Predicting accurate erosion rate due to sand particles in oil and gas production is important for maintaining safe and reliable operations while maximizing output efficiency. Computational Fluid Dynamic (CFD) is a powerful tool for erosion prediction as it provides detailed erosion pattern in complex geometry. In an effort to improve accuracy of erosion prediction, this paper proposes an algorithm to accurately represent particle shape in CFD erosion simulation through coupling with Discrete Element Method (DEM) for non-spherical shape particles. The fluid motions are predicted by CFD and the particle movements (including particle-particle and particle-wall collisions) and fluid-particle interaction are calculated using DEM. It is widely known that sand particles are of finite volume with a non-spherical shape, accurate representation of sand particles is important in CFD modelling for accurate prediction of erosion rate. Traditional CFD approach usages lagrangian tracking of sand particles through Discrete Phase Model (DPM), where a particle is assumed as a point mass for the calculation of trajectory and particle-wall interaction. Particle impact velocity and impact angle are important parameter in determining erosion. Assumption of point mass in DPM approach, will not capture particle-wall interaction accurately especially when particles are of non-spherical in shape. In additional, DPM approach ignores particle-particle interactions. This can adversary affect the accuracy of erosion predictions. Integrating non-spherical DEM collision algorithm with CFD erosion simulation, will overcome these limitations and improve erosion predictions. Benefits of this CFD-DEM erosion modelling was demonstrated for gas-solid flow in a 2" pipework which consists of out-of-plane elbows in series and blind-tees. Experimental dataset [ 1 ] for erosion pattern on each elbow was used to validate CFD predictions. Three different erosion CFD simulations were performed, traditional DPM based CFD simulation, CFD-DEM simulation for spherical shape particles and CFD-DEM simulation for non-spherical shape particles. CFD-DEM coupled simulations clearly show an improvement on erosion predictions compared to DPM based CFD simulation. Effect of non-spherical shape on rebound angle during particle-wall collision is captured accurately in CFD-DEM simulation. CFD-DEM simulation using non-spherical particle, was able to predict erosion pattern closer to experimental observations. This paper will demonstrate an increase in accuracy of sand erosion prediction by integrating DEM collision algorithm in CFD modelling. The prediction results of elbow erosion subject to a condition of dilute gas-particle flow are validated against experimental data. Improved prediction of erosion risk will increase the safety and reliability of oil & gas operations, while maximizing output efficiency.

Depositional mechanisms of sediments and post-depositional process often cause spatial variation and heterogeneity in rock fabric, which can impact the directional dependency of petrophysical, electrical, and mechanical properties. Quantification of the directional dependency of the aforementioned properties is fundamental for the appropriate characterization of hydrocarbon-bearing reservoirs. Anisotropy quantification can be accomplished through numerical simulations of physical phenomena such as fluid flow, gas diffusion, and electric current conduction in porous media using multi-scale image data. Typically, the outcome of these simulations is a transport property (e.g., permeability). However, it is also possible to quantify the tortuosity of the media used as simulation domain, which is a fundamental descriptor of the microstructure of the rock. The objectives of this paper are (a) to quantify tortuosity anisotropy of porous media using multi-scale image data (i.e., whole-core CT-scan and micro-CT-scan image stacks) through simulation of electrical potential distribution, diffusion, and fluid flow, and (b) to compare electrical, diffusional, and hydraulic tortuosity. First, we pre-process the images (i.e., CT-scan images) to remove non-rock material visual elements (e.g., core barrel). Then, we perform image analysis to identify different phases in the raw images. Then, we proceed with the numerical simulations of electric potential distribution. The simulation results are utilized as inputs for a streamline algorithm and subsequent direction-dependent electrical tortuosity estimation. Next, we conduct numerical simulation of diffusion using a random walk algorithm. The distance covered by each walker in each cartesian direction is used to compute the direction-dependent diffusional tortuosity. Finally, we conduct fluid-flow simulations to obtain the velocity distribution and compute the direction-dependent hydraulic tortuosity. The simulations are conducted in the most continuous phase of the segmented whole-core CT-scan image stacks and in the segmented pore-space of the micro-CT-scan image stacks. Finally, the direction-dependent tortuosity values obtained with each technique are employed to assess the anisotropy of the evaluated samples. We tested the introduced workflow on dual energy whole-core CT-scan images and on smaller scale micro-CT-scan images. The whole-core CT-scan images were obtained from a siliciclastic depth interval, composed mainly by spiculites. Micro-CT-scan images we obtained from Berea Sandstone and Austin Chalk formations. We observed numerical differences in the estimates of direction-dependent electrical, diffusional, and hydraulic tortuosity for both types of image data employed. The highest numerical differences were observed when comparing electrical and hydraulic tortuosity with diffusional tortuosity. The observed differences were significant specially in anisotropic samples. The documented comparison provides useful insight in the selection process of techniques for estimation of tortuosity. The use of core-scale image data in the proposed workflow provides semi-continuous estimates of tortuosity and tortuosity anisotropy which is typically not attainable when using pore-scale images. Additionally, the semi-continuous nature of the tortuosity and tortuosity anisotropy estimates in whole-core CT-scan image data provides an excellent tool for the selection of core plugs coring locations.

