The aim of this investigation is to develop a comprehensive understanding of an enhanced oil recovery (EOR) candidate reservoir based in an unconventional sandstone dominated environment. The unique geology, owing to its proximity to an inland, endorheic basin, alongside its complex stratigraphic geometry incorporating extensive folding and faulting as well as a laterally extensive unconformity. The study leans heavily on the forefront of reservoir characterizations. Reservoir characterization is crucial in providing an outline of the sub-surface and helps visualize the hydrocarbon system in-place. Our study area is the deeper consolidated units. This section was analyzed in detail to understand the petrophysical and fluid properties. The properties of the rock formation(s) of interest were identified from mineralogical content based on XRD analysis and SEM analysis to develop an interlink between the results. A compilation of the results plays a key role in determining reservoir quality and fluid properties which heavily influences important variables such as porosity, permeability, capillary pressure, relative permeability, wettability, interfacial tension, and fluid compositions. The clay mineralogy affects the penetration rate and the diagenetic overprint either enhances or deliberates fluid flow. The novelty of this integrated study lays the foundation for a thorough and bespoke screening EOR study, which is currently under development for an offshore candidate field. Preliminary screenings were also conducted through core flooding with representative outcrops. An understanding of the integration of the various reservoirs and fluid properties is essential in determining the characteristics of the entirety of the candidate reservoir. Incorporating these complex zones in an integrated reservoir characterization study is fundamental in achieving successful EOR deployment and optimizes oil production.

This investigation presents laboratory and field deployment results that demonstrate the potential candidacy utilizing Nano and bio-technologies to create superior chemicals for novel applications to increase oil recovery from both onshore and offshore reservoirs. Nano-technology is gaining momentum as a tool to improve performance in multiple industries, and has shown significant potential to enhance hydrocarbon production. The laboratory analysis and specifically designed coreflood results indicate there are beneficial interactions at liquid-nano solid interface that increase oil mobility. This will increase the surface activity of chemical surfactants and thereby make them the dominant agents to mobilize and recover oil from oil-bearing reservoirs. Advances in biotechnology offer another rich resource of knowledge for surface active materials that are renewable and more environmental-friendly. In addition, our studies also demonstrate that bio-surfactants are well-suited to provide superior performances in enhancing oil recovery. Nano-particles and biosurfactants may be included with synthetic surfactants to create novel and more efficient surface active agents for enhanced oil recovery. These formulations can promote better flow back of the injected stimulation fluids and additional mobilization to extract more oil from the matrix and micro-fractures. Laboratory experiments demonstrate that the specialized surfactant formulations created, interact with mixed or oil-wet low permeability formations to produce additional oil. Furthermore, this investigation also compares the total production on a candidate field with respect to typical water flood and the novel formulated surfactant approach. For each surfactant treatment, the overall designed injected fluid volume is 1500 m3 (~ 396,000 gallons) with 4 gpt (gallon per thousand unit) of surfactant concentration. Results indicate improved oil production with longer exposure time of the key surfactants within the reservoir. Enhanced surface wetting and super-low interfacial tension (IFT) at lower chemical concentrations are recognized to be the main mechanisms. The novel surfactant also shows stronger sustainability and endurance in keeping rock surface wettability over traditional surfactant system up to 5 times for an 8 PV wash. Furthermore, this can assist to identify and initiate the optimization of the identified mechanisms for potential applications within other compatible reservoirs. A number of successful field applications of EOR with special formulated nano and bio-based surfactant formulation are discussed in this paper. This unique study bridges the gap between the field realized results and lab optimization to enhance feasibility as a function of time and cost.

The sedimentology, petrography and reservoir potential of Pliocene sandstones within the Upper Red Series in the offshore LAM field, Western Turkmenistan, have been examined. Depositional settings are interpreted within the framework of the Red Series palaeoenvironments across the entire Turkmen sector of the Apsheron-Prebalkhan uplift zone, including its onshore extension to the east.Examination of 81 m of core from three separate intervals suggests that the Red Series in the LAM field is the product of a fluvial-dominated delta system with associated floodplain deposits, periodically flooded by the saline waters of the South Caspian Lake. Relatively thick sandstones, up to around 5 m thick, are interpreted as channel and pointbar deposits of a meandering river system, with thinner and finer-grained sandstones and siltstones inferred to be crevasse-splay and interdistributary floodplain deposits. Floodplain mudstones display signs of desiccation, soil formation, plant rootlets and occasional thin layers of anhydrite. Intervals with marine trace-fossil assemblages record incursions of saline-lake waters. Conglomeratic layers at the base of thicker mudstone intervals may be associated with abrupt transgressions of the lake. The best reservoir qualities are associated with the fluvial channel and point-bar sandstones. Crevasse-splay and other overbank sandstones are of poorer quality, while intercalated floodplain to lacustrine claystone/siltstone units may constitute local seals.Eighteen sandstone plug samples from the cored intervals were examined in thin-section and by XRD and SEM to assess how mineralogy, grain size and diagenesis affect reservoir quality. The samples consist predominantly of lithic arkoses and feldspathic litharenites; higher porosities, and therefore better reservoir potential, are associated with the feldspathic litharenites. Primary controls on porosity include compaction, clay-matrix content and calcite cementation. XRD data reveal the presence of illite, illite-smectite and chlorite. The presence

