Learn more about training courses being offered. Learn more about training courses being offered. This course covers the fundamental principles concerning how hydraulic fracturing treatments can be used to stimulate oil and gas wells. It includes discussions on how to select wells for stimulation, what controls fracture propagation, fracture width, etc., how to develop data sets, and how to calculate fracture dimensions. The course also covers information concerning fracturing fluids, propping agents, and how to design and pump successful fracturing treatments. Learn more about training courses being offered. Current and future SPE Section and Student Chapter leaders are invited to engage and share. Every attendee leaves energised with a full list of ideas and a support network of fellow leaders. Those sections and student chapters actively participating in this workshop have consistently been recognized with awards as the best in SPE. SPE Cares is a global volunteering drive aimed at promoting, supporting and participating in community services at the SPE section and student chapter’s level. On its official launch this year at ATCE Dubai, SPE Cares will conduct a “Give a Ghaf” Tree Planting Programme to help preserve Ghaf’s cultural and ecological heritage. The Ghaf tree is an indigenous species, specific to UAE, Oman and Saudi Arabia. It is a drought tolerant, evergreen tree that can survive a harsh desert environment. The initiative not only aims to hold events/activities at ATCE, but also recognise community service that SPE members are already conducting in their respective student chapters and professional sections. The KEY Club, open daily, is an exclusive lounge for key SPE members. The lounge is open to those with 25 years or more of continuous membership, Century Club members, current and former SPE Board officers and directors, Honorary and Distinguished Members, as well as this year’s SPE International Award Winners and Distinguished Lecturers. DSATS (SPE’s Drilling Systems Automation Technical Section) will hold a half-day symposium featuring keynote presentations on urban automation. This symposium will explore technologies being used in developing smart cities through the automation of their infrastructure, transportation systems, energy distribution, water systems, street lighting, refuse collection, etc. These efforts rely on many of the same tools needed for drilling systems automation yielding increased efficiencies, lower maintenance and reduced emissions. Their knowledge and experience can guide the path being travelled by the oilfield drilling industry.
The Alvheim field, offshore Norway, has subsea wells with long horizontal branches completed with sand screens. After 10 years of production, water production starts to constrain the oil production. Mechanical water shut-off is impossible in these wells, hence other methods are of interest. In a well workover in 2013, two high-viscous polymer pills were bull-headed and squeezed into the reservoir. The well productivity was reduced with around 50% while the water-cut dropped and pointed to potentially 3 mmstb of extra oil recovery. A research study was initiated with the objectives to understand the changed well performance and if polymer bull-heading can be a future method to reduce water production and enhance oil production.
An experimental laboratory program started with filtration tests of polymer solutions based on the polymer used in the well operation. Core flood experiments were performed by injecting polymer into two parallel mounted cores, then back producing these individually with either water or oil. Several combinations of parallel cores were tested with polymer injection: high vs. low permeability, high oil saturation vs. low oil saturation, outcrop sandstone vs. Alvheim core, as well as two different polymer versions.
The polymer recipe as used in the well operation showed to plug standard filters with filter size larger than the reservoir pore sizes but did not plug the cores. The polymer recipe as used in the well gave a better disproportionate permeability reduction (DPR) than the alternative polymer variant with similar viscosity. A theoretical model for the shear rate in the porous media matched the experimental measured data excellent. The core results show a stable permeability reduction factor of 100-450 for water, while only a factor 2-10 and decreasing with time for oil. The achieved DPR ratio of 45-80 is better than the trend from earlier published results.
The DPR as measured in the laboratory was next integrated in the reservoir model as part of the history match of the treated well. The Alvheim field has several reservoir zones separated with thin shales, and this reservoir zonation seems key for this EOR method to work.
The laboratory work, the reservoir studies and the field experience all point to a possible robust and simple EOR method for Alvheim and similar oil fields. The polymer seems to act as a "magic filter", allowing oil to pass while not water. Future work includes more research and maturing a new polymer pilot on Alvheim.
