateral horizontal wells have been completed offshore using dedicated multistage hydraulic fracturing completions. The first well, located in the Central North Sea (referred to as ML-CNS), was stimulated using acid fracturing; while the second well, located in the Black Sea (referred to as ML-BKS), was stimulated using proppant fracturing. This paper presents the different drivers, challenges and lessons learned for each well while emphasizing the well construction and stimulation methodologies developed for the different reservoirs and field characteristics.
The field development drivers for drilling and completing these offshore hydraulic fractured multilateral wells, a first of their kind globally, was different for each case. The objective of the first project, initially considered uneconomic, was to engineer a technical solution for completion and production of two separate reservoirs with only one subsea well. The second project was seeking to optimize infill drilling from the last available slot on the offshore platform to maximize reservoir contact and production in the same reservoir. ML-CNS was a TAML Level 2 completion with a 14-stage, 5 ½" multistage completion run in each lateral and set-up for sequential acid fracturing. Operationally, the first lateral was drilled and stimulated, followed by the drilling and stimulation of the second lateral, using the drilling whipstock to navigate through the multilateral junction. ML-BKS was a TAML Level 3 completion that had a 6-stage, 4 ½" multistage completion installed in each lateral, which were proppant fractured following a sequence designed to minimize the jack-up rig time required. Both legs were drilled and completed prior to starting the stimulation, access to either lateral was achieved with the existing workover unit on the platform by manipulating a custom designed BHA.
The lessons learned from the first project executed in the North Sea were able to be transferred and applied to the second project in the Black Sea to allow for a more efficient and confident completion solution. Led by varying economical and regional constraints, the key factor for both wells centered on delivering operationally simple and reliable multilateral completion designs to economically meet the field development strategy in place.
To the knowledge of the authors and following subsequent literature research, both wells are a worldwide first for an offshore multilateral well completed with multistage acid fracturing and multistage proppant fracturing, and together they represent a new trend in cost-effective offshore field development through well stimulation. The successful case studies for both wells with the combined analysis of the benefits, challenges, and lessons learned will provide a guide and instill confidence with operators who find this approach beneficial with a view to applying it in other assets.
Jackson, A. C. (Chevron Corporation) | Dean, R. M. (Chevron Corporation) | Lyon, J. (Chevron Corporation) | Dwarakanath, V. (Chevron Corporation) | Alexis, D. (Chevron Corporation) | Poulsen, A. (Chevron Corporation) | Espinosa, D. (Chevron Corporation)
Reservoir management for an economically successful chemical EOR project involves maintaining high injectivity to improve processing rates. In the Captain Field, horizontal injection wells offshore have been stimulated with surfactant-polymer fluids to reduce surrounding oil saturations and boost water relative permeability. The surfactant-polymer stimulation process described herein enables a step change in injectivity and advances the commercialization of this application. This paper explains the damage mechanism, laboratory chemical design, quality control through offshore field execution and data quantifying the results.
Phase behaviour laboratory experiments and analytical injectivity models are used to design a near wellbore clean-up and relative permeability improvement. Three field trials were conducted in wells that had observed significant injectivity decline over 1-3 years of polymer injection. Surfactant and polymer are blended with injection water and fluid quality is confirmed at the wellheads. Pressure is continuously monitored with injectivity index to determine the chemical efficiency and treatment longevity. Oil saturation changes and outflow profile distributions are analysed from well logs run before and after stimulating. Learnings are applied to refine the process for future well treatments.
The key execution elements include using polymer to provide adequate mobility control at high relative permeability and ensure contact along the entire wellbore. Repeatability of success with surfactant-polymer injection is demonstrated with decreased skin in all the wells. The key results include the oil saturation logs that prove the reduction of oil near the well completion and improves the relative permeability to aqueous phase. The results also prove to be sustainable over months of post-stimulation operation data with high injectivity.
Injectivity enhancement was supported by chemical quality control through the whole process. From laboratory to the field (from core flood experiments to dissolution of trapped oil near wellbore), surveillance measurements prove that the chemical design was maintained and executed successfully. The enhanced injectivity during clean-up allows for higher processing rate during polymer injection and negates the need for additional wells.
The application of surfactant-polymer technology can rejuvenate existing wells and avoid high costs associated with redrilling offshore wells. This improves processing rate for EOR methods and can even be applied to waterflood wells to improve the injectivity, e.g low permeability reservoirs.
The Health and Safety Executive's analysis shows poor hazard identification and risk analysis is a causal factor in 12 out of 14 recent major hydrocarbon releases, demonstrating that major accidents could be prevented if workers had a better understanding of major accident hazards (MAHs). Therefore, it is proposed that improving awareness of MAHs across the workforce, both onshore and offshore, would lead to better MAH management and a reduction in major accidents.
Once the domain of process engineers, major accident hazard management has been largely overlooked by much of industry. It was acknowledged as a problem but ignored in the hope that specialists had it under control.
Step Change in Safety's Major Accident Hazard Understanding workgroup responded to this by identifying different job roles (onshore and offshore), evaluating the resources to develop MAH understanding already available and creating a suite of resources to fill the gaps.
These resources include an e-learning tool for onshore (office-based) personnel, bowtie lunch and learn sessions, gap analysis tools to identify training requirements of offshore jobs, senior leaders' workshops and a MAH Awareness programme. The MAH Awareness programme, consisting of short films and presentations which can be customised to suit specific worksites and job roles. Each of the four packs explores different aspects of major accident management including MAH identification and analysis, bowties and safety and environmental critical elements, barrier maintenance, assurance and verification and the importance of taking responsibility of ‘owning’ your barrier.
Analysis of questionnaires completed before and after exposure to the programme demonstrates that knowledge of MAH management increased by approximately 30%. Additionally, the data demonstrates that elected safety representatives have a greater base knowledge of MAHs than the general offshore workforce, as do technical staff compared to non-technical and those employed by operators compared to contractor employees.
Whether this increased knowledge gained through taking part in the MAH Awareness programme is retained or impacts the number of major accidents has not yet been analysed but data such as the number of major accidents, including hydrocarbon releases, will be examined over forthcoming years to evaluate the effectiveness of the resources developed.