Abstract In the past decades, oil companies have shown growing interest in increasing oil recovery efficiency. Commonly, after primary and secondary recovery phases, a large amount of oil remains trapped inside the reservoir. Thus, the number of studies focused on enhanced oil recovery is growing, aiming to increase the recovery factor. The focus of this work is to study the fundamentals of oil displacement in porous media using a confocal laser scanning microscope, which enables 3D visualization of dynamic phenomena with a good spacial and time resolution. The analysis was on oil displacement that results from the use of a suspension of gellan gum microcapsules in water injected after water injection. These microcapsules moving along with the water, blocked some of the preferential paths and forced the water to displace trapped oil ganglia. The result achieved was a collection of 3D images from artificial porous media, in which it was possible to distinguish the distribution of phases (microcapsules, oil, and aqueous phases) inside the porous media, before and after the microcapsules injection. These images showed that indeed the gellan gum microcapsules blocked preferential water paths and that, after the blockage, some oil ganglia were displaced from their original positions. This work applied modern techniques of microscopy to investigate the concept behind enhanced oil recovery using microcapsules.

Abstract This study aims at evaluating the mechanical integrity and the changes in the pore system of illitic sandstone formations being treated with HF acid generated in-situ and thermochemical fluids ( TCF ). Firstly, the acid-generating fluids were injected separately inside the core within a typical core flooding experiment. After that the core permeability, NMR porosity and rock static and dynamic parameters such as rock strength ( UCS ), dynamic Young's modulus, Poisson's ratio, shear modulus and bulk compressibility were evaluated before and after the treatment. Sand production prediction model was used to examine the potential of sand production problems for the cores treated with the in-situ generated acid ( ISGA ) and the TCF . Treating Scioto cores with the ISGA only led to permeability enhancement with final to initial permeability ratio K f i n a l K i n i t i a l of 1.2. In addition, treating the same cores with acid generating fluids and thermochemicals resulted in higher permeability enhancement with K f i n a l K i n i t i a l of 485. This higher enhancement in the formation permeability was attributed to the creation of some microfractures as was proved using the NMR scans. There was a reduction of the cores' static and dynamic parameters after being treated with the ISGA. This reduction was even higher after treating the core with thermochemical fluids. However, the sand production prediction model stated that the reduction in rock mechanical parameters would not lead to sand production problems.

Abstract Data uncertainty adds extra complexity in reservoir simulation of large and heterogeneous fields. Such complexity leads to higher consumption of time and effort in optimization study, e.g. in determining optimum well placement. Developing a systematic methodology to deal with any data uncertainty is critical to improve the reliability of such optimization study. In this study, we present a new methodology to optimize well placement configuration under uncertainty in waterflood design. As the waterflood performance is highly influenced by its timing, multiple scenarios were defined with varying injection starting time. Through this new methodology, we have successfully optimized all scenarios and determined the optimum time to start the waterflood.

In waterflooding, achieving adequate mobility control in high-salinity reservoirs is a key challenge because polymers, the traditional mobility control agents, have poor solubility at high salinities. The objective of this work is to find an inexpensive and environmentally friendly mobility control formulation using a clay-stabilized Pickering emulsion and test its performance for waterflooding at high salinity conditions. Pickering emulsion is an emulsion that is stabilized by solid particles. Decane-in-water Pickering emulsions stabilized with clay particles (sodium montmorillonite) in NaCl brines at high salinity were prepared using a sonicator. The emulsion droplet coalescence stability was analyzed by measuring the droplet size distribution of the emulsion over time by light scattering, and creaming stability was evaluated by emulsion height visualization. A fluorescent dye was added into the clay suspension to characterize the structure of the emulsion by fluorescence imaging. The arrangement of clay particles on the oil-water interface was examined by Cyro-SEM, wherein the emulsion sample was frozen before being placed in the SEM chamber. The rheological properties of clay-stabilized Pickering emulsion under high-salinity conditions were measured with a rheometer. Flooding experiments with clay-stabilized emulsion were conducted in both a microfluidic and a sandpack apparatus to test mobility control performance of Pickering emulsions. Results show that clay particles have the ability to stabilize Pickering emulsions, which exhibit good coalescence stability at high salinities. Clay particles adsorb at the oil-water interface, thus preventing the droplets from coalescing for at least several months. Fluorescent and cryo-SEM images revealed a 3D spherical structure of emulsion droplets with clay particles arranged perpendicular to the oil-water interface. The bulk viscosity of stable emulsion with 5 vol. % oil fraction is around 100 mPa.s at a shear rate of 7 s -1 . Microfluidic experiments showed that the injection of Pickering emulsion provides adequate mobility control, as evidenced by significant recovery of residual oil after waterflooding. After Pickering emulsion flooding, oil recovery factor increased from 67% (water flooding) to more than 80%. Enhanced oil recovery (EOR) mechanisms of Pickering emulsion flooding are also studied by using a microfluidic chip showing some novel and interesting phenomena. In sandpack with higher permeability, emulsion injection mobilized more than 10% residual oil after water flooding. This is the first time research on using clay-stabilized Pickering emulsion for mobility control under high-salinity conditions is reported. Results reveal that clay-stabilized Pickering emulsions exhibit good coalescence stability and promising potential for EOR at high salinity conditions. Since clay particles are naturally-occurring, they may also be an economical and environmentally friendly alternative to polymer for mobility control in a high salinity reservoir.