A Reliable reservoir characterization and model are useful for reservoir development in overpressure and complex reservoirs. The field has overpressure, multi fluid contacts, multi reservoir subunits, structural and stratigraphic sand discontinuities. The reservoir properties and quality decrease with increase of depth due to overburden compaction. However rock quality is useful for oil in place and productivity. Therefore, reliable reservoir characterization in deep reservoirs and estimation of fluids in place requires an integrated subsurface data approach. Overpressure reservoir has been observed and evaluated in some reservoirs, it tends to preserve porosity and has sufficient permeability for oil productivity from the deep reservoirs. Image resistivity/density log and chromatography data have been used to identify minor fault, gas/fluid evaluation and update the reservoir model. An integrated petrophysical evaluation has been implemented in reservoir characterization. A reliable in-house permeability log has been developed from porosity, clay bound, pore size, core and mobility data. It has used the of hybrid saturation height model that based on SCAL data including capillary pressure and Relative Permeability data for every reservoir rock type and fluid contacts for subunits. The advanced evaluation approach of subsurface and well test data has been used to provide reliable and good of reservoir properties and results on porosity, permeability, fluid contacts, reservoir rock type and initial water saturation in deep and overpressure reservoirs. The saturation height model (SHM) has been used, a quasi-SHM for unavailable core data in deep reservoir and PVT data have been used in the evaluation. The suitable open and cased hole logs data such as image resistivity/density, chromatography, pulse-neutron capture and production logs have been used to verify fault, fluid contacts, contribution, water saturation changes and production optimization. For every reservoir subunits, the formation pressure has been used to identify an initial oil water contact, reservoir subunits evaluation and thus it has provided SHM for complex reservoir modeling. The study has provided reliable reservoir characterization, reservoir modeling and for the development for multi-layers, over pressure and complex sandstone reservoirs. The high overpressure deep reservoirs have contributed for good oil productivity. It provides support to improve oil recovery from reservoirs and future plan for reservoir development target. Therefore the integrated reservoir evaluation approach has provided reliable assurance and important benefits for reservoir characterization, optimization and reservoir management. The integrated hybrid approach in this paper shows the value of advanced reservoir characterization in overpressure and faulted complex reservoirs. It has utilized the integration updated open and cased-hole data, gas/fluid contacts, stress direction, advanced permeability, saturation height model and gas-fluid evaluation. The evaluation also has provided the reliable for reservoir modeling, oil in place volume and field development purposes.

Water flooding is an established method of secondary recovery to increase oil production in conventional reservoirs. Analytical models such as capacitance resistance models (CRM) have been used to understand the connectivity between injectors and producers to drive optimization. However, these methods are not applicable to waterflood fields at the initial stage of life with limited data (less than 2 years of injection history). In this work, a novel approach is presented that combines analytics and machine learning to process data and hence quantify connectivity for optimization strategies. A combination of statistical (cross-correlation, mutual information) and machine learning (linear regression, random forest) methods are used to understand the relationship between measured injection and production data from wells. This workflow is first validated using synthetic simulation data with known reservoir heterogeneities as well as known connectivity between wells. Each of the four methods is validated by comparing the result with the CRM results, and it was found that each method provides specific insights and has its associated limitations making it necessary to combine these results for a successful interpretation of connectivity. The proposed workflow is applied to a complex offshore Caspian Sea field with 49 production wells and 8 injection wells. It was observed that implementing the diffusivity filter in the models while being computationally expensive, offers additional insights into the transmissibility between injector producer pairs. The machine learning approach addresses injection time delay through feature engineering, and applying a diffusive filter determines effective injection rates as a function of dissipation through the reservoir. Hence, the combined interpretation of connectivity from the different methods resulted in a better understanding of the field. The presented approach can be extended to similar waterflood systems helping companies realize the benefits of digitization, in not just accessing data, but also using data through such novel workflows that can help evaluate and continuously optimize injection processes.