bluuebunny/crossref_metadata_2025 huggingface dataset:
Heterogeneity Effects on Low Salinity Water Flooding
Authors: Al-Ibadi Hasan , Stephen Karl , Mackay Eric
Published: June 2020

We investigate the effect of heterogeneous petrophysical properties on Low Salinity Water Flooding (LSWF). We considered reservoir scale models, where the geological properties were obtained from a giant Middle East carbonate reservoir. The results are compared against a typical sandstone model.

We simulated low salinity induced wettability changes in field scale models in which the petrophysical properties were randomly distributed with spatial correlation. We examined a wide range of geological realisations which mimic complex geological structures. Sandstone was simulated using a log-linear porosity-permeability relation with fairly good correlation. A carbonate reservoir from the Middle East was simulated where a much less correlated porosity permeability relationship was obtained. The salinity of formation water was set to typically observed values for the sandstone and carbonate cases. A number of simulations were then carried out to assess the flow behaviour.

We have found that the general trend of permeability-porosity correlation has a key role that could mitigate or aggravate the impact of spatial distributions of petrophysical properties. We considered models with a log-linear permeability-porosity correlation, as generally observed for sandstone reservoirs. These are likely to be directly affected by the spatial distribution more than models with a power permeability-porosity correlation, which is often reported for flow units of carbonate reservoirs. The scatter of data in the permeability-porosity correlations had a relatively small impact on the flow performance. On the other hand, the effect of heterogeneity decreases with the width of the effective salinity range. Thus, uncertainty in carbonate reservoirs arises due to the ambiguity of spatial distribution of permeability and porosity would be less affects the LSWF predictability than in sandstone case. Overall, the incremental oil recovery due to LSWF was higher in the carbonate models than the sandstone cases. We observe from uncertainty analysis that the formation waterfront was less fingered than the low salinity waterfront and the salinity concentration. The dispersivity of salinity front and the water cut can be estimated for models with various degrees of heterogeneity.

The outcome of the study is a better understanding of the implications of heterogeneity on LSWF. In some cases the behaviour can appear like a waterflood in very heterogeneous cases. It is important to assess the reservoir effectively to determine the best business decision.
Understanding the Spatial Relationships that Trigger Movements in Regulatory Frameworks Through Time
Authors: Moridis Nefeli , Lee W. John , Sim Wayne , Blasingame Thomas
Published: June 2020

The first objective of this work is to determine the volume of hydrocarbon that can be moved from Resources other than Reserves (ROTR) to Reserves, or from Proved Undeveloped Reserves (PUD) to Reserves based on well placement. The second objective is to create a model that incorporates the production history and forecasted estimated ultimate recovery (EUR), in this case by implementing multi-segment decline curve analysis (DCA) as presented in URTeC 336 (Moridis et al.(2), 2019). To perform this analysis, we selected 38 wells from a Permian Basin dataset available to Texas A&M University.

The first portion of this work involves running a sensitivity analysis to determine the spatial well relationships that may trigger movements in certain regulatory frameworks. A successful well may promote the offsetting 2P wells to PUD wells. We incorporate the methodology in SPEE Monograph 3 (2013) for estimating PUD volumes beyond immediate offset locations that can be used to estimate the Reserves and possibly Contingent Resources in some situations. The question we aim to answer is: How do we move the PUDs to proved developed producing (PDP) Reserves?

In the second part of this work, we create a model which includes the production history and the forecasted EURs. As time moves forward, continuity and consistency must be maintained across the model. Assume the following scenario: we plan to move a volume "x" from 1C Contingent Resources to1P Reserves, but we can only book 0.7 x as 1P Reserves. The model must reflect the fraction of the volume x that was actually moved and how it depends on, for example, commodity price contingencies. The remaining 0.3 x volume that was not classified as Reserves must be accounted in the model. The continuity of the model through time will track the volumes, and it needs to be able to do so consistently.
Improving Reservoir Development by Integrating Reservoir Navigation Interpretations into Sub-Surface 3D Models
Authors: Austin Simon , Wang Xuandong , Ferreira Enrico , Vetsak Alex
Published: June 2020

Reservoir navigation, often referred to as geosteering, is commonly used to optimize the placement of highly deviated wells. This technology has contributed significantly to the prolongation and economic well-being of mature hydrocarbon provinces around the world and been a major enabler for the commercial success of unconventional reservoirs.