In an era of increasing energy demand, declining oil fields and fluctuating crude oil prices globally, most oil companies are looking forward to implementing cost effective and environmentally sustainable enhanced oil recovery (EOR) techniques such as low salinity waterflooding (LSWF) and microbial EOR (MEOR). The present study numerically investigates the combined influence of simultaneous LSWF and microbial flooding for in-Situ MEOR in tertiary mode within a sandstone core under spatiotemporally fluctuating pH and temperature conditions. The developed black oil model consists of five major coupled submodels: nonlinear heat transport model; ion transport coupled with multiple ion exchange (MIE) involving uncomplexed cations and anions; pH variation with salinity and temperature; coupled reactive transport of injected substrates, Pseudomonas putida and produced biosurfactants with microbial maximum specific growth rate varying with temperature, salinity and pH; relative permeability and fractional flow curve variations due to interfacial tension reduction and wettability alteration (WA) by LSWF and biofilm deposition. The governing equations are solved using finite difference technique. Operator splitting and bisection methods are adopted to solve the MIE-transport model. The present model is found to be numerically stable and agree well with previously published experimental and analytical results. In the proposed MIE-transport mechanism, decreasing injection water salinity (IWS) from 2.52 to 0.32 M causes enhanced Ca 2+ desorption rendering rock surface towards more water wet. Consequently, oil relative permeability (k ro ) increases with >55% reduction in water fractional flow (f w ) at water saturation of 0.5 from the initial oil-wet condition. Further reducing IWS to 0.03 M causes Ca 2+ adsorption shifting the surface wettability towards more oil-wet thus increasing f w by 52%. Formation water salinity (FWS) showed minor impact on WA with <5% decrease in f w when FWS is reduced from 3.15 to 1.05 M. During LSAMF, biosurfactant production is enhanced by >63% on reducing IWS from 2.52 to 0.32 M with negligible increase on further reducing IWS and FWS. This might be due to limiting nonisothermal (40 to 55 °C) and nutrient availability conditions. LSAMF caused significant WA, increase in k ro with f w reduction by >84%. Though pH increased from 8.0 to 8.9, it showed minor impact on microbial metabolism. Formation damage due to bioplugging observed near injection point is compensated by effective migration of biosurfactants deep within sandstone core. The present study is a novel attempt to show synergistic effect of LSAMF over LSWF in enhancing oil mobility and recovery at core scale by simultaneously addressing complex crude oil-rock-brine chemistry and critical thermodynamic parameters that govern MEOR efficiency within a typical sandstone formation. The present model with relatively lower computational cost and running time improves the predictive capability to pre-select potential field candidates for successful LSAMF implementation.

Recovery from gas condensate reservoirs, when the pressure is below dew point pressure (P dew ), is adversely affected by the accumulation of condensate in the near wellbore region. The mitigation of the near-well bore condensate banking is the main purpose of any enhanced recovery method implemented in gas condensate reservoirs. In this work, a new method was tested to improve condensate recovery by using a chemical that was delivered using hydrocarbon gas as a carrier into a very low permeability and very low porosity reservoir rock. Chemicals are typically injected using liquid carrier solvents. The use of hydrocarbon gas as the carrier provides a remedy to mitigate condensate banking in very low permeability cores by minimizing complications associated with low injectivity and back flow clean-up process requirements of an injected liquid. The chemical potential was evaluated by recording production data from unsteady-state coreflood experiments. The injection of the chemical with equilibrated gas resulted in condensate saturation to decrease from 19.6% to 6.5%. This decrease was not instantaneous and took some time to occur indicating that the chemical needs time to interact with the resident fluid and rock. The benefit of the method, at the field scale, was also estimated by performing single-well numerical simulations that use relative permeability (kr) data which history matched the measured coreflood production data. The results of these preliminary simulations also showed improved recovery of gas and condensate compared to pure depletion, without chemical, by around 40% for the cases considered.