Flowback rate transient analysis (RTA) is a practical tool for characterizing hydraulic fracture (HF) properties. However, the accuracy of the interpreted results from flowback RTA is challenged by the complexity in two-phase flow in the hydraulic fracture and matrix system. Accordingly, we present a new semianalytical method to characterize HF attributes and dynamics using multi-phase flowback data for tight and ultratight (shale) oil wells. The proposed method includes a two-phase diagnostic plot, a fracture RTA approach for straight-line analysis, and a matrix model capable of characterizing water and oil flow. The RTA approach is based on fracture infinite acting linear flow (IALF) and boundary dominated flow (BDF) solutions, which treats HF as an open tank with a variable production rate at the well and the contribution of water and oil from matrix within the distance of investigation (DOI). The pressure-dependent fluid and geomechanical properties, such as permeability and porosity, are considered in the pseudotime defined in fracture and matrix to reduce the nonlinearity of the system. We tested the accuracy of the proposed method against numerical results obtained from commercial software and verified its applicability by analyzing the flowback and long-term production data from a field example in Eagle Ford shale. The validation results confirm that our method can closely calculate water and oil influx from matrix as well as the average pressure and saturation in the HF and matrix DOI. The accurate estimation of the initial fracture permeability and pore volume demonstrates the applicability of the proposed method in quantifying HF properties from two-phase flowback data exhibiting fracture IALF and BDF regimes. The analysis results show that the estimated initial fracture pore volume shows more accuracy than initial fracture permeability due to the different calculation sources in the straight-line analysis. In short, the proposed method is, to our best knowledge, the first RTA approach incorporating the two-phase water and oil influx from matrix into the inverse analysis of fracture properties and dynamics using straight-line analysis, instead of history matching

Identification of the location and orientation of fractures and preferential flow paths using the dynamic reservoir response can provide insightful guidance for naturally fractured reservoir development and management. However, data assimilation for high-resolution fractured reservoir models using well responses is time consuming. The streamline-based technology has proven to be effective and efficient for subsurface flow modeling and inverse problems. We propose a novel and robust streamline tracing method in dual porosity dual permeability (DPDK) systems and an efficient workflow to identify fracture location in fractured reservoir models using dynamic data. In DPDK models, the matrix-fracture interactions are typically described by non-neighbor connections (NNCs) which make streamline tracing non-trivial. We use a boundary layer method to reconstruct the fluxes and avoid flux discontinuities at NNCs. The flux reconstruction allows us to trace streamlines and compute the time of flight (TOF) in DPDK models. The fracture identification workflow relies on the streamline-based analytic sensitivity computation and rapid model calibration using dynamic data. Multiple realizations of fracture distribution are initialized and calibrated using observed well responses, for example water cut and BHP. The ensemble of calibrated fracture models is then used for uncertainty analysis, and a probability map of the spatial distribution of fractures is finally generated. The power and utility of our approach are demonstrated using several applications. We first validate the streamline tracing algorithm for DPDK model by comparing its TOF with the result generated by the finite volume formulation of TOF generalized for compressible flow. Next, we validate the fracture identification workflow using a synthetic case by comparing the fracture probability map with the "true" fracture distribution. Finally, we apply our method to a DPDK model of a fractured reservoir and generate fracture probability map by calibrating multiple model realizations to well production and pressure data. The fracture probability maps serve as valuable tools to guide reservoir management and field development strategy. The novelty of this work is the newly developed streamline tracing algorithm for DPDK models and the efficient workflow to generate fracture probability maps based on dynamic data. The proposed approach is easy to implement and can be coupled with commercial simulators for field scale applications.

