The evidence from the produced-brine chemistry suggests that the Gyda field has experienced a variety of geochemical reactions caused by the high temperature and initial calcium (Ca) concentration, and so it is worth reviewing the produced-water data set and studying what in-situ geochemical reactions may be taking place.
Produced-brine-chemistry data from 16 wells in the Gyda field are plotted and analyzed in combination with general geological information and the reservoir description. A 1D reactive-transport model is developed to identify the possible geochemical reactions occurring within the reservoir triggered by seawater injection, and then extended with the inclusion of thermal modeling and also to be a 2D vertical-cross-section model.
Three possible classes of formation-water composition in different regions of the Gyda field have been identified by analysis of the produced-water data set. Anhydrite and barite precipitation are the two dominant mineral reactions taking place deep within the reservoir. Magnesium (Mg) stripping may be a result of multicomponent ion exchange (MIE), dolomite precipitation, or a combination of both. Reservoir temperature is lowered during coldwater injection. The solubility of anhydrite increases at lower temperature, and anhydrite will gradually dissolve in response to the movement of the temperature front, which is much slower than the formation/injection-water mixing front. The extent of mineral precipitation within the reservoir can be reduced by the heterogeneity; the modeling shows that the extent of ion stripping caused by mineral reactions in the reservoir is greatest when simulating a single uniform layer. Brine mixing and the occurrence of geochemical reactions caused by vertical mixing are not observable, even when assigning a high vertical permeability in a heterogeneous model.
Thermal modeling is included to evaluate the effect of nonisothermal processes and heat transport on the geochemical reactions, especially the anhydrite mineral reaction. We have investigated how the difference in horizontal permeability in the two layers affects brine mixing of formation and injection water and geochemical reactions.
In waterflooded reservoirs under active scale management produced water samples are routinely collected and analysed, yielding information on the evolving variations in chemical composition. These produced water chemical compositional data contain clues as to the fluid/fluid and fluid/rock interactions occurring in the subsurface, and are used to inform scale management programmes designed to minimise damage and enable improved recovery.
In this interdisciplinary paper, the analyses of produced water compositional data from the Miller Field are presented and a 1D reactive transport model is developed to study possible geochemical reactions taking place within the reservoir through matching model results with observed produced water data. However, in the 1D reactive transport model, only one flow path was simulated; this does not fully represent the fluid flow and mixing behaviour in the reservoir.
Therefore, this paper also presents a fully 3D reservoir simulation study for the Miller Field to evaluate brine flow and mixing processes occurring in the reservoir, using an available history matched streamline reservoir simulation model integrated with produced water chemical data. Conservative natural tracers were added into the modelled injection water, and then the displacement of injection water and the behaviours of the produced water in two given production wells were further studied. In addition, the connectivity between producers and injectors was investigated based on the comparison of production behaviour calculated by the reservoir model with produced water chemical data, and an assessment of the properties of the intervening faults was also performed. Finally, a model of BaSO4 scale precipitation was included in the model, and the simulation results with and without barite precipitation were compared with produced water chemical data (observed barium and sulphate concentrations in the produced brine). In general, the modelled and observed data were found to be in good agreement, but any discrepancies were in fact found to be very informative also. The model assumes scale deposition is possible everywhere in the formation, whereas in reality the near production well zones were generally protected by scale inhibitor squeeze treatments, and thus the discrepancies between modelled and observed data could be used to diagnose the effectiveness of the chemical treatments to prevent formation damage around the production wells.
Vazquez, O. (Heriot-Watt University) | Young, C. (Maersk Oil) | Demyanov, V. (Heriot Watt University) | Arnold, A. (Heriot Watt University) | Fisher, A. (Maersk Oil) | MacMillan, A. (Maersk Oil) | Christie, M. (Heriot Watt University)
Produced Water Chemistry data (PWC) is the main source of information to monitor scale precipitation in oil field
operations. Chloride concentration is used in order to evaluate the seawater fraction of the total produced water per producing
well and is included as an extra history matching constraint to revaluate a good conventionally history matched reservoir
model for the Janice field. Generally PWC is not included in conventional history matching and this approach shows the
value of considering the nature of the seawater injection front and the associated brine mixing between the distinctive
formation water and injected seawater.
Adding the extra constraint resulted in the re-conceptualization of the reservoir geology between a key injector and two
producers. The transmissibility of a shale layer is locally modified within a range of geologically consistent values. Also, a
major lineament is identified which is interpreted as a NW-SE trending fault, whereby the zero transmissibility of a
secondary shale in the Middle Fulmar is locally adjusted to allow cross-flow. Both uncertainties are consistent with the
complex faulting known to exist in the region of the targeted wells. Other uncertainties that were carried forward to the
assisted history matching phase included: water allocation to the major seawater injectors; thermal fracture orientation of
injectors and the vertical and horizontal permeability ratio (kv/kh) of the Fulmar formation.
Finally, a Stochastic Particle Swarm Optimization (PSO) algorithm is used to generate an ensemble of history matched
(HM) models using seawater fraction as an extra constraint in the misfit definition. Use of addition data in history matching
has improved the original good history matched solution. Field Oil Production Rate is interpreted as improved over a key
period and although no obvious improvement was observed in Field Water Production Rate, Seawater fraction in a number of
wells was improved.
Scale precipitation is a major flow assurance problem where minerals precipitate and further nucleate on surfaces such as
production tubing, reservoir pore or pore throats, perforation intervals and surface facilities. These deposits can inhibit well
inflow and outflow performance which may result in costly well interventions, downtime or ultimately abandonment. The
sampling of produced water chemistry and wellbore monitoring surveys can however aid oilfield scale detection and its
management (Carbone et al., 1999).
One of the most common occurring oilfield scales is sulphate minerals, which form due to the mixing of formation water
(rich in cations such as Ba, Sr, Mg, Ca) and injected seawater rich in sulphate ions. Predicting the location of the front and
hence sulphate mineral deposition is an intricate process; its prediction requires accurate modelling of the seawater and
formation water mixing front and associated breakthrough time. The use of produced water chemistry, due to their clear
distinctive chemistries, has been used for seawater fraction determination in a number of techniques, such as reacting ions
method (Ishkov et al., 2009) and Multivariate Analysis (Scheck and Ross, 2008). In this particular study, Chloride ion
concentration is considered as it is one of the most common methods used in the oil industry.
Vazquez, Oscar (Heriot-Watt University) | Young, Callum (Heriot Watt University) | Demyanovvasily, Vasily (Heriot Watt University) | Arnold, Dan (Heriot Watt University) | Fisher, Andrew (Maersk Oil) | MacMillan, Alasdair (Maersk Oil) | Christie, Mike (Heriot Watt University)
Inorganic scale precipitation and deposition in production wells can be a significant impediment to effective reservoir management. In extreme cases scale can cause the well to be abandoned as a result of reservoir formation damage in the near wellbore area and the narrowing of the production tubing annulus thus preventing fluid flow. The prediction of the time and location of scale formation is therefore essential for scale management. This study is focused on sulphate scales, which form when sulphate rich seawater mixes with formation brines, rich in barium, strontium and calcium, and which are amongst the most difficult types of scale to prevent and remove. Formation brines in reservoirs with a tendency for sulphate scale deposition can have a very different makeup when compared to seawater, which may be injected for pressure support. Having such different chemistries allows seawater and formation brine to be tracked. In this study, two different types of water are considered, formation brine and injected seawater.
The objective of this work is to predict uncertainty in sulphate scale deposition from multiple history matched reservoir models, by tracking injected seawater in the Janice Field. There are many examples in the literature where conventional reservoir history matching, namely gas rate, oil rate and bottom hole pressure, are used to generate an ensemble of good history matched models, which will determine the uncertainty of a hydrocarbon reservoir production forecast. In this study, the same approach will be adopted, but including produced water chemistry, in particular seawater breakthrough. This approach provides a methodology to predict the uncertainty of the formation brine and the injected seawater mixing zone within the reservoir formation. The methodology provides a Bayesian confidence interval (P10-P50-P90) in time and space for the injected seawater, identifying which wells will be at risk based on seawater breakthrough and in which zones of the reservoir mixing is more likely to occur.
Vazquez, Oscar (Heriot-Watt University) | Young, Callum (Maersk Oil North Sea UK Limited) | Demyanov, Vasily (Heriot-Watt University) | Arnold, Dan (Heriot-Watt University) | Fisher, Andrew (Maersk Oil North Sea Limited) | Macmillan, Alasdair (Maersk Oil North Sea UK Limited) | Christie, Michael (Heriot-Watt University)
Oscar Vazquez, SPE, Heriot-Watt University; Callum Young, SPE, Maersk Oil North Sea UK Limited; Vasily Demyanov, SPE, and Dan Arnold, SPE, Heriot-Watt University; Andrew Fisher, SPE, and Alasdair MacMillan, SPE, Maersk Oil North Sea UK Limited; and Mike Christie, SPE, Heriot-Watt University Summary Inorganic-scale precipitation and deposition in production wells can be a significant impediment to effective reservoir management. In extreme cases, scale can cause the well to be abandoned as a result of reservoir-formation damage in the near-wellbore region and the narrowing of the production-tubing annulus, thus preventing fluid flow. The prediction of the time and location of scale formation is therefore essential for scale management. This study is focused on sulfate scales, which form when sulfate-rich seawater mixes with formation brines that are rich in barium, calcium, and strontium, and which are among the most difficult types of scale to prevent and remove. Formation brines in reservoirs with a tendency for sulfatescale deposition can have a very different makeup when compared with seawater, which may be injected for pressure support. Having such different chemistries allows seawater and formation brine to be tracked.