This study investigated the ability to produce accurate multiphase flow profiles simulating the response of producing reservoirs, using Generative Deep Learning (GDL) methods. Historical production data from numerical simulators were used to train a GDL model that was then used to predict the output of new wells in unseen locations. This work describes a procedure in which data analysis techniques are used to gain insight into reservoir flow behavior at a field level based on existing historical data. The procedure includes clustering, dimensionality reduction, correlation, in addition to novel interpretation methodologies that synthesize the results from reservoir simulation output, characterizing flow conditions. The insight was then used to build and train a GDL algorithm that reproduces the multiphase reservoir behavior for unseen operational conditions with high accuracy. The trained algorithm can be used to further generate new predictions of the reservoir response under operational conditions for which we do not have previous examples in the training data set. We found that the GDL algorithm can be used as a robust multiphase flow simulator. In addition, we showed that the physics of flow can be captured and manipulated in the GDL latent space after training to reproduce different physical effects that did not exist in the original training data set. Applying the methodology to the problem of determining multiphase production rate from new producing wells in undrilled locations showed positive results. The methodology was tested successfully in predicting multiphase production under different scenarios including multiwell channelized and heterogeneous reservoirs. Comparison with other shallow supervised algorithms demonstrated improvements realized by the proposed methodology, compared to existing methods. The study developed a novel methodology to interpret both data and GDL algorithms, geared towards improving reservoir management. The method was able to predict the performance of new wells in previously undrilled locations without using a reservoir simulator.

The potential of tuned-composition waterflooding to enhance oil recovery from carbonate reservoirs has been widely investigated in the literature. The consensus is that wettability alteration occurs because of the electrostatic interactions between the carbonate rock surface and the potential determining ions, Ca 2+ , Mg 2+ , CO 3 2 − , and SO 4 2 − . Recently, glycine, the simplest amino acid, has also been investigated as a wettability modifier for carbonates that acts similarly as the sulfate ions in brine. The impact of wettability modifiers like glycine and calcite's potential determining ions has been described by surface complexation models (SCM) and the wetting-state of the rock has been related to change of the surface potential. However, determining the relevance of the geochemical reactions is obstructed by the complexity of the SCM. Moreover, the surface potential as a surrogate of the wetting-state of the rock does not correlate with the experimental results with glycine reported in the literature. The present research analyzed the results of single-phase displacement using a SCM for calcite to determine the important surface complexation reactions. Then, wettability alteration is modeled as a set of anion exchange reactions between wettability modifiers, like SO 4 2 − and Gly − , and adsorbed carboxylic acids. Finally, analytical solutions are presented for the coupled two-phase and multicomponent reactive-transport model with anion exchange reactions.

Hydrocarbon production is commonly associated as the dispersed flow of two and more immiscible phases starting from porous media to surface facilities. In the dispersed flow, one phase is usually dispersed into another dominating phase in terms of droplets. Accurate prediction of the droplet size distribution of a dispersed phase is critical in characterizing complex flow behavior in pipe flows. In the first part of this paper, we provide the analyses of open-source experimental data on the maximum droplet size in gas-liquid annular flow and evaluate the existing theoretical models and suggest an improvement based on the experimental data analyses to predict the maximum droplet size of the entrained liquid droplets in gas-liquid annular flow. In the second part of this paper, we cover the experimental results from the open-source literature data and in-house experimental data to give the general understanding on droplet formation concepts and evaluate the existing predictive models and present a new modeling approach to determine a maximum stable droplet size of the dispersed phase in the liquid-liquid dispersed flow under turbulent flow conditions.