The reservoir information and analysis obtained during reservoir navigation is extensive and very valuable, yet is known to sometimes remain unused. Part of the reason is the complexity of reservoir navigation data and the limitations that many geosteering software applications cannot integrate the information provided from this data to update seismic-based 3D models.

This paper demonstrates a fast and effective method of utilizing spatial reservoir navigation information to improve the three-dimensional understanding of producing reservoirs. Reservoir navigation interpretations from one or more wells can be used as inputs. The results include updated structure maps, refined gross rock volume (eg shale volume in unconventional reservoirs), updated values for porosity and water saturation and ultimately a revised volumetrics calculation. The results can be compared with calculations from other methods such as material balance and decline curves. Analyzing conflicting field data and reconciling them creates opportunities for improved drilling opportunities and better reservoir development. Datasets used in the paper show some specific examples of how the 3D workflows lead to better field developments with enhanced drilling operations and improving recovery factors.

In the future, significant technical developments are expected in the type and complexity of reservoir navigation data originating from logging while drilling (LWD) tools. These data types will easily be included in the new 3D workflows without introducing undue complexity.

Integrating reservoir navigation interpretations into sub-surface 3D models can be of benefit for real time drilling operations and also for field studies. The method uses a 3D workflow that can be completed easily and is fast enough to update models in real time. It is therefore useful for the purposes of improving architectural and geomorphological understanding of an area larger in scale than just the immediate active well. This creates an information rich environment with insightful information during geosteering real time jobs for better decisions. Additionally, the analysis method can be performed as a field study. This more comprehensive approach allows integration with other information after drilling operations have ceased to improve resource recovery and pick better future drilling targets.
Automated Interpretation Tool for Synchronous History Matching of Multiple Scal Experiments with Advance Nurbs Representations of Relevant Functions
Authors: Manasipov Roman , Jenei Bettina
Published: June 2020

Relative permeability and capillary pressure are the key parameters of the multiphase flow in a reservoir. To ensure an accurate determination of these functions in the areas of interest, the core flooding and centrifuge experiments on the relevant core samples need to be interpreted meticulously. In this work, relative permeability and capillary pressure functions are determined synchronously by history matching of multiple experiments simultaneously in order to increase the precision of results based on additional constraints coming from extra measurements.

To take into account the underlying physics without making crude assumptions, the Special Core Analysis (SCAL) experiments are chosen to be simulated instead of using well know simplified analytical or semi-analytical solutions. Corresponding numerical models are implemented with MRST (Lie, 2019) library. The history matching approach is based on the adjoint gradient method for the constrained optimization problem. Relative permeability and capillary pressure curves, which are the objectives of history matching, within current implementation can have a variety of representations as Corey, LET, B-Splines and NURBS. For the purpose of analyzing the influence of correlations on the history matching results in this study, the interpretation process with assumed analytical correlations is compared to history matching based on generic NURBS representation of relevant functions.
A Study on the Adsorption Behavior of Different Surfactants in Carbonate Using Different Techniques
Authors: AlMatouq Hana , Almubarak Majed , Algadrah Abdulkarem , Alhodaythi Waleed
Published: June 2020

Surfactant based foams are used as one of the most effective techniques in controlling gas mobility during gas injection processes. Foam reduces gas mobility in porous media by increasing the gas apparent viscosity and decreasing the gas relative permeability, and hence it helps in improving sweep efficiency. However, one of the critical encounters when using foam in reservoirs is the adsorption of the surfactant on the rock surface. The loss of surfactant to the rock surface will lead to destabilizing the foam and accelerating the collapse rate of foam films. The objective of this paper is to study the behavior of surfactant adsorption in carbonate.

