The oil & gas industry uses production forecasts to make a number of decisions as mundane as whether to change the choke setting on a well, or as significant as whether to develop a field. As these forecasts are being used to develop cashflow predictions and value and decision metrics such as Net Present Value and Internal Rate of Return, their quality is essential for making good decision. Thus, forecasting skills are important for value creation and we should keep track of whether production forecasts are accurate and free from bias.
In this paper we compare probabilistic production forecasts at the time of the development FID with the actual annual production to assess whether the forecasts are biased; i.e., either optimistic, overconfident, or both.
While biases in time and cost estimates in the exploration & production industry are well documented, probabilistic production forecasts have yet to be the focus of a major study. The main reason for this is that production forecasts for exploration & production development projects are not publicly available. Without access to such estimates, the quality of the forecasts cannot be evaluated.
Drawing on the Norwegian Petroleum Directorates (NPD) extensive database, annual production forecasts, given at time of project sanction (FID), for 56 fields in the 1995 – 2017 period, have been compared with actual annual production from the same fields. The NPD guidelines specify that the operators should report the annual mean and P10/90-percentiles for the projected life of the field at the time of the FID; that is, the forecasts should be probabilistic. The actual annual production from the fields was statistically compared with the forecast to investigate if the forecasts were biased and to assess the financial impact of such biases.
This paper presents the results from the first public study of the quality of probabilistic production forecasts. The main conclusions are that production forecasts that are being used at the FID for E&P development projects are both optimistic and overconfident. As production forecasts form the basis for the main investment decision in the life of a field, biased forecasts will lead to poor decisions and to loss of value.
Saasen, Arild (University of Stavanger) | Pallin, Jan Egil (JAGTECH AS) | Ånesbug, Geir Olav (JAGTECH AS) | Lindgren, Alf Magne (Schlumberger Oilfield Services) | Aaker, Gudmund (Schlumberger Oilfield Services) | Rødsjø, Mads (AkerBP)
Different logging operations can suffer from presence of metallic particles in the drilling fluids. Directional drilling in Arctic areas can be a challenge because of magnetic contamination in the drilling fluid. This is a challenge especially when drilling east-west relative to the magnetic north direction. Magnetic and paramagnetic particles in the drilling fluid will shield the down hole compasses and introduce additional errors to the surveying than those normally included in the uncertainty ellipsoid. The objective of the project is to remove the magnetic particles being the largest contributor to this error.
On many offshore drilling rigs there is mounted ditch magnets to remove metallic swarf from the drilling fluid. These magnets will normally only remove the coarser swarf. In this project we use a combination of strong magnets and flow directors to significantly improve the performance of the ditch magnets. This combination, together with proper routines for cleaning the ditch magnets significantly helps cleaning the drilling fluid.
By the combined use of flow directors and ditch magnets it was possible to extract more than five times as much magnetic contamination from the drilling fluid. This is verified by comparing the ditch magnet efficiencies from two drilling rigs drilling ERD wells. The logging tool signal strengths of several down hole instruments were unusually good and insignificant down times were observed on the logging tools. The results are anticipated to have aided to the directional drilling performance.
Detailed information on how to clean the drilling fluid properly from magnetic contamination is presented. It is also shown that this cleaning is significantly better than conventional cleaning of magnetic debris from drilling fluids.
Geophysical Reservoir Monitoring GRM systems such 4D seismic are increasingly used in the oil and gas industry because they provide unique and useful information on fluid movement within the reservoir. This information is relevant for many reservoir management decisions; including new well placement, well intervention, and reservoir model updating.
Unfortunately, it has been difficult to estimate the value creation of any data acquisition scheme due to the fact that a multidisciplinary approach is required to model the value that future measurements will imply in future decisions. This assessment requires a common decision making simulation frame work that can integrate the input from geo-modelers, geophysicist and reservoir engineers.
This work presents an example of how a Close Loop Reservoir Management (CLRM) simplification can be used as a framework for simulating NPV changes due to assimilation of production and saturations in a simple toy model. It combines state-of-the-art data assimilation and uncertainty modeling methods with a robust optimization genetic algorithm to calculate NPV improvements due to model update and its relationship with the NPV obtained from the synthetic reservoir.
In this context a simple synthetic model is presented. It recreates a segment of green field under a strong aquifer influence with two discovery wells. The reservoir development requires the selection of 4 well locations at fixed drilling times. The development strategy selection is obtained with the use of a genetic algorithm within the CLRM framework. Subsequently two cases are presented: one of assimilating only production after the first two wells have been drilled, just before deciding the locations of the last two wells; and a second case, in which production and saturation are assimilated at the same time. The saturation map assimilated is assumed to be output of a 4D seismic acquisition. The model update imposes the need of optimally relocate the last two wells which results in a NPV change.