Rock heterogeneities, such as variations in pore distribution, pore throat diameter, and initial permeability, significantly affect the outcome of carbonate matrix stimulation treatments. A better understanding of the influence of these parameters on stimulation and diversion, especially for the performance of self-diverting acids, is needed for efficient stimulation designs. Carbonate rock samples from six outcrop formations, with permeability ranging from 2 to 150 md, were used in the study. Large blocks were acquired for each outcrop, and several 1.5×6-in. core plugs were drilled from these blocks. Pore structure in each outcrop was characterized by high-pressure mercury injection (HPMI) porosimetry and flowing fraction measured with nondestructive tracer tests. Pore volume to breakthrough (PV bt ) for a viscoelastic self-diverting (VES) acid was determined at 150°F for injection rates ranging from 1 to 10 cm 3 /min. The diversion ability for the VES acid was evaluated by (1) the increase in pressure during VES acid injection and (2) the pore volumes this higher pressure was maintained. The results show that flowing fractions measured by injection of either KCl (potassium chloride) tracer in deionized water or a dilute polymer solution is an effective means for characterizing the pore structure and for predicting the pore volume to breakthrough and diversion performance of VES acids. High-permeability grainstones such as Indiana Limestone, where most of the rock porosity is accessible to aqueous fluids (high flowing fraction), have the largest pore volume to breakthrough and the largest relative pressure buildup during injection of VES acids. Low-permeability rocks with heterogeneous porosity (low flowing fraction) have lower pore volume to breakthrough and had a relatively low-pressure build-up. The results are summarized in a master-curve, which facilitates prediction of pore volume to breakthrough of VES acids from rock properties that can be measured by non-destructive techniques. Correlations for PV bt and the diversion ability of the VES acid are presented, so that the performance of these acid systems can be estimated for formation rocks where direct measuremets of PV bt or diversion are not be practical.

Recent studies have shown the utility of the Fast Marching Method and the Diffusive Time of Flight for the rapid simulation and analysis of Unconventional reservoirs, where the time scale for pressure transients are long and field developments are dominated by single well performance. We show that similar fast simulation and multi-well modeling approaches can be developed utilizing the PSS pressure as a spatial coordinate, providing an extension to both Conventional and Unconventional reservoir analysis. We reformulate the multi-dimensional multi-phase flow equations using the PSS pressure drop as a spatial coordinate. Properties are obtained by coarsening and upscaling a fine scale 3D reservoir model, and are then used to obtain fast single well simulation models. We also develop new 1D solutions to the Eikonal equation that are aligned with the PSS discretization, which better represent superposition and finite sized boundary effects than the original 3D Eikonal equation. These solutions allow the use of superposition to extend the single well results to multiple wells. The new solutions to the Eikonal equation more accurately represent multi-fracture interference for a horizontal MTFW well, the effects of strong heterogeneity, and finite reservoir extent than those obtained by the Fast Marching Method. The new methodologies are validated against a series of increasingly heterogeneous synthetic examples, with vertical and horizontal wells. We find that the results are systematically more accurate than those based upon the Diffusive Time of Flight, especially as the wells are placed closer to the reservoir boundary or as heterogeneity increases. The approach is applied to the Brugge benchmark study. We consider the history matching stage of the study and utilize the multi-well fast modeling approach to determine the rank quality of the 100+ static realizations provided in the benchmark dataset against historical data. The multi-well calculation uses superposition to obtain a direct calculation of the interaction of the rates and pressures of the wells without the need to explicitly solve flow equations within the reservoir model. The ranked realizations are then compared against full field simulation to demonstrate the significant reduction in simulation cost and the corresponding ability to explore the subsurface uncertainty more extensively. We demonstrate two completely new methods for rapid reservoir analysis, based upon the use of the PSS pressure as a spatial coordinate. The first approach demonstrates the utility of rapid single well flow simulation, with improved accuracy compared to the use of the Diffusive Time of Flight. We are also able to reformulate and solve the Eikonal equation in these coordinates, giving a rapid analytic method of transient flow analysis for both single and multi-well modeling.