The adsorption of various surfactants in contact with carbonate was evaluated. We compared two different techniques to evaluate the adsorption of surfactant components onto the rock surface. The first method is using a total organic carbon (TOC) analyzer to measure the carbon number in each surfactant over time after being in contact with rock. The second method is using UV-spectroscopy in which the light absorbance at a certain wavelength is measured. The measurements are then used to calculate the total surfactant adsorption onto the rock surface. This paper presents the adsorption behavior of each surfactant studied in detail.

The results obtained by the techniques were compared for two different surfactants. An amphoteric surfactant and an anionic surfactant were used in this study. Results illustrated that both surfactants were adsorbed by the rock minerals. Surfactant 1 showed a higher adsorption value than the surfactant 2. However, the two used techniques to measure the adsorption showed different adsorption values for both surfactants. Using TOC, surfactants 1 and 2 showed a total adsorption of 0.746 and 0.428 mg/grock, respectively. While, using UV-spectroscopy, surfactants 1 and 2 showed a total adsorption of 1.149 and 0.306 mg/grock, respectively.

Understanding the surfactant adsorption behavior is an essential step in the surfactant selection process. Selecting a surfactant with minimal loss to the rock surfaces will lead to keeping the generated foam stable for a longer time in the reservoir and therefore, result in having a higher sweep efficiency.
Optimisation of Polymer Flooding in a Heterogeneous Reservoir Considering Geological and History Matching Uncertainties
Authors: Ibiam Emmanuel , Geiger Sebastian , Demyanov Vasily , Arnold Dan
Published: June 2020

Polymer flooding offers the potential to recover more oil from reservoirs but requires significant investments which necessitate a robust analysis of economic upsides and downsides. Key uncertainties in designing a polymer flood are often reservoir geology and polymer degradation. The objective of this study is to understand the impact of geological uncertainties and history matching techniques on designing the optimal strategy and quantifying the economic risks of polymer flooding in a heterogeneous clastic reservoir.

We applied two different history matching techniques (adjoint-based and a stochastic algorithm) to match data from a prolonged waterflood in the Watt Field, a semi-synthetic reservoir that contains a wide range of geological and interpretational uncertainties. An ensemble of reservoir models is available for the Watt Field, and history matching was carried out for the entire ensemble using both techniques. Next, sensitivity studies were carried out to identify first-order parameters that impact the Net Present Value (NPV). These parameters were then deployed in an experimental design study using a Latin Hypercube to generate training runs from which a proxy model was created. The proxy model was constructed using polynomial regression and validated using further full-physics simulations. A particle swarm optimisation algorithm was then used to optimize the NPV for the polymer flood. The same approach was used to optimise a standard water flood for comparison. Optimisations of the polymer flood and water flood were performed for the history matched model ensemble and the original ensemble.

The sensitivity studies showed that polymer concentration, location of polymer injection wells and time to commence polymer injection are key to optimizing the polymer flood. The optimal strategy to deploy the polymer flood and maximize NPV varies based on the history matching technique. The average NPV is predicted to be higher in the stochastic history matching compared to the adjoint technique. The variance in NPV is also higher for the stochastic history matching technique. This is due to the ability of the stochastic algorithm to explore the parameter space more broadly, which created situations where the oil in place is shifted upwards, resulting in higher NPV. Optimizing a history matched ensemble leads to a narrow variance in absolute NPV compared to history matching the original ensemble. This is because the uncertainties associated with polymer degradation are not captured during history matching. The result of cross comparison, where an optimal polymer design strategy for one ensemble member is deployed to the other ensemble members, predicted a decline in NPV but surprisingly still shows that the overall NPV is higher than for an optimized water food. This indicates that a polymer flood could be beneficial compared to a water flood, even if geological uncertainties are not captured properly.
Dynamic Immiscible Flood Monitoring in Sand Packs Via Frequency Domain Reflectometry
Authors: Kuznetcov Ilia , Kantzas Apostolos , Bryant Steven
Published: June 2020

Dynamic saturation distribution of fluids in oil reservoirs is arguably the most important piece of information petroleum engineers and geophysicists need. It allows them to better characterize oil fields, choose right enhanced oil recovery techniques and make accurate recovery forecasts. The main objective of the present paper is to develop and test a novel non-intrusive technology that enables real time in-situ monitoring of fluid saturations in porous media during immiscible floods.