The results show how the obtained NPVs is incremented by the relocation of the last two wells in both cases. A bigger increment is obtained when both, production and saturation are assimilated. In addition, the ensemble improved its forecast capability the most, when saturation assimilation is included. Nevertheless, the ensemble expected NPV decreases after assimilation from the value obtained from the first development strategy optimization; this indicates an optimistic early NPV valuation due to the initial ensemble distributions spread.
The study presents an asset simulation framework that could be used to evaluate data acquisition investments through the systematic modeling of reservoir uncertainties with in a decision oriented focus. This could include the inclusion of additional uncertain model parameters, the insertion of water injector and well conversions, the assimilation of saturations at different intervals, the change on the quality of the saturation maps assimilated, in addition to sensitivity studies of other economic constrains.
Alcorn, Zachary P. (University of Bergen) | Fredriksen, Sunniva B. (University of Bergen) | Sharma, Mohan (University of Stavanger) | Rognmo, Arthur U. (University of Bergen) | Føyen, Tore L. (University of Bergen and SINTEF Industry) | Fernø, Martin A. (University of Bergen) | Graue, Arne (University of Bergen)
A carbon-dioxide (CO2) -foam enhanced-oil-recovery (EOR) field pilot research program has been started to advance the technology of CO2 foam for mobility control in a heterogeneous carbonate reservoir. Increased oil recovery with associated anthropogenic-CO2 storage is a promising technology for mitigating global warming as part of carbon capture, utilization, and storage (CCUS). Previous field tests with CO2 foam report various results because of injectivity problems and the difficulty of attributing fluid displacement specifically to CO2 foam. Thus, a comprehensive integrated multiscale methodology is required for project design to better link laboratory- and field-scale displacement mechanisms. This study presents an integrated upscaling approach for designing a miscible CO2-foam field trial, including pilot-well-selection criteria and laboratory corefloods combined with reservoir-scale simulation to offer recommendations for the injection of alternating slugs of surfactant solution and CO2, or surfactant-alternating-gas (SAG) injection, while assessing CO2-storage potential.
Laboratory investigations include dynamic aging, foam-stability scans, CO2-foam EOR corefloods with associated CO2 storage, and unsteady-state CO2/water endpoint relative permeability measurements. Tertiary CO2-foam EOR corefloods at oil-wet conditions result in a total recovery factor of 80% of original oil in place (OOIP), with an incremental recovery of 30% of OOIP by CO2 foam after waterflooding. Stable CO2 foam, using aqueous surfactants with a gas fraction of 0.70, provided mobility-reduction factors (MRFs) up to 340 compared with pure-CO2 injection at reservoir conditions. Oil recovery, gas-mobility reduction, producing-gas/oil ratio (GOR), and CO2 utilization at field pilot scale were investigated with a validated numerical model. Simulation studies show the effectiveness of foam to reduce gas mobility, improve CO2 utilization, and decrease GOR.
Andersen, Pål Østebø (University of Stavanger) | Lohne, Arild (International Research Institute of Stavanger) | Stavland, Arne (International Research Institute of Stavanger) | Hiorth, Aksel (University of Stavanger) | Brattekås, Bergit (University of Bergen)
Capillary spontaneous imbibition (SI) of solvent (water bound in gel) from formed polymer gel into an adjacent, oil-saturated porous medium was recently observed in laboratory experiments. Loss of water from the gel by SI might influence the blocking capacity of the gel residing in a fracture, by decreasing its volume, and might contribute to gel failure, often observed in water-wet oil fields.
This work presents an original modeling approach to simulate and interpret spontaneous imbibition of water from Cr(III)-acetatehydrolyzed-polyacrylamide (HPAM) gel into adjacent oil-saturated rock matrix. Simulations were compared to experiments on the core scale, using two different boundary conditions: all faces open (AFO) and two-ends-open free spontaneous imbibition (TEOFSI). Capillary forces enable water (used as gel solvent) to enter the rock matrix. The gel particle network itself is, however, inhibited from entering because of its structure, and remains on the surface of the rock matrix. We developed a theory that describes the gel as a compressible porous medium and describes the flow of water through gel. The polymer structure of the gel is proposed to constitute a gel matrix of constant solid volume. Gel porosity, defined by the volume fraction of solvent, is modeled as a function of pore pressure and gel compressibility. Gel permeability is modeled as function of gel porosity using a Kozeny-Carman approach. The flow equations for the gel and core domains were solved simultaneously by implementing the proposed description into the core-scale simulator IORCoreSim. The gel surrounding the core was discretized and included as a part of the total grid.
The simulated flow of water through and from the gel occurred in a transient manner, driven by the coupled gradients in gel fluid pressure and gel porosity. Gel porosity initially decreased in a layer close to the core surface because of reduced aqueous pressure, and continued to decrease in layers away from the core surface. The propagation rate was controlled by two main gel parameters: First, gel compressibility controlled the pressure gradient within the gel network, and the amount of water transported from the outer part of the gel toward the core surface to balance the pore pressure; and, second, gel permeability limited how fast water could flow within the gel at a given pressure gradient, thus increasing the time scale of the overall imbibition process.
This paper presents a numerical study of water displacing oil using combined cocurrent/countercurrent spontaneous imbibition (SI) of water displacing oil from a water-wet matrix block exposed to water on one side and oil on the other. Countercurrent flows can induce a stronger viscous coupling than during cocurrent flows, leading to deceleration of the phases. Even as water displaces oil cocurrently, the saturation gradient in the block induces countercurrent capillary diffusion. The extent of countercurrent flow may dominate the domain of the matrix block near the water-exposed surfaces while cocurrent imbibition may dominate the domain near the oil-exposed surfaces, implying that one unique effective relative permeability curve for each phase does not adequately represent the system. Because relative permeabilities are routinely measured cocurrently, it is an open question whether the imbibition rates in the reservoir (depending on a variety of flow regimes and parameters) will in fact be correctly predicted. We present a generalized model of two-phase flow dependent on momentum equations from mixture theory that can account dynamically for viscous coupling between the phases and the porous media because of fluid/rock interaction (friction) and fluid/fluid interaction (drag). These momentum equations effectively replace and generalize Darcy’s law. The model is parameterized using experimental data from the literature.
We consider a water-wet matrix block in one dimension that is exposed to oil on one side and water on the other side. This setup favors cocurrent SI. We also account for the fact that oil produced countercurrently into water must overcome the so-called capillary backpressure, which represents a resistance for oil to be produced as droplets. This parameter can thus influence the extent of countercurrent production and hence viscous coupling. This complex mixture of flow regimes implies that it is not straightforward to model the system by a single set of relative permeabilities, but rather relies on a generalized momentum-equation model that couples the two phases. In particular, directly applying cocurrently measured relative permeability curves gives significantly different predictions than the generalized model. It is seen that at high water/oil-mobility ratios, viscous coupling can lower the imbibition rate and shift the production from less countercurrent to more cocurrent compared with conventional modeling. Although the viscous-coupling effects are triggered by countercurrent flow, reducing or eliminating countercurrent production by means of the capillary backpressure does not eliminate the effects of viscous coupling that take place inside the core, which effectively lower the mobility of the system. It was further seen that viscous coupling can increase the remaining oil saturation in standard cocurrent-imbibition setups.
Remya Ravindran Nair, Evgenia Protasova, Torleiv Bilstad, and Skule Strand, University of Stavanger Summary This research focuses on membrane-separation efficiencies by adjusting the ionic composition of deoiled produced water (PW) and evaluates the possibility for smartwater production from PW for enhanced oil recovery (EOR) in carbonate reservoirs. Key characteristics of smartwater for carbonate reservoirs are increased concentrations of divalent ions and low concentrations of monovalent ions compared with seawater. In this research, PW was pretreated with media filters, which resulted in 96 to 98% oil removal. This deoiled PW was used as feed for nanofiltration (NF) membranes. NF-membrane performance was evaluated in terms of flux and the separation efficiencies of the key scaling ions calcium (Ca) and barium (Ba). No membrane fouling was observed during the experiments. The results showed no Ca dissolution, which could affect chalk-reservoir compaction. A process scheme is proposed for smartwater production by ionic selection from seawater and PW at an operating pressure of 18 bar. Energy-consumption analysis for smartwater production before membrane treatment concluded NF to be economic over other desalination technologies. The power consumed by NF membranes for smartwater production at 18 bar is calculated at 0.88 kWh/m Introduction PW is one of the major waste streams from the oil and gas industry and should be managed in an environmentally sustainable manner. PW treatment is concerned with contaminants such as solids and residual oil, together with production chemicals (Fink 2012). The current water/oil ratio (WOR) in oil production is 2:1 to 3:1 worldwide. Onshore-treatment costs of PW from the North Sea differ from 0.19 to 3.40 USD/bbl of PW (Duhon 2012).
Gudmestad, Ove Tobias (University of Stavanger)
In this paper, we define sustainability as the requirement to manage the available resources such that our average quality of life can be shared by future generations. For this definition to make sense, we must define the qualities of life that are important to us—these are the safety of personnel involved in an activity, the clean, nonpolluted environment, and the safe use of assets for owners and investors; this also includes management of resources and safe operations. The sustainability requirement raises challenges for investments and developments. We must apply technology that is safe to use and that ensures that the environment, in a broad sense, is maintained in a way in which renewable resources are not depleted or damaged by pollution. The sustainable use of the Arctic seas is particularly challenging, as pollution is considered to be more persistent in the Arctic environment than in more temperate areas. Most of the examples in the paper will be taken from the Barents Sea, although general aspects are valid for all Arctic seas.
With increased environmental focus and sustainability, classical water-based EOR with surfactants or polymers meet larger implementation scepticism. This has increased the attention toward water-based EOR methods with low environmental impact and lower costs, such as Smart Water and alkaline flooding. Both methods are based on the establishment of alkaline conditions in the formation. Chemical interactions among the rock minerals, reservoir fluids, and injection brine can be reflected in the pH of the produced water. Thus, the scope of this work is to investigate the development and transportation of pH through porous media during 1) low salinity (LS) Smart Water flooding, and 2) alkaline LS (alk. LS) waterflooding.
Outcrop sandstone cores were used in core flooding experiments. Several pH-screening tests were performed to study the pH development during waterflooding. The ability of LS and alk. LS injection brines to increase the pH in sandstone core material with different mineralogy was compared, and the effect of pH on oil recovery was confirmed in an oil recovery test.
The results of the pH-screening tests by LS brine injection showed a potential for increasing the effluent LS water pH up to 2 units in comparison to its initial pH-value. The oil recovery test performed on the same core material showed almost 10% incremental oil recovery during LS flooding in secondary mode, in comparison with formation water (FW) flooding. pH-screening tests with alkaline LS brine injection showed low potential for extra alkalinity above that obtained by LS brine injection. Transportation of alkalinity through a mineral system with large surface area seemed to be challenging due to pH buffering from brine/mineral interactions as well as from chemical interactions involving inorganic cations from the formation water.
Based on the experimental results, ion exchanges between rock minerals and injected water can influence the reservoir pH and induce the wettability alteration. These chemical interactions can result in both development and consumption of alkalinity depending on the type of injected brine and chemical reactivity of the minerals. It was concluded that an in-situ generation of alkaline conditions at the waterfront seemed to have larger potential for EOR purposes than transferring the alkalinity of the injected brine through the reservoir.
Hanea, Remus (Equinor and University of Stavanger) | Casanova, Pierrick (Equinor) | Hustoft, Lars (Equinor) | Bratvold, Reidar (University of Stavanger) | Nair, Rohith (TNO) | Hewson, Christopher William (TNO) | Leeuwenburgh, Olwijn (TNO and Delft University of Technology) | Fonseca, Rahul-Mark (TNO)
The goal of reservoir management is to make decisions with the objective of maximizing the value creation from oil or gas production. To achieve this, models that preserve geological realism and have predictive capabilities are being developed and used. These models are commonly calibrated using assisted-history-matching (AHM) methods which, in general, will lead to reduced uncertainty in the predicted production. Although uncertainty assessment and reduction are often elements of high-quality decision making, they are not value-creating. Value can only be created through decisions, and any decision changes resulting from AHM should be modeled explicitly. Recently, there has been a surge in the application and understanding of value-of-information (VOI) work flows for reservoir management. In this text, we present a comparison of existing work flows and note the differences between them. After this, we introduce a practically driven approach, referred to as “drill and learn,” with elements and concepts from existing work flows to quantify the value of learning (VOL). VOL can be used as a metric to quantify the potential of such work flows and the strategies obtained. Ensemble methods [ensemble smoother with multiple data assimilation (ES-MDA) and stochastic simplex approximate gradient (StoSAG)] are used for the history matching and optimization. The results presented are obtained by applying the proposed drill-and-learn work flow on a realistic synthetic case. Sensitivities to the amount of information obtained before a closed-loop exercise is performed are also investigated. We show the benefit of performing the closed-loop approach to quantify the VOL to modify field-development decisions, which leads to a mature and robust decision-making framework.