Caprocks play a crucial role in geological storage of CO 2 by preventing the escape of CO 2 and thus trapping CO 2 into underlying porous reservoirs. An evaluation of interaction-induced alteration of hydromechanical properties of caprocks are essential to better assess the leaking risk and injection-induced rock instability, and thus ensuring a long-term viability of geological CO 2 storage. We study the changes in nanopores, elastic velocities and mechanical responses of a carbonate caprock due to rock-water/brine-CO 2 interaction (CO 2 pressure ~ 12 MPa; 50 ℃). Before the interaction, the total and accessible porosities are 1.6% and 0.6%, respectively, as characterized by the Small Angle Neutron Scattering (SANS) technique. SANS results show that the total porosity of the carbonate caprock increases apparently due to rock-brine-CO 2 interaction and the increasing rate rises as brine concentration increases (2.2% for 0M NaCl, 2.6% for 1M NaCl, and 2.7% for 4M NaCl). The increase total porosity is due to the dissolution of calcite which tends to enlarge accessible pores (by 0.8%-1.2%) while slightly decrease the inaccessible pores (by 0.1%-0.2%). Under CO 2 -acidified water environment, P- and S-wave velocities (5536.7 m/s and 2699.7 m/s) of a core sample containing natural fractures decreases by 8.5% and 8.1% respectively, while both P- and S-wave velocities (6074.1 m/s and 3858.8 m/s) for a intact sample show only ~0.5% decreases. The interaction also causes more than 50% degradation of the uniaxial compressive strength for the core sample with natural fractures. We also conduct simulations of the single-phase creeping flow and two-phase water-CO 2 flow in micron-scale natural fractures, as extracted from X-ray Micro-CT images of the core sample. The simulated absolute permeability (2.0×10 -12 m 2 ) is much higher than the matrix permeability (6.7×10 -20 m 2 before the interaction; 1.3×10 -19 m 2 after the interaction), as calculated based on the Kozeny–Carman Equation. This indicates that natural fractures provide preferential flow paths for CO 2 while flow through caprock matrix can be reasonably neglected. Simulation results also indicate that CO 2 preferentially migrates in the natural fractures where there are more inter-connected and permeable channels. The study recommends that more attention should be addressed on interaction-induced alteration of fracture/faults permeability/stability, and its effect on the sealing integrity of carbonate caprocks.

The knowledge of the effects of instability and heterogeneity on displacements, primarily enhanced oil recovery and carbon dioxide storage, are well known though they remain difficult to predict. The usual recourse to modeling these effects is through numerical simulation. Simulation remains the gold standard for prediction; however, its results lack generality, being case specific. There are also several analytic models for displacements that are usually more informative than simulation results. However, these methods apply to steady-state, incompressible flow. Carbon dioxide injection for storage uses compressible fluids, and, in the absence of producers, will not approach steady-state flow ( Yun et al., 2017 ). Consequently, it is unlikely that storage will be in reservoirs of open boundaries. Flow of compressible fluid necessitates the use of closed or partially sealed boundaries, a factor that is consistent with compressible flow. This work deals with the conditions that cause the onset of viscous fingering or Saffman-Taylor (ST) instability. The actual propagation of fingers, a subject of much recent literature, is not discussed here. The original ST formalism of M>1 is highly restrictive: it is for linear flow of nonmixing incompressible fluids in steady-state flow. In this work we relax the incompressible flow restriction and thereby broaden the ST criterion to media that have sealing and/or partially sealing outer boundaries. We use the non-linear partial differential equation for linear flow and developed analytic solutions for a tracer flow analog and also for a two-fluid compressible flow. The analysis is restricted to so-called stabilized flow, and to constant compressibility fluids, but we are not restricted to small compressibility fluids. There is no transition (mixing) zone between displacing and displaced fluids; the two components are locally segregated or the displacement is piston-like. The absence of a transition zone means that the results apply to both miscible and immiscible displacements, absent dispersion or local capillary pressure. We use the product of the fluid compressibility and pressure drop ( c f ΔP ) cut-off to differentiate the compressibility group. Here, small and large compressibility groups correspond to the cases where c f ΔP < 0.1 and c f ΔP > 0.1 respectively 9-10 . In this work, ΔP is defined as the pressure drop within the specific fluid region. Results will be based on proposed analytical solutions compared to numerical flow simulation. The key contribution here is the addition of compressibility, which additionally makes possible the study of the effect of external boundaries. Absent compressibility, the necessary condition for the growth of a viscous finger is simply the mobility ratio, M>1. It is the objective of this work to study how the ST criterion is affected by the inclusion of compressible flows and in the presence of sealing and partially sealing outer boundaries as in CO 2 -storage and EOR by gas injection. Results show that adding compressibility always makes displacements more unstable for steady-state flow, even for favorable mobility ratio (M<1) at extremely large compressibility ( e.g . c f > 5e −3 1/psi). For a sealed external boundary, displacements will become more stable as a front approaches an external boundary for all mobility ratios (M) investigated.