To achieve this goal we designed, constructed and commissioned a high pressure (up to 25MPa) and temperature (up to 200°C) core-holder with an antenna that allows for low power electromagnetic sweeps in the radio frequency range. A novel inversion algorithm was created and incorporated with our core-holder-pump system that enables dynamic acquisition of the oil and water saturations. Experiments were conducted through sand packs saturated with water and then displaced with oils of varying viscosity (drainage) followed by water flooding (imbibition). Reflection and transmission coefficients in the frequency domain were measured while flooding using a commercial vector network analyzer connected to the core holder. Recorded frequency data was processed with the novel high-resolution inversion technique to obtain impulse reflection and transmission responses in the time domain. These responses were further normalized to dynamically track the water-oil volumetric saturations within the porous media. Every displacement experiment has been performed in both vertical and horizontal positions to emulate water-oil override and underride scenarios. Material balance calculations were performed to validate fluid saturation profiles for all imbibition and drainage experiments every 5 % of the pore volume of the fluids injected.

Frequency domain reflection and transmission electromagnetic responses were measured every 1 % of the fluid injected. Material balance was used to validate the measured saturation profiles. The goodness of fit was calculated between these two independent measurements for every flood experiment performed. The mean-square error was calculated to be around 1.26% of the total pore volume on average. Late breakthroughs and piston-like displacement were observed in the floods with favorable mobility ratios. In contrast, much earlier breakthroughs have been registered in all the experiments with unfavorable mobility ratios due to fingering. All our observations are in agreement with the current theory of immiscible displacement in porous media.

The novel automated system paired with the inversion algorithm were developed to allow for virtually real time monitoring of the fluid saturations during imbibition and drainage displacement cycles. Our technology is shown to be a promising candidate to compliment resistive logging measurements in the field.
Deriving Alkali Polymer Parameter Distributions from Core Flooding by Applying Machine Learning in a Bayesian Framework to Simulate Incremental Oil Recovery
Authors: Steineder Dominik , Vanegas Gisela , Clemens Torsten , Zechner Markus
Published: June 2020

Various physico-chemical processes are affecting Alkali Polymer (AP) Flooding. Core floods can be performed to determine ranges for the parameters used in numerical models describing these processes. Because the parameters are uncertain, prior parameter ranges are introduced and the data is conditioned to observed data. It is challenging to determine posterior distributions of the various parameters as they need to be consistent with the different sets of data that are observed (e.g. pressures, oil and water production, chemical concentration at the outlet).

Here, we are applying Machine Learning in a Bayesian Framework to condition parameter ranges to a multitude of observed data.

To generate the response of the parameters, we used a numerical model and applied Latin Hypercube Sampling (2000 simulation runs) from the prior parameter ranges.

To ensure that sufficient parameter combinations of the model comply with various observed data, Machine Learning can be applied. After defining multiple Objective Functions (OF) covering the different observed data (here six different Objective Functions), we used the Random Forest algorithm to generate statistical models for each of the Objective Functions.

Next, parameter combinations which lead to results that are outside of the acceptance limit of the first Objective Function are rejected. Then, resampling is performed and the next Objective Function is applied until the last Objective Function is reached. To account for parameter interactions, the resulting parameter distributions are tested for the limits of all the Objective Functions.

The results show that posterior parameter distributions can be efficiently conditioned to the various sets of observed data. Insensitive parameter ranges are not modified as they are not influenced by the information from the observed data. This is crucial as insensitive parameters in history could become sensitive in the forecast if the production mechanism is changed.