A common challenge in exploration in the North Slope of Alaska is the formation evaluation of low-permeability formations when near-wellbore damage is caused by water-based muds (WBM). This study describes the novel application of existing technology to collect high-quality hydrocarbon samples efficiently in these challenging conditions. The concept was tested with a wireline formation tester in a well with severe formation damage caused by WBM. The procedure and hardware used are discussed and an example of the effectiveness of the proposed technique is shown. Due to the unfavorable mobility ratio, WBM filtrates tends to move preferentially while attempting oil sampling in low permeability rock leading to long station times during wireline formation testing operations. To overcome this challenge, a target sampling interval was subjected to high drawdown using a 3D radial probe to move the target phase closer to the wellbore. Once hydrocarbon was detected in the fluid analyzer, the 3D radial probe was retracted, and the string repositioned to cover the same interval with a straddle packer assembly. Straddle packers provide wellbore annular space for filtrate and hydrocarbon to segregate after the flow period is resumed. When hydrocarbons are again seen in the fluid analyzer, a simultaneous two-pump flow is used to collect them and discard the filtrate. The combination of 3D radial probe and straddle packer assists with displacing the mud filtrate, bringing the target hydrocarbons to the wellbore, and enables the collection of segregated samples with exceptional quality. After pumping at one sampling station using the 3D Radial probe, the maximum hydrocarbon fraction observed was 5%. When the straddle packer was positioned at the same interval, the fluid analyzer showed that the low velocity in the annular space between tool's mandrel and wellbore enabled hydrocarbon segregation from the filtrate due to the existing density contrast. When the hydrocarbon in the wellbore reached the straddle packer inlet, the lower pump was used to flow most of the filtrate in the down direction at high rate. Meanwhile, the hydrocarbon was "skimmed off" and placed in sample containers at a much lower rate using the upper pump. Laboratory results confirmed that the samples collected with the traditional sampling method contained 95% filtrate whereas the samples collected with our technique contained 90% hydrocarbon. Downhole fluid segregation using single-inlet, wireline straddle packer and dual-pump action has not been found in the literature. Recent developments in wireline formation testing use dual inlets in straddle packer modules to enable downhole segregation. We consider that the technique described here innovatively uses the capabilities of current formation testers to collect high-quality hydrocarbon samples in low permeability conditions. With minor adjustments, this technique can also be applied in gas or water sampling in wells drilled with oil-based muds.

The Mishrif formation in west Kuwait is a tight carbonate reservoir having low oil mobility. It is fractured and heterogeneous with wide variation in porosity ranging from 10 to 25%, matrix permeability of about 0.1 to 10 md, and 20°API oil. Production tests and geomechanical study results have revealed that productivity is mostly from the high-permeability matrix and critically stressed fracture networks. Recently, the Mishrif development has been dominated by horizontal wells to maximize reservoir contact and enhance productivity. However, a challenge in such openhole completion is the stimulation strategy requiring effective diversion technology due to the uneven acid distribution along the lateral section. To address those challenges, a novel engineered workflow has been implemented relying on distributed temperature sensing (DTS) to assess the fluid coverage across the openhole section. Results enable identifying high- and low-intake zones, segmenting the uncased section into intervals requiring different levels of stimulation, and making informed decisions regarding diversion requirements. The intervention was conducted in two stages. Coiled tubing (CT) was the selected fluid conveyance method on the first stage given its capacity for more controlled fluid placement, and high-rate bullheading stimulation was selected for the second stage. During the treatment, multiple challenges were faced, mainly driven by a high-permeability streak identified by the DTS near the heel of the lateral. The CT stimulation procedures were modified on the spot, and measures were taken to minimize the impact on the thief zone, which included a combination of diversion techniques, such as high-pressure jetting, dual injection, and pumping of a near-wellbore nonreactive diverter, which is composed of a customized blend of multimodal particles and degradable fibers to minimize fluid leakoff into the high-intake zone. Likewise, real-time downhole telemetry was crucial throughout the CT stimulation because it allowed the highest injection rate possible below the preset pressure limits, continuous monitoring of downhole dynamics along the intervention, and optimal actuation of the high-pressure jetting tool. Upon completion of the CT stimulation, a second DTS log was carried out to evaluate the fluid coverage and effectiveness of the diversion strategy, enabling further adjustment of the bullhead stimulation program. This stimulation workflow implemented in west Kuwait represents a cost-effective alternative to stimulate openhole tight carbonates. This study brings new perspectives for treating complex reservoirs in the region, and shares lessons learned for future interventions.

Oil-wetness and heterogeneity (i.e., existence of low and high permeability regions) are two main factors that result in low oil recovery by waterflood in carbonate reservoirs. The injected water is likely to flow through high permeability regions and bypass the oil in low permeability matrix. In this study, systematic coreflood tests were carried out in both "homogeneous" cores and "heterogeneous" cores. The heterogeneous coreflood test was proposed to model the heterogeneity of carbonate reservoirs, bypassing in low-permeability matrix during waterfloods, and dynamic imbibition of surfactant into the low-permeability matrix. The results of homogeneous coreflood tests showed that both secondary-waterflood and secondary-surfactant flood can achieve high oil recovery (>50%) from relatively homogenous cores. A shut-in phase after the surfactant injection resulted in an additional oil recovery, which suggests enough time should be allowed while using surfactants for wettability alteration. The core with a higher extent of heterogeneity produced lower oil recovery to waterflood in the coreflood tests. Final oil recovery from the matrix depends on matrix permeability as well as the rock heterogeneity. The results of heterogeneous coreflood tests showed that a slow surfactant injection (dynamic imbibition) can significantly improve the oil recovery if the oil-wet reservoir is not well-swept.