The three-dimensional connectivity of the fluid phases in porous media plays a crucial role in governing the fluid transport, displacement, and recovery. Accurate three-dimensional quantification of the fluid phase connectivity following each fluid injection stage will lead to better understanding of the efficacy and efficiency of the fluid injection strategies. Two metrics for measuring the connectivity in 3D show robust performance; one uses fast marching method to quantify average time required for a monotonically advancing wave to travel between any two pixels and the other uses two-point probability function to approximate the average distance between any two connected pixels belonging to the same fluid phase. The two connectivity metrics are applied on the three-dimensional (3D) CT scans of one water-wet Ketton whole-core sample subjected to five stages of multiphase fluid injection to quantify the evolution of the three-dimensional connectivity of the three fluid phases (oil, water, and gas). The water-wet Ketton carbonate sample (4.9 mm in diameter and 19.5 mm in length) is subjected to five sequential stages of fluid injection: 100%-brine-saturated sample, oil injection, water-flooding #1, gas injection, and water-flooding #2. CT-scan of the core sample was acquired after each injection stage. The metric response for oil phase connectivity drops after each injection process, denoting a reduction in oil connectivity after each fluid injection. The spatiotemporal variations in the connectivity of a fluid phase help understand the fluid displacement across pores of varying sizes depending on the wettability.

Gas condensate field development is a challenging task involving many technical disciplines, from sedimentology and petrophysics to reservoir and facility engineering. For evaluation of development options in a Nile Delta onshore field with original reservoir pressure close to dew point, reservoir simulation must account for potential condensate blockage near wellbore. Uncertainties related to blockage can severely risk the estimation of gas and condensate reserves and production, and significantly impact project development or even put the investment decision on hold. The method of W hitson 8 for determining velocity-dependent gas-condensate relative permeabilities is sufficiently robust and reliable to model well deliverability in moderately homogenous reservoirs. However, with increasing heterogeneity, gas condensate flow in contrasting facies or thin laminated zones requires deeper investigation. Thin low permeability layers can act as bounding surfaces with condensate dropout below dew point, which may trap initially connected gas volumes. Estimation of gas condensate well deliverability is further complicated if shortage of reservoir core material and fluids precludes reliable coreflood experiments across the full range of pressure/flow regimes. This paper demonstrates how digital rocks technology can enhance the understanding and de-risk the prediction of gas condensate flow in contrasting rock types and with only limited core material and cuttings at hand. Remnants of sidewall core plugs from earlier laboratory analyses were scanned using X-ray micro-tomography to obtain 3D images down to pore-scale of regions ranging from open to tight. Flow simulations were performed in the pore space of the processed images to reconcile connected porosity, absolute permeability and capillary pressure-saturation curves with laboratory core analysis results, and to refine the rock types ranging from higher to lower reservoir quality. As input to two-phase gas-condensate flow simulation, representative capillary numbers and viscosity ratios were estimated based on PVT and the planned field development options and existing dynamic reservoir model. The dynamic pore-scale simulations yielded gas-condensate relative permeability curves versus rock type and capillary number which agreed well with published literature. The delivery of consistent relative permeability estimates in a short timeframe from this digital rocks approach served to reduce uncertainties in reservoir modeling to de-risk the development planning of the gas condensate field.