The workflow introduced here can be applied for conditioning parameter ranges of field (re-)development projects to various observed data as well.
Effects of Heterogeneous Local Swelling and Multiple Pore Types on Coal and Shale Permeability Evolution
Authors: Zeng Jie , Liu Jishan , Li Wai , Tian Jianwei , Leong Yee-Kwong , Elsworth Derek , Guo Jianchun
Published: June 2020

The permeability of fractured sorbing media, such as shale and coal, is mainly controlled by effective stresses and sorption-induced strains. Although the influence of effective stresses on permeability has been extensively studied, how sorption-induced strains affect permeability evolution has not been fully understood. Sorption-induced strains can impact the permeability in opposite ways at different time scales. If the swelling occurs at matrix surfaces (local swelling), the swelling strain purely reduces fracture aperture and results in a permeability decline. However, when the whole rock is fully invaded by injected gas, the swelling of the whole rock (global swelling) increases fracture aperture and the bulk volume, enhancing the permeability. Most existing models only use fracture (pore) pressure to describe rock swelling, assuming that the rock is fully invaded and matrix-fracture pressure equilibrium is achieved. They cannot explain some experimental data because rocks may never be fully invaded during permeability measurement. Moreover, different pore types are not considered and local swelling can be heterogeneous due to complex matrix components.

In this paper, the non-equilibrium effects are depicted by defining two continua (matrices and fractures) with distinct pressure values. The transition between local swelling and global swelling is quantified by the pressure difference between the two systems. The larger the pressure difference is, the heavier local swelling effects will be. And global swelling is only a function of fracture pressure. Different pore types are included in our permeability model. And the heterogeneous local swelling strain is characterized by a splitting strain function.

This model is verified against laboratory data from common permeability measurement conditions. Under constant effective stress and constant confining stress conditions, the permeability changes at different times and becomes stable after a relatively long time. With the matrix-fracture pressure difference first increases to a maximum value and then decreases to zero, local swelling effects change from zero to a peak value and finally drop to zero. By combining permeability curves at different injection pressure levels, 3-D permeability surfaces are obtained. The impacts of rock properties, heterogeneous local swelling, and multiple pore types on permeability evolution are analyzed. Adsorption and mechanical properties control specific regions of permeability curves. Effects of heterogeneous local swelling are determined by the adsorption capacity of the dominant matrix component. The existence of multiple pore types makes the permeability curve deviate from those of single-pore-type cases and affects a wider range of permeability curves compared with heterogeneous local swelling.
Wettability Changes and Interfacial Tension Reduction in Alkali Polymer Flooding of High and Low Tan Number Oils
Authors: Arekhov Vladislav , Hincapie Rafael E. , Clemens Torsten
Published: June 2020

Injection of chemicals into sandstones could lead to wettability alteration, where oil characteristics such as the TAN (Total Acid Number) may determine the wetting-state of the reservoir. By combining the spontaneous imbibition principle (Amott-Harvey method) and interfacial tension indexers’ evaluations, we propose a workflow and a comprehensive assessment to evaluate wettability alteration and IFT when injecting chemical EOR agents. The study focused on examining the effect of alkaline and polymer solutions (alone) and alkali-polymer.

The evaluation focused on comparing the effects of chemical agent injection on wettability and IFT due to: core ageing (non-aged, water-wet and aged, neutral to oil-wet); brine composition (no divalent and with divalent ions); core mineralogy (~2.5% and ~10% Clay) and crude-oil type (Low and high TAN). Amott experiments were performed on cleaned water-wet core plugs as well as on samples with restored oil-wet state. IFT experiments were compared for a duration of 300 minutes.