The radius of investigation (ROI) of pressure transient analyses has been traditionally assessed using analytical formulations with basic reservoir parameters for homogenous systems. Numerous studies aimed to improve ROI formulations to incorporate all reservoir and testing parameters such as gauge resolution and rate for more accurate ROI assessments. However, new generation wireline formation testers aim to improve deep transient tests with significant developments in gauge resolution and increasing rate. Challenges still remain in heterogeneous formations such as shaly sands and carbonate reservoirs. In this study, detailed conceptual high-resolution numerical models are set up, including comprehensive reservoir and measurement parameters, to investigate more realistic ROI assessments in layered heterogeneous systems without and with hydraulic communication. Several conceptual examples are presented in layered systems with permeability contrasts. In addition, deviation from infinite-acting radial flow (IAFR) and pressure propagation in highly heterogeneous layered systems are investigated to detect the presence of geological features, including closed boundary systems and the presence of a fault in the proximity of wellbore.

With the expanding offshore rig activity in United Arab Emirates leading to an increased number of horizontal wells and longer drains, coupled with changing rock fabrics, it became imperative to diverge from the existing stimulation methods to deliver more consistent and reliable results. These results were achieved via the introduction of single-phase retarded acid (SPRA) and viscoelastic diverting acid (VEDA) to both active and shut-in wells offshore. The introduction of SPRA and VEDA was possible after extensive laboratory testing including core flow tests, solubility tests, emulsion tendency testing, and corrosion inhibition tests to evaluate and benchmark the performance of these blends in comparison to the existing acid recipes such as plain HCl and polymer-based diverted acid. These tests showed that a combination of SPRA and VEDA would allow maximizing lateral coverage and enhance acid penetration due to the reduced rate of reaction and chemical diversion capabilities from thief zones. Combining the introduction of SPRA and VEDA with a shift to bullheading and higher pumping rates enabled the delivery of previously unachievable production results at sustainable wellhead pressures or even well revival of shut-in wells. In addition, reduction of acid content for dolomite stimulation was possible due to the implementation of acid retardation, which also allowed protecting wellheads from exposure to higher acid concentrations while bullheading. Treatment parameters such as volumes, rates, and acid/diverter sequence and ratio were then adjusted for optimal wormhole penetration across all zones using a new carbonate matrix acidizing modeling software. Post-treatment evaluation for the cases of previously shut-in wells has proven the success of the SPRA and VEDA combination. Shut-in wells that were unable to produce sustainably at the required tubing-head pressure (production flowline pressure), were able to produce sustainably with a 100% increase in production compared to prestimulation testing. Similarly, for gas wells, the combination of SPRA and VEDA resulted in a 50% increase in production at a similar bottomhole pressure. In addition, water injectors have also exhibited sustainably increased levels of injectivity compared to prestimulation levels, leading to better sweepage. The novelty of this paper is the comparison between historical carbonate stimulation results in UAE using plain HCl acid with polymer-based diverted acid and using SPRA with VEDA. It also sheds light on the game-changing solutions that suit the ever-increasing challenges observed in offshore oil and gas wells including well placement, lithology, permeability contrast, and type of hydrocarbon within the various target sublayers.