Kåre Langaas and Emile J. W. G. Jeurissen, Aker BP ASA, and Hailu Kebede Abay, Resman A/S Summary In this paper we describe the analysis, test, and design work to deliver an optimal lower completion for a trilateral well by integrating passive and autonomous inflow-control devices (ICDs) (AICDs) at the Alvheim Field offshore Norway. In 2015, both passive ICDs and AICDs were tested in the laboratory with Alvheim fluids at reservoir conditions. The experimental flow testing demonstrated that the AICD chokes gas more efficiently than the passive ICD. The experimental results enabled correct modeling of AICDs in both the reservoir-simulation model and the simpler steady-state inflow model. The following lower-completion strategy was established for the new well: Where the well was close to the overlying gas cap, AICDs should be used, whereas passive ICDs with variable strength were to be used elsewhere to optimize the inflow. During the drilling phase, the steady-state model was updated with the as-drilled information; the lower-completion design for each branch focused on obtaining what was estimated to be an optimal inflow depending on the oil volume per drainage area. A key uncertainty in the design work was whether shaly zones along the wellbore would creep/collapse with time and act effectively as packers. The lower completion covered 7 km of reservoir penetration in the three branches, and 15 unique oil tracers were installed to evaluate the cleanup and the inflow profile along the well. In August 2016, a restart-tracer-sampling campaign was performed after a 12-day shut-in, and this formed the basis for a "chemical production log." The tracer-based inflow interpretation was compared quantitatively with the model-predicted inflow and qualitatively to the tracer responses seen during the cleanup. The comparison confirmed that the lower completion works as initially planned. The interpretation further indicated that the upper zone has a lower degree of pressure support than the lower zone, and that the larger shaly sections have creeped/collapsed and act as packers.
A dual lateral horizontal well was drilled on the Kneler structure of the Alvheim Field (offshore Norway) in 2015. The use of a newly processed 4D seismic dataset changed the original planned target for the main branch and led to justifying drilling the branch below an existing producer. The objective of the main branch was to target undrained oil below a stratigraphically compartmentalized segment. The Alvheim Field started production in 2008. The baseline seismic survey was acquired in 1996 and a 4D monitor survey was acquired in 2013. The 4D seismic data was used to estimate the movement of the oil water contact, and 4D difference geobodies were benchmarked against production data directly, giving high confidence in the estimates. The 4D difference geobodies were integrated in the history matching process. A lower zone infill target below an existing upper zone producer was identified as the result of the multidisciplinary data integration. The lower zone has excellent pressure support via the large Heimdal aquifer system while the upper zone producer has limited pressure support and has historically produced at low rates. Pre-drill reservoir simulation studies indicated a benefit in enabling cross-flow between the two zones. The drilling results showed oil as predicted by the 4D seismic data. However, the upper zone was thicker than expected. A thin oil column was found in the lower zone before drilling into water, again confirming the 4D seismic interpretation. As the lower zone target was smaller than expected, the main value of the branch was refocused towards enabling optimal cross-flow. The pre-drill reservoir models were updated pragmatically and studies were done to optimize the lower completion, e.g. deciding the optimal cross-flow rate, production and injection intervals and how to use inflow control devices to assist the clean-up of all zones. The clean-up went as planned in November 2015 and a 20 bar drawdown was achieved across the injection interval of the branch. The branch was produced for 40 days before shut-in to act as a cross-flow injector. Pressure interference data indicated a successful clean-up of the injection interval. The cross flow well has showed to work as intended giving an increased oil rate of around 4000 stb/d. A cross-flow injector can be a cost effective solution for partly segmented compartments close to strong aquifers. To the knowledge of the authors, no example of this type of cross-flow injection has been documented in the literature.
Coupled, full-field, integrated, holistic, or asset: Call it what you will, this class of modeling is becoming increasingly commonplace. The ability to interrogate the response of a system, from the reservoir to fiscal meter, is quite potent and encourages integration in all senses of the word—technically, operationally, and organizationally. Such end-to-end models may reveal bottlenecks, constraints, and potential flow-assurance issues. While the benefits are manifest, two related issues are worthy of consideration: complexity and piloting. The complexity of any individual component (such as the reservoir model) refers to the engineering judgment required to ensure that it is fit for purpose.
Coupled, full-field, integrated, holistic, or asset: Call it what you will, this class of modeling is becoming increasingly commonplace. The ability to interrogate the response of a system, from the reservoir to fiscal meter, is quite potent and encourages integration in all senses of the word—technically, operationally, and organizationally. Such end-to-end models may reveal bottlenecks, constraints, and potential flow-assurance issues.
While the benefits are manifest, two related issues are worthy of consideration: complexity and piloting. The complexity of any individual component (such as the reservoir model) refers to the engineering judgment required to ensure that it is fit for purpose. For example, should one use a simple model (computationally rapid but approximate) or should a more complex model (computationally slower but accurate) be adopted? The former is better suited for rapid scenario screening and sensitivity analysis, while the latter is better suited for detailed engineering, with a spectrum of models in between.
Piloting is another consideration. The degree of technical insight required to competently steer any single component simulator is often quite high. Having several simulators under a single, seamless platform places an extra burden on the pilots involved because the added layer of software (the integration platform) may mask possible shortcomings in a model, thus rendering potentially incorrect results and even suboptimal capital decisions.