An Aker BP operated oil field in the North Sea has occasionally experienced production flow instabilities in the production lines and risers. The oscillations in multiphase rates are kept within the process capacity limitation at the host installation typically by increasing backpressure (planned flaring is not allowed for on the Norwegian Continental Shelf). The heightened backpressure impacts the production potential of the field. The objective of the project described in this paper has been to develop and implement a new method for real-time production optimization providing an online assessment of slugging severity and suggested actions in order to mitigate slugging and increase production. The developed software tool has been validated using field data. A statistical approach based on the physical characteristics of the separator has been developed. A combination of transient multiphase flow simulations and data analysis has been employed in order to formulate the risk of exceeding separator constraints as a multidimensional function of the operational conditions. In order to generate a three-dimensional heat map of the risk related to the current state, operational data is continuously gathered from production sensors and transformed into pseudo-steady state values. A heat map is defined by a function where four relevant operational values can be selected. These values are: oil production rate, topside choke setting, gas lift rates and water cut. The software solution is run on a cloud infrastructure with an interactive web user interface. In a pilot program we have evaluated the ability of the stability advisor to continuously assess the severity of flow instabilities, identify measures to reduce the risk level and minimize associated production losses. The operator has identified valuable operational insights from the tool in a pilot program. The flow instabilities predicted by the model correlate well with observed data from the field. The tool is scalable to other fields with similar flow problems. Previous papers on slug flow prediction are in general conducted as offline study projects. There has been little success in making real-time scalable solutions available to continuous operations. This paper explains a method on how physical modelling of the flow system combined with statistical methods and access to real-time sensor data can provide a new approach for real-time slug flow prediction. The result demonstrates a scalable solution where output is presented in a format that can be applied by daily operations to act on and provide new and valuable production insights.

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases. The workflow is tested for a 50x50 two-dimensional (2D) heterogenous permeability field and for the SPE benchmark Brugge field, and is seen to result in significant improvement in oil recovery and sweep efficiency. A single forward run of the trained ML model is faster than the conventional simulator by about 3 orders of magnitude, making the approach suitable for large scale field application accounting for geologic uncertainty. The parsimonious representation of geologic heterogeneity and the use of ML for forward modeling makes the approach highly scalable and well-suited for full field applications.

The historical challenges and high failure rate of using standalone screen in cased and perforated wellbores pushed several operators to consider cased hole gravel packing or frac-packing as the completion of the choice. Despite the reliability of these options, they are more expensive than standalone screen completion. Since several developments are not designed for cased hole gravel pack or frac-pack, purpose-driven sand control methods for cased and perforated wells are recommended. This paper employs a combined physical lab testing and Computational Fluid Dynamics (CFD) for lab scale and field scale to assess the potential use of the standalone screen in completing the cased and perforated wells. The aim is to design a fit-to-purpose sand control method in cased and perforated wells and provide guidelines in perforation strategy and investigate screen and perforation characteristics. More specifically, the simultaneous effect of screen and perforation parameters, near wellbore conditions on pressure distribution and pressure drop are investigated in detail. A common mistake in completion operation is to separately focus on the design of the screen based on the reservoir sand print and design of the perforation. If sand control deemed to be required, the perforation strategy and design must go hand in hand with sand control design. Several experiments and simulation models were designed to better understand the role of perforation density, the fill-up of annular gap between the casing and screen, perforation collapse and screen plugging on pressure drop. The experiments consisted of a series of step rate tests to investigate the role of fluid rate on pressure drop and sand production. There is a critical rate in which the sand filled annular gap will fluidize and also sanding would be different for different fluid density. Both test results and CFD simulation scenarios comparatively allow to establish the relation between wellbore pressure drop with screen and perforation parameters and determine the optimized design. The results of this study highlight the workflow to optimize the standalone screen design for the application in cased and perforated completion. The proper design of standalone screen and perforation parameters allows maintaining cost-effective well productivity. Results of this work could be used for choosing the proper sand control and perforation strategy, rather than using gravel packing and frac-packing methods in cased and perforated completions.