Data was gathered from 48 Amott imbibition experiments with duplicates. IFT and baselines were defined in each case for brine, polymer and alkali on every set of experiments. When focusing on the TAN and aging effects it was observed that in all cases, the early time production is slower and final oil recovery is larger comparing to non-aged core plugs. This data confirms the change of rock surface wettability towards more oil-wet state after ageing and reverse wettability alteration due to chemical injection. Furthermore, application of alkali with high-TAN oil resulted in a low equilibrium IFT. In contrast, alkali alone fails to mobilize trapped low-TAN oil, but causes wettability alteration and neutral-wet state of the aged core plugs. Looking into brine composition, the presence of divalent ions promotes water-wetness of the non- aged core plugs and oil-wetness of the aged core plugs. Divalent ions act as bridges between mineral surface and polar compound of the in-situ created surfactant, hence accelerating wettability alteration. Finally, concerning mineralogy effects, high clay content core plugs are more oil-wet even without ageing. After ageing, a strongly oil-wet behaviour is exhibited. Alkali-polymer is efficient in wettability alteration of oil-wet core plugs towards water-wet state.

Three main points are addressed in the paper: A comprehensive methodology to evaluate wettability and IFT changes for different oil and mineralogy types is presentedIn particular, for alkali injection, substantial wettability change effects are observed.For high TAN number oils, wettability and IFT effects can be quantified using the methodology and applied for screening of chemical agents for various rock types.
On the Role of Molecular Diffusion in Modelling Enhanced Recovery in Unconventional Condensate Reservoirs
Authors: Santiago Carla Jordana , Kantzas Apostolos
Published: June 2020

Molecular diffusion is a transport mechanism often ignored in conventional, non-fractured multi-component petroleum upstream simulations due to the predominance of convection. In unconventional fractured reservoirs, diffusion plays a vital role in hydrocarbon production. A "shale" reservoir is characterized by thin, ultra-tight matrix blocks surrounded by natural or induced fractures. This creates conditions in which diffusion fluxes could be significant. In ultra-tight formations, convection is a slow process, and the presence of thin blocks surrounded by fractures increases the contact area, both of which favors diffusion.

In this paper, we discuss the application of cyclic gas injection to enhance recovery in tight reservoirs in the gas condensate window. A fully implicit model is implemented with the objective to investigate the impact of diffusion on liquid dropout and vaporization on a matrix level. Diffusion fluxes are implemented considering a gradient in total chemical potential as driving force. Additionally, since capillary forces are significant in ultra-tight formations, phase equilibria calculations are modified to account for nano-confinement effects. Sensitivity is performed on matrix block size and injection gas composition (pure C1, a mixture of C1 and CO2, and a mixture of C1, C2 and C3), and the role of diffusion is evaluated for each scenario.

As gas is injected, the composition of heavier hydrocarbon fractions in the gas phase significantly increases due to vaporization of condensate. Molecular diffusion helps to spread composition banks. As a result, liquid dropout is delayed during the subsequent production stages. Heavier fractions remain in the gas phase for longer periods, which ultimately enhances its recovery. In addition to that, retention of heavier fractions due to condensate dropout is intensified as the size of the matrix block increases. Longer matrix blocks result in lower swept length for the same number of cycles. As a result, liquid dropout occurs earlier because feed of gas at in-situ composition diffuses from the center of the matrix block towards the fracture boundary.

We demonstrate that heavier components recovery is more affected by molecular diffusion than lighter components. Furthermore, it is observed that molecular diffusion strongly influences time and location of occurrence of liquid dropout in tight gas condensate reservoirs. Implementation of a rigorous model that includes convection, diffusion, adsorption and phase change allowed to investigate the commingling effects of different physics involved in enhanced recovery in unconventional reservoirs.
Modelling Micro-Proppant Transport in Stress-Sensitive Naturally-Fractured Reservoirs
Authors: Di Vaira Nathan , Leonardi Christopher , Johnson Jr. Raymond
Published: June 2020