The development of carbonate reservoirs of a giant field, Offshore Abu Dhabi, requires long horizontal wells to maximize productivity, but at the risk of unwanted gas and water channeling through its inherent heterogeneities. Conformance can be enhanced with dedicated segmented completions (blank sections, Inflow Control Device, Autonomous Inflow Control Device, etc.) or selective acid stimulation (diverter, Limited Entry Liner), which are increasingly implemented to extend well life, and eventually well value. If these technologies have matured, success depends heavily on the quality of the formation knowledge prior to completion. As of today, conventional logs provide the basic ground, but they lack dynamic information, whereas production logging results are obtained too late, when the well is already completed. Initially introduced for the optimization of unconventional well completions (see Jacques et al, URTEC 2019), the Well Testing Logging (WTLog) offers the advantage to record a log of mobility, at the end of drilling the openhole, enabling a favorable timing to influence adapted completion and stimulation design. Contrasted viscosity brines are sequentially circulated through the drill pipes at a constant rate and back-produced from the casing at constant pressure. The fluids interface travels in the drain from the TD to the casing shoe, and the measurement of the differential formation seepage is interpreted into an injectivity profile. Combined with rate fall-off phase analysis, permeability and skin logs are derived. Lasting a few hours and realized with conventional rig equipment (such as cement pumps, coriolis flowmeters, Managed Pressure Drilling system), it is a nonintrusive, safe, and ultimately low-cost operation. Forward, it can replace costly logging, when aimed at characterizing heterogeneities. Within a year, the two first WTLog pilots of the Middle East were successfully designed and carried out. They targeted two appraisal wells in distinct undeveloped reservoirs (Cretaceous and Upper Jurassic formations) which benefited from rich acquisition programs (Image log, Production log) to benchmark and qualify this technology. After an explanation of the technology principles, this paper describes the design, operations, and results of these pilots. It then focuses on the petrophysical consolidation of the matrix/fracture characterization. It concludes by sharing the learnings and offers insight to what extent it is a promising technology to be applied in Middle East carbonate reservoir developments.

This paper presents a continuum-scale diffusion-based model informed by pore-scale data for gas transport in organic nanoporous media. A mass transfer and adsorption model is developed by considering multiple transport and storage mechanisms, including bulk diffusion and Knudsen diffusion for free phase, surface diffusion for sorbed phase, and multilayer adsorption. The continuum-scale diffusion-based governing equation is developed solely based on free phase concentration for the overall mass conservation of free and sorbed phases, carrying a newly-defined effective diffusion coefficient and a capacity factor to account for multilayer adsorption. Diffusion of free and sorbed phases is coupled through the pore-scale simplified local density method based on the modified Peng-Robinson equation of state for confinement effects. The model is first utilized to analyze pore-scale adsorption data from the krypton (Kr) gas adsorption experiment on graphite. Then we implement the model to conduct sensitivity analysis for the effects of pore size on gas transport for Kr-graphite and methane-coal systems. The model is finally used to study Kr diffusion profiles through a coal matrix obtained through X-ray micro-CT imaging. The results show that the sorbed phase occupies most of the pore space in organic nanoporous media due to multilayer adsorption, and surface diffusion contributes significantly to the total mass flux. Therefore, neglecting the volume of sorbed phase and surface diffusion in organic nanoporous rocks may result in considerable errors. Furthermore, the results reveal that implementing a Langmuir-based model may be erroneous for an organic-rich reservoir with nanopores during the early depletion period when the reservoir pressure is high.

The aim of this study is to demonstrate the value of a fully integrated ensemble-based modeling approach for an onshore field in Abu Dhabi. Model uncertainties are included in both static and dynamic domains and valuable insights are achieved in record time of nine-weeks with very promising results. Workflows are established to honor the recommended static and dynamic modeling processes suited to the complexity of the field. Realistic sedimentological, structural and dynamic reservoir parameter uncertainties are identified and propagated to obtain realistic variability in the reservoir simulator response. These integrated workflows are used to generate an ensemble of equi-probable reservoir models. All realizations in the ensemble are then history-matched simultaneously before carrying out the production predictions using the entire ensemble. Analysis of the updates made during the history-matching process demonstrates valuable insights to the reservoir such as the presence of enhanced permeability streaks. These represent a challenge in the explicit modeling process due to the complex responses on the well log profiles. However, results analysis of the history matched ensemble shows that the location of high permeability updates generated by the history matching process is consistent with geological observations of enhanced permeability streaks in cores and the sequence stratigraphic framework. Additionally, post processing of available PLT data as a blind test show trends of fluid flow along horizontal wells are well captured, increasing confidence in the geologic consistency of the ensemble of models. This modeling approach provides an ensemble of history- matched reservoir models having an excellent match for both field and individual wells’ observed field production data. Furthermore, with the recommended modeling workflows, the generated models are geologically consistent and honor inherent correlations in the input data. Forecast of this ensemble of models enables realistic uncertainties in dynamic responses to be quantified, providing insights for informed reservoir management decisions and risk mitigation. Analysis of forecasted ensemble dynamic responses help evaluating performance of existing infill targets and delineate new infill targets while understanding the associated risks under both static and dynamic uncertainty. Repeatable workflows allow incorporation of new data in a robust manner and accelerates time from model building to decision making.

