This paper describe an application of combined experimental and digital technology workflow for field appraisal. It includes the description of heterogeneous low permeability X oil field located in the southeastern part of the Kurdistan Region of Iraq and its field development planning (FDP) challenges. An integrated laboratory study of low permeability carbonate reservoir rocks (dolomitic limestones) included a digital rock (DR) workflow that accelerated the time to complete core analysis program while bringing vital information about the pore-scale flow dynamics. The DR workflow combined high-resolution digital rock imaging, digital fluid models of reservoir brine and live oil samples, detailed wettability model for sample aging and boundary conditions in digital coreflood experiments. DR imaging spanned from micro-CT for meso- and micropores to high-resolution SEM imaging of submicrometer porosity. Direct HydroDynamic flow simulator was used to model multiphase flow in digital experiments by solving equations of the density functional hydrodynamics (DFH). These equations are conservation laws for the mixture of chemical components, momentum, and energy with constitutive relations involving Helmholtz free energy or the entropy functional. Samples were prepared for DR analysis and their representativeness was verified by obtaining routine properties of original plugs, trims, and mini-plugs selected for high-resolution DR imaging. We established the routine core analysis (RCA) properties of samples using DR and compared them with experimental data. Porous plate digital experiments were performed to obtain air-brine capillary pressure curves on all samples, with DR data verification with laboratory data on selected samples. A set of steady-state (SS) relative permeability digital experiments were then performed with live fluids at reservoir conditions. DR models were first fully saturated with brine and then de-saturated to water saturation that matched reservoir water saturation estimated from well logs. The SS cycle was performed after extended aging to establish a mixed-wet condition. SS relative permeability curves were obtained for all studied samples. DR modeling enabled looking at the dynamic changes of phase saturation in pores and significantly accelerated the laboratory program by performing porous plate tests 100-500 times faster and SS tests 20-50 times faster than conventional analysis using live fluids at pressure and temperature conditions surpassing operating ranges of laboratory equipment. The comprehensive combined study (both laboratory tests and DR analysis) results determined the reservoir flow properties within the entire permeability range. It allowed to reduce uncertainties in predicting production levels, improved the forecast quality of the hydrodynamic model and reduced the difference between the minimum and maximum estimates of geological and recoverable reserves.

An integrated laboratory study of low permeable carbonate reservoir (dolomitic limestones, Sarqala field) included a digital rock (DR) workflow that accelerated the time to complete the core analysis program, in a case when the standard is ineffective. All these data were used to justify the field development strategy.

Use of numerical models to characterize and evaluate reservoir potential is an industry wide practice, with increasingly more development decisions being substantiated by finite difference models. Advances on hardware and software, along with the ability to effectively incorporate accurate process physics, makes simulation a robust tool for field development decisions, particularly on complex operations such as enhanced oil recovery and/or reservoirs with challenging heterogeneity and pore structures. Use of these models does not come without its challenges where data requirements (and use of special characterization both at lab and field level) increase as does the reservoir characterization granularity and thus model sizes. Unsurprisingly the increase of model precision and data requirements amplifies non-uniqueness of the numerical solutions obtained during any field evaluation including field development planning (FDP). Incomplete/inconsistent datasets pose a further challenge to the accuracy (and arguably risk) of the forecasts by introducing further uncertainty on the process characterization. Use of complementary technology such as digital rock, that would enable mitigate impact of such uncertainties in a timely manner -either at field or laboratory level, is thus highly desirable particularly when dealing with enhanced oil recovery. Compounding the non-linearity effect of the EOR agent characterization is the effect of the augmented numerical artifacts (dispersion, dilution, etc) of which complex chemical implementations are prone to, making the upscaling process from laboratory dimensions to field more complex. This paper complements our previous investigation on the use of digital rock solutions and multi-scale upscaling and is addressing two complementing topics: Use of multiscale digital rock technology for field development – using a case study to illustrate the use of DR on field appraisal complementing otherwise unsampled facies, using a multi-nested approach to reconcile DR observations at different plug scalesEvaluate the impact of finite-difference numerical simulation grid on the surfactant injection performance- highlighting limitations and challenges of existing models as well as proposing potential upscaling alternatives. It is our intention to further reconcile digital rock upscaling with other EOR methods such as polymer/CO2 injection and of course surfactant. While we were able to highlight the caveats of upscaling on complex chemical floods we continue to investigate and design a solution that would encompass combination of chemicals (surfactant, alkaline and polymer) as well as handle of concentration/salinity changes.