Optimal proppant placement is critical to maintaining productivity from stress-sensitive reservoirs, in which gas conductivity depends on the connectivity of the network of secondary fractures to the wellbore. In a colloquial sense, this research places micro-proppants in induced and natural fractures, shows how they are excluded from reaching far into the reservoir, and describes which sizes of proppants this occurs for. Micromechanical modelling of a hydraulic fracturing fluid, in which the hydrodynamics between the fluid and solid phases are fully resolved, is achieved via the lattice Boltzmann method (LBM) for fluids coupled with the discrete element method (DEM) for particles. It is shown that proppant transport along the primary hydraulic fracture channel is strongly inhibited by leak-off into the secondary fracture system. This leak-off is strongly affected by the migration of particles across the fracture width, which in turn is a function of reservoir and treatment properties. A novel numerical approach is proposed for predicting proppant transport through the secondary fracture system, with far-reaching applications to porous media particulate transport.
High Definition Reservoir Mapping Technology Provides a Unique Solution to Map Uncertain Water Contact as an Innovative Approach for Pilot Hole Elimination; Umm Ghudair Field, West Kuwait
Authors: AL-Hajri Nasser Fadghoush , Al-Khaldy Ali Dawood , Hassan Jassim Mohammed , Dashti Reham Abbas , Kader Mohamed Abdulmonem , Gupta Satya Kumar , Al-Buloushi Zainab Abdulkareem , Abdelbaset Shady Moustafa , Siam Mahmoud , Al-Hassan Ahmed , Chang Catherine , Ramadan Zeyad
Published: June 2020

Umm Ghudair Field is one of the major oil producing fields in West Kuwait. Oil was discovered in 1962 in the Lower Cretaceous Minagish Oolite Formation and more than 200 wells have been drilled to exploit this reservoir since then. Stratigraphically, the formation is defined by three units; Lower, Middle and Upper. The lower and upper units are considered non-reservoirs, while the middle one is hydrocarbon bearing. However, because of the continuous production over the past 50 years, the filed started to show a variable rise in its oil water contact (OWC). Consequently, this uncertain OWC rise has impacted the planning and production of the newly drilled wells (deviated and horizontal). Several recently drilled wells showed water breakthrough much earlier than expected.

To address this challenge and with an attempt to proactively predict the current OWC depth in the new wells to be drilled, Kuwait Oil Company (KOC) decided to try the new High Definition Reservoir-Mapping-While-Drilling (HD-RMWD) technology in one of the horizontal well in their field. The objective was to assess the potential of the technology in detecting and mapping the current OWC while landing the well in the target. Due to the ultra-deep detection range of the technology (in excess of 200 ft), the landing point could be adjusted proactively and early enough to accommodate any unexpected OWC depth changes in the field.
Exergoeconomic Optimization of Oil and Gas Production Systems
Authors: Akchiche Meziane , Beauquin Jean-Louis , Sochard Sabine , Serra Sylvain , Reneaume Jean-Michel , Stouffs Pascal
Published: June 2020

In the present paper, we first developed and implemented the exergy analysis within an Integrated Asset Modeling (IAM) platform to evaluate the overall energy efficiency and Greenhouse Gas (GHG) emissions of a future offshore oil production system. The use of the same state function enables a direct comparison of the different irreversibilities that occur through the entire production system (drawdown losses, lift losses, Artificial lift and boosting systems losses, etc.) and thus, provides the necessary guidance for engineers to select the best solution. Then, we modeled and evaluated the performance of the oil production system with three artificial lift and boosting techniques, including multiphase boosting, gas lift, and ESP. In all the cases, liquid production has been maximized while respecting the same constraints. The exergy analysis enabled us to quantify for the first time the physical exergy supplied naturally by the reservoir in the form of pressure (mechanical exergy) and temperature (thermal exergy). After that, we proposed a new methodology to improve the design of petroleum production systems over their whole life. This methodology permits the simultaneous evaluation of a multitude of development schemes by using generic models. Finally, the multi-period exergoeconomic optimization results highlight a performance gap, quite logical, between the most cost-effective scheme identified and the most energy-efficient one. There are hence excellent opportunities for progress by developing the exergy approach and digital tools for the selection and development of greener and more profitable production concepts, processes, and technologies.
Modelling of Multi-Stage Hydraulic Fractