Prudhoe Bay Field Study - Return Fluid Analysis

A high level screening has been performed of UKCS oil fields to identify the most likely LSWF candidates utilising screening criteria with a focus on kaolinite clay content. The screening results suggest that approximately 57% of the fields have 6 % or higher kaolinite clay content. Of these fields 26 % were water-wet and 74 % were mixed-wet in terms of wettability. This suggests that a significant number of fields would fall within the eligibility for consideration of LSWF EOR although their suitability will depend on field maturity (current recovery factor and facilities constraints). The difficulty in applying LSWF in tertiary mode unlike secondary mode, is in obtaining a reasonable prediction of how the reservoir is likely to respond. The question of core availability and quality has been raised in a number of studies in terms of LSWF and electrical property testing. We propose a methodology which can be applied to compensate for the lack of usable core based on petrophysical log response. The logs can be utilised to determine the clay types present (including fractions) from which the cation exchange capacity can be calculated. Selected compositions from anonymised field data from core was used to provide quality control the log derived values. The most likely recovery mechanism, multi-component ion exchange (MIE), requires the input of key electrical properties into the models (cation exchange capacity, reactive surface area, activation energy and mineral fraction) in order to predict the response of the reservoir to LSWF. In this study the effect of clay content on the reservoir response was modelled indirectly by altering the cation exchange capacity relative to the clay mineral fraction present in the reservoir to determine its effect. Utilising a mechanistic modelling approach, homogeneous Cartesian models were run in the compositional finite difference reservoir simulator GEM to assess the impact on oil recovery. The simulated coreflood tests reveal that under secondary LSWF recovery was 68.4 % compared to 63.6 % for formation water (high salinity). The conservative nature of the relative permeability curves limited the incremental recovery. An analysis of the tertiary recovery utilising a coreflood based on Fjelde et al. (2012) revealed that cation exchange impacts the predicted recovery by up to 2.65 % OOIP for the range of 5 - 30 % clay content. Given that the recovery under tertiary conditions is considered in the literature to be between 6 and 12 %, this is significant and highlights that if idealised data is selected rather than real field data, then significant potential exists to under or over-predict the incremental recovery.

show abstract

Integrated Modeling for Assisted History Matching and Production Forecasting of Low Salinity Waterflooding

Dang¹,

Nghiem²,

Nguyen

et al. 2016

SPE Europec Featured at 78th EAGE Conference and Exhibition

View full text Add to dashboard Cite

Summary From a technical point of view, the success or failure of LSW (low salinity waterflooding) projects strongly depends on reservoir geology; however, this has not been systematically evaluated in the past and the effects of clay minerals are often neglected in conventional reservoir simulation. This paper presents one of the first studies on integrated modeling, assisted history matching (HM) and production forecasting of field-scale LSW. To handle this complex recovery process, we used a comprehensive ion-exchange model, fully coupled with geochemistry specially designed for the modeling of LSW physical phenomena in an EOS reservoir simulator. The model is capable of accounting for the critical role of the properties, quantity, and distributions of clay minerals. We developed an integrated modeling approach that involves the combination of geological software, a reservoir simulator, and a robust optimizer in a big-loop workflow for sensitivity analysis, HM, optimization, and uncertainty assessment. The numerical simulation results indicate that LSW's performance depends critically on the reservoir geological characteristics. Multiple geological realizations can be automatically generated from the big-loop approach that are needed for fast and accurate HM and optimization of LSW. In sandstone reservoirs, clay content varies across regions, resulting in differences in ion-exchange capacity and weights of the relative permeability modification. We introduce the scaled-equivalent-fraction ion exchange which is associated with the calculated Cation-Exchange-Capacity function; the wettability alteration will be shifted based on both the ion exchange and the clay content in each grid block. The key parameters for successful field-scale LSW HM include: clay distribution/quantity associated with different facies, relative permeability modification, wettability alteration thresholds, reservoir minerals, geochemical reactions, and operating conditions. Finally, LSW HM by tuning reservoir parameters only may lead to poor prediction results, while the integrated modeling approach provides much better forecasting results to the true history data. The work presented in this paper contributes to an understanding of the critical roles of reservoir geology on the field-scale LSW performance, in particular, for substantially reducing HM errors, accurately predicting the future production, maximizing oil recovery and minimizing the risks of LSW implementation.

show abstract

Prudhoe Bay Field Study - Return Fluid Analysis

Cited by 5 publications

References 20 publications

A framework for assisted history matching and robust optimization of low salinity waterflooding under geological uncertainties

A framework for assisted history matching and robust optimization of low salinity waterflooding under geological uncertainties

Influence of Clay Content and Type on Oil Recovery Under Low Salinity Waterflooding in North Sea Reservoirs

Integrated Modeling for Assisted History Matching and Production Forecasting of Low Salinity Waterflooding

Contact Info

Product

Resources

About