Nanoparticles have great potential to mobilize trapped oil in reservoirs by reducing the oil-water interfacial tension, altering the rock wettability, stabilizing foams and emulsions, and heating the reservoir to decrease the oil viscosity. However, the direct application of magnetic forces on paramagnetic nanoparticles in reservoir engineering applications has not be extensively investigated. We demonstrate the enhanced oil recovery (EOR) potential of hydrophilic magnetic nanoparticles in oil production by direct observation using microfluidics. We studied the mobilization of oil blobs by a ferrofluid (a suspension of hydrophilic magnetic nanoparticles in water) in a converging-diverging channel with varying depth (so-called 2.5D micromodel). The channel had a varying depth of 10-30 microns and a varying width of 50-200 microns, approximating a flow path in the rock. The nanoparticle suspension was injected at 0.1 microliter/hour. The channel was made of glass and thus the water-based ferrofluid was the wetting fluid. Initial ferrofluid flooding experiments were performed under a static magnetic field. This magnetic field caused oil droplet deformation, dynamic break-up into smaller droplets, and subsequent residual oil saturation reduction. Significant oil blob displacement was observed within 2 hours after the magnetic field was applied. During the flooding, the oil saturation within the observation area of the micromodel reduced from 27.4% to 12.0%. We then hypothesized that a changing field would have an even larger effect in saturation reduction. We have thus designed experiments with a magnetic field of the same magnitude slowly rotating under the micromodel. We subsequently observed a completely different phenomenon, namely self-assembly of oil droplets, indicating formation of the hydrophilic magnetic nanoparticles microstructures (chains under the magnetic field). These magnetic nanoparticle microstructures were ever-changing under the rotating magnetic field. While the ability of ferrofluid to rotate small blobs was in itself interesting, in experiments without actual flooding (and thus synergy of hydrodynamic and magnetic forces) we did not observe any additional oil recovery.

Slug flows generate variable loads that excite pipelines, inducing oscillatory displacements and tensions of significant magnitude, raising concerns about the physical integrity of the pipe’s structure. The present paper presents a simulation model to compute non-uniform slugs, to provide a tool for the analysis of the dynamic behavior of horizontal pipelines in subsea petroleum production systems. This model was tested for a straight, horizontal, free span hanging pipeline supported at both ends. The development of the present methodology was based on a previous model of regular slugs. The present model takes into account the expansion of the gas bubble length along the pipeline, generated by the negative streamwise pressure gradient between the pipeline’s entrance and exit, resulting in a longitudinal sequence of non-uniform slugs. The model’s algorithm used to calculate the mass distribution in the slug flow is implemented in a subroutine of a pre-existent software, commonly known to simulate the mechanical behavior of pipelines under dynamic loads. The dynamic responses of a pipeline excited by non-uniform slugs – vertical displacement, bending moment and bending stress – were analyzed as a function of the gas expansion global rate, and were compared to the dynamic responses induced by a regular slug flow. It is concluded that the non-uniform slug distribution imposes a more complex excitation on the pipe, while the perfect regular slug flow induces an excitation with a single well-determined frequency. The difference between irregular and regular flows depends on the magnitude of the pressure gradient acting along the pipeline’s length.

The objective of this paper is to structure a data-driven-based workflow to design and optimize alkali-surfactant-polymer flooding ( ASP ) projects. Various objective functions from the techno-eco perspectives are considered to obtain comprehensive optimum ASP slug formulations and injection operation schemes. Several universal multi-layer neural networks ( MLNN ) are trained and they act as surrogate models of high-fidelity numerical simulation models to evaluate the objective functions involved in the optimization workflow. The input parameters considered by the machine-learning workflow include the reservoir rock and fluid properties, ASP slug formulation, and project design parameters. A physical equation of state, HLD - NAC equation, is employed to model the microemulsion phase behavior of the crude oil/brine/surfactant system. The validity of the surrogate models is confirmed via extensive blind testing applications with error margins of less than 5%. Thus, the MLNN can be employed as an expert system to assess the response functions of the ASP injection processes, including oil recovery, water cut reduction, pressure responses, etc. A hybrid global optimization workflow is structured by coupling the expert MLNN systems with particle swarm optimizer ( PSO ). Comprehensive techno-eco-assessments are carried considering the oil recovery, chemical slug utilization ratio (incremental oil production per unit mass of chemical additives), and project economics as objectives. This paper presents case studies to illustrate the robustness of the proposed workflow in optimizing the ASP injection projects considering multiple objective functions. The optimization work focuses on the design of ASP slug formulations and injection patterns. A sensitivity analysis is carried to investigate the trade-off factors between pairs of the objectives. Objective functions exhibiting a strong trade-off relationship can be included to structure Pareto front solutions, which enables the optimization workflow to find various optimized ASP formulations and injection schemes. The outcomes of this work not only provide field operators with various options to implement ASP injection processes but also generate stochastic assessments of the optimized objectives. This work develops a universal proxy model that is competent to generalize the microemulsion phase behavior that occurs in the ASP injection processes. The trade-off relationship amongst the critical objective functions is investigated via a rigorous sensitivity analysis using the proxy models. With the help of the developed model, the decision-makers can design ASP injection projects based on various project preferences. Moreover, the project risks can be understood by observing the stochastic outcomes of the optimized objective functions.

This paper presents the analysis of transient pressure measurements from a recent CO 2 foam pilot in East Seminole Field, Permian Basin, USA. A surfactant-stabilized foam was selected to mitigate CO 2 EOR challenges in this field by reducing CO 2 mobility in an effort toimprove sweep efficiency, oil recovery, and CO 2 storage potential. The surfactant system was designed in the laboratory by measuring surfactant adsorption and verifying foam stability. A surfactant-alternating-gas (SAG) injection strategy, with 10 days of surfactant solution followed by 20 days of CO 2 , began in May 2019. The pilot monitoring program aimed to evaluate reservoir response to foam injection. Surveys included CO 2 injection profiles, CO 2 tracer tests, collection of injection bottom hole pressure/temperature data, and three-phase flow rates. Injection BHP and temperature data from the downhole pressure gauge (DHPG) was used to evaluate the pilot response during surfactant and CO 2 injection. The analysis was conducted by examining the differential pressure (dP) and differential temperature (dT) through time for the first nine SAG cycles. A high-resolution two-dimensional radial flow model was developed to history match the measured transient pressure data. The simulation model included the porosity and permeability distribution from a validated sector-scale model of the pilot pattern and surrounding producers. The radial flow model was used to examine the impact of foam and/or relative permeability on injectivity and mobility reduction when switching between surfactant solution and CO 2 in a SAG process. Transient analysis showed that the temperature responses were quite similar during most SAG cycles. On the other hand, differential pressures consistently increased during periods of surfactant injection and decreased during the subsequent CO 2 injection periods. The pressure increase (buildup) during surfactant injection was due to a decrease in mobility, showing development of a mobility bank in the reservoir. There are also questions regarding the impact of foam and/or relative permeability on injectivity and mobility reduction when switching between surfactant solution and CO 2 in a SAG process.

The onshore Senoro field is an Indonesian carbonate pinnacle reef gas reservoir that so far has produced around 15% of the estimated original gas in place (OGIP). Twelve wells have been drilled consisting of ten production wells, one disposal well, and one monitoring well. All production wells were equipped with a permanent downhole gauge (PDG) to obtain near-bottom hole pressure data. A p/Z plot [ 1 ] of the pressure data exhibits a non-linear trend suggestive of pressure support from the aquifer or, perhaps, an adjacent gas reservoir in restricted communication with the main reservoir. If the non-linear trend is due to aquifer support, analysis assuming a weak water drive yields a bigger estimate of OGIP, and vice versa. Analysis of reservoir pressure and production data alone can result in unacceptably-high uncertainty related to drive mechanism and OGIP. This paper describes how cased-hole saturation logging from the gas reservoir across the contact and into the aquifer was integrated with other surveillance techniques based on pressure and production data to reduce the uncertainty and improve definition of drive mechanism and estimates of OGIP. Core data and pressure transient analysis in the Senoro field shows that the gas zone has a permeability in the range of 50 milidarcy (md) to 200 md, while the aquifer, which is mainly found in an underlying platform facies, has a much lower permeability in the range of 1 md to 40 md. The high permeability contrast between gas and water zone was expected to result in weak pressure support from the aquifer. Moreover, a tight streak is found in the middle of the aquifer which virtually eliminates bottom-drive aquifer support. Nevertheless, ongoing surveillance, including analysis of production data using flowing material balance and type curve analysis, indicates there is pressure support. Therefore, to address the uncertainty about aquifer support, it is necessary to evaluate the aquifer performance with other surveillance techniques to augment the PDG data. These other techniques included annual time-lapse saturation logging in the monitoring well, and static (wireline) bottomhole pressure (SBHP) surveys taken in select production wells and the monitoring well to estimate gas and aquifer pressure. After four years of production, the latest saturation log shows increased water saturation above the initial depth of the gas-water contact (GWC), indicating movement of the aquifer into the bottom of the gas column at the flank of the reservoir. The SBHP survey in the aquifer also shows that aquifer pressure has dropped by 330 psi compare to the initial pressure taken with a wireline formation tester. This compares to a pressure decrease of 370 psi in the overlying gas reservoir. Analysis of the current gas reservoir pressure trend, and the current aquifer trend, shows that the current depth of the GWC is about 50 feet shallower than the initial depth, which is consistent with the depth of the increased water saturation seen in saturation logging in the flank monitoring well. This result is consistent with the match from a simulation model with a weak water drive. Conversely, if a strong water drive is assumed, the decline in aquifer pressure will be smaller than observed and the GWC will be higher than observed. Sensitivity to combination of gas expansion energy and aquifer strength has been done to narrow the range of OGIP. The results described in this paper illustrate the benefit of integrating saturation and pressure measurements from the aquifer with other surveillance data to better measure aquifer performance, determine drive mechanism, estimate OGIP and recovery, forecast production, and anticipate problematic water production in a gas reservoir.

State-of-the-art chemical flooding simulators typically use nonpredictive phase behavior and property models to design a surfactant flood. For example, a variation of the black-oil model is often used to represent phase behavior in several commercial simulators. We examine the available methods including more recent physics-based models such as the HLD-NAC equation-of-state and their effects on overall recovery, front speeds, and breakthrough times. We implement the HLD-NAC EoS model in UTCHEM to examine the impact of changing salinity and other variables on the phase behavior and the recovery process. A novel predictive viscosity model is also implemented for the first time in UTCHEM to give a more accurate prediction of viscosity. We isolate the impact of salinity and other gradients on recovery in a one-dimensional homogeneous reservoir. Results show that the composition path can enter the Winsor II+ region for certain changes in variable gradients. When the two-phase region is entered, the trailing injected fluid surpasses the chemical slug and contacts the oil bank directly. The microemulsion phase saturation is then decreased to immobile values so that surfactant is now immobile and oil recovery is significantly decreased. We further show that the presence of polymer - both in the buffer and the chemical slug - has little effect on the appearance of the arrested microemulsion and oil bank. Polymer does partially offset the negative effects by providing conformance control immediately after the microemulsion phase is trapped. The salinity gradient should be designed so that the composition path avoids the II+ lobe in its entirety, giving a robust and mobile slug with or without polymer. We propose a limit in injection salinity under which the II+ lobe can be avoided. We also show that the less accurate viscosity model overestimates recovery in a two-dimensional simulation of the chemical flood.

Since 2010, hydrocarbon production from long horizontal wells targeting shales has become the norm for industry leaders. Because of the steep decline rates, it is vital to understand the reservoir and its properties before going through with a full-scale fracture stimulation. Through the application of Diagnostic Fracture Injection Tests (DFIT), one can determine accurate estimates of closure pressure, net pressure, pore pressure, formation permeability, and induced fracture geometry. The Utica shale is among the most promising reservoirs of the future, but there is limited information available discussing its properties. In SPE-196149-MS, we analyzed a DFIT from one horizontal well targeting the Utica. However, in order to fully understand the Utica shale at scale, further analysis is required. In this study, we will present three additional horizontal wells targeting the Utica, and analyze the pressure and its derivative to accurately estimate the properties mentioned above. DFIT analysis is an advanced technique to accurately predict stress regimes and reservoir properties. However, interpretation of DFIT data is challenging, especially in shale formations. In this study, we overview the geologic properties of the Utica shale, discuss the development of DFIT analysis and its governing equations, then present the three data sets and resulting conclusions. We specifically discuss the Tangent Line Method, the Compliance Method, and the Variable Compliance method in detail, while comparing their underlying equations and assumptions to determine closure pressure. After-Closure analysis is then performed in order to verify fracture closure and identify flow regimes. Through linear regression of this data, pore pressure from a linear flow regime is extrapolated, and through numerical simulation, key reservoir properties, such as permeability and fracture geometry, are estimated for the Utica shale. The DFIT interpretation and simulation results from this study are very insightful. Interpreting the GdP/dG function, the closure pressure ranges from 4,943 psi to 6,141 psi, contributing to a closure pressure gradient of 0.797 to 0.891 psi/ft for the Utica shale. Based on the pressure transient analysis, the pore pressure ranges from 3,238 psi to 4,064 psi, contributing to a pore pressure gradient of 0.486 to 0.616 psi/ft for the Utica shale. Additionally, field wide ranges of reservoirs properties are presented, allowing industry to further optimize their drilling and fracing techniques in the Utica shale. Two of the wells in this study are close in proximity and show very similar results both in After-Closure analysis and in pressure response curves. The third well displays a different GdP/dG response, leak off characteristics, pressure transient behaviors, formation permeability, and fracture geometry. This variance in results can be attributed to regional differences in geology, stresses, and pressures. Therefore, operators need to consider regional differences in reservoir properties in order to enhance the development of Utica shale and unlock all potential recoverable hydrocarbons.