These considerations notwithstanding, I am genuinely optimistic about the potential these full-field models will bring and the insights they can deliver. More articles are certain to appear detailing predictions vs. observations and how planning, operations, and economics benefited from such integrated studies. I respectfully submit that the story of fully coupled, full-field, integrated asset modeling has only just begun. JPT
The Alvheim field is located offshore Norway, with a small portion extending into the UK sector. The field is composed of several low relief hydrocarbon accumulations within the Palaeocene Heimdal Formation. Production started in 2008. Recently, a new integrated reservoir model of the Alvheim field was built with the following key objectives: Integrate all known data/constraints, simplify where reasonable, and establish workflows for continuous maintenance/improvement.
The Alvheim field includes thin oil rim reservoirs with horizontal wells. The oil-water contact is varying, partly explained by aquifer depletion from nearby fields. Smaller sector models were constructed to test different alternatives for grid selection, saturation modelling, upscaling methods, initialisation methodology, aquifer modelling and lower completion (inflow control devices) modelling. The dynamic full field model is the main tool for production forecasting and should include all relevant constraints and optimisation aspects. The possibility to use active controls to honour the FPSO unit's swivel velocity constraints and to optimise gas lift were investigated. The studies showed that an orthogonal block centred grid was best for the dynamic full field model, giving a good representation of the horizontal wells and a very computationally efficient model. The static model grid was chosen to best honour the geological concepts and to be applicable in dynamic sector model studies. The varying hydrocarbon contacts were gridded as part of the saturation modelling in the static model and included in the upscaling to the full field dynamic model. Studies showed that the Heimdal aquifer model could be simplified and that the dynamic model could be initialised in 2008. The inflow control devices were found to impact the history match and have been implemented as part of the dynamic model. The active controls implemented in the dynamic full field model have simplified the forecast setup and has the ability to improve the forecast quality and the production optimisation. The new Alvheim model has proved to work well, and the established work flows are used for continuous model improvement.
Simulation to Seismic (Sim2Seis) is a forward modeling technique used to predict/generate synthetic seismic response from a static or dynamic reservoir model. There are two key components of a Sim2Seis workflow: reservoir model (geological and/or simulation model) and petro-elastic models (PEMs). PEMs are rock physics functions which relate reservoir properties such as rock types, porosity and fluid saturation to the elastic properties such as compressional and shear velocities, and density. Predicted elastic properties are used to compute reflection coefficients, when convolved with a wavelet generate a synthetic seismic volume (1D or 3D).
There are several applications for Sim2Seis in reservoir characterization. It can be applied to test the consistency of a 3D geological static model, or of a history-matched simulation (dynamic) model with the actual seismic data. It can also be applied to study the impact of saturation change on seismic response (4D effect). A case study from an oil producing Tertiary age field in the North Sea was used to illustrate the applications of Sim2Seis workflow. This case study reveals the value of integrating the static and dynamic data for more accurate reservoir characterization, and consequently building a more reliable reservoir flow model which honors petrophysical and seismic data as well as production data.
The Alvheim Field is comprised of several hydrocarbon accumulations, known as Kameleon, East Kameleon, Boa, and Kneler which are located in Norwegian North Sea blocks 24/6 and 25/4 (Fig. 1), bordering the United Kingdom. Alvheim is located in the central part of Viking Graben where deepwater deposits of the Paleocene and Eocene (known as the Rogaland Group) have been the main exploration targets (Fig. 2). The main sediments present in the Rogaland Group (Fig. 3) are siliciclastics with minor coal, tuff, volcaniclastics, marls and reworked carbonate sediments which were sourced from the East Sheldland Platform. Coarser sediments were reworked and redeposited during three major episodes of sea level fall in this period (Brunstad et al., 2009). The main coarse clastic units of the Rogaland Group are Ty, Heimdal and Hermond Sandstones interbedded with Lista and Sele Shales. All producing fields within Alvheim are producing from the Palaeocene Heimdal Sand Member of the Lista Formation.
Development of offshore fields at an early stage is connected with significant uncertainties and risks because of poor knowledge of reservoirs characteristics and the low reliability of hydrocarbon reserves. In this paper we present the methodology to assess the possibility to start offshore fields development in condition of limited geological information. The methodology is implemented as a workflow, the result of which is the conclusion about: types of production units, number of wells and their placement boundaries, required minimum reserves density to begin field development, as well as types of exploration work on fields. The application of the methodology and workflow are demonstrated on the examples of assessment of the potential of development of some Russian arctic offshore fields.