We aim to find a universal method and/or parameter to quantify impact of overall heterogeneity on waterflood performance. For this purpose, we combined the Lorenz coefficient, horizontal permeability to vertical permeability ratio, and thief zone permeability to average permeability ratio, with a radar chart. The area of the radar chart serves as a single parameter to rank reservoirs according to heterogeneity, and correlates to waterflood performance. The parameters investigated are vertical and horizontal permeability. Average porosity, initial water saturation, and initial diagonal pressure ratio are kept constant. Computer based experiments are used over the course of this entire research. We conducted permeability studies that demonstrate the effects of thief zones and crossflow. After normalizing these parameters into a number between 0 and 1, we then plot them on a radar chart. A reservoir's overall degree of heterogeneity can be inferred using the radar chart area procedure discussed in this study. In general, our simulations illustrate that the larger the radar chart area, the more heterogenous the reservoir is, which in turn yields higher water cut trends and lower recovery factors. Computer simulations done during this study also show that the higher the Lorenz coefficient, the higher the probability of a thief zone to exist. Simulations done to study crossflow also show certain trends with respect to under tonguing and radar chart area.

We measured steady-state liquid (dodecane) permeability in four horizontal core plugs from the middle member of the Bakken Formation at multiple effective stress conditions to investigate how permeability evolves with confining stress and to infer the matrix permeability. Three of the four tested samples behaved almost perfectly elastically as the hysteresis effect was negligible. In contrast, the fourth sample showed a permeability decrease of ~40% at the end of the test program. Our interpretation is that the closure of open artificial micro-fractures initially present in the sample (based on micro-CT imaging) caused that permeability hysteresis. The matrix permeability to dodecane (oil) of the tested samples is between ~50 nD and ~520 nD at the confining pressure of 9500 psi. The 520 nD sample exhibited the lowest porosity, the highest calcite content, and the largest dominant pore throat radii. In contrast, the 50 nD sample was more porous, and exhibited the highest dolomite content and the smallest dominant pore throat radii. This study shows that our multi-stress testing protocol allows the study of the permeability hysteresis effect to interpret the matrix permeability. We also document the presence of middle Bakken lithologies with permeabilities up to one order of magnitude greater than others. These permeable lithologies may have a significant contribution to well production rates.

Formation evaluation in heterogeneous reservoirs can be very challenging especially in fields that extend over several kilometers in area where the permeability varies from 0.1 mD up to 1000 D within the same porosity. The porosity, hydrocarbon saturation and net sand thickness in most of Obaiyed field wells are consistent; hence, the productivity of these wells is enormously dependent on the reservoir permeability. Since the permeability is highly heterogeneous, initial production rate of the wells varies between few MMSCFD to almost one hundred MMSCFD. The huge permeability variation led to a tremendous uncertainty in the dynamic modeling, which resulted in an inaccurate production forecast affecting the field economics estimation. Understanding permeability distribution and heterogeneity in Obaiyed field is the key factor for establishing a realistic permeability model, which will lead to a successful field development strategy. Extensive work was performed to understand key factors that govern the permeability in Obaiyed using the data of 1-kilometer length of cores acquired in more than 50 wells covering different reservoir properties in the field. Core data were used to separate the reservoir into different Hydraulic Flow Units (HFU) according to Amaefule's work performed on the Kozeny-Carmen model. Afterwards, a correlation between the HFU and well logs was established using IPSOM Electro-Facies module in order to define the flow units in un-cored wells. The result of this correlation was used to calibrate a Porosity-Permeability relationship for each flow unit. The next step was examining the clay-type distribution and diagenesis in each flow unit using the petrographic analysis (XRD) results from the core xdata. All factors controlling the permeability can now be represented in hydraulic flow units which are considered as a method of measurement of the reservoir quality. Consequently, property maps were constructed showing the location and continuity of each of the flow units, leading to a more deterministic approach in the well placement process. Based on this new work methodology, a production cut-off criteria relating the reservoir productivity to both clay minerals presence and percentages was established for multiple wells scenarios. As a result, the development strategy of the field changed from only vertical wells to include horizontal wells as well which proved to be the only economic approach to produce the Illite dominated zones. This paper presents a workflow to provide a representative estimation of permeability in extremely heterogeneous reservoirs especially the ones dominated by complex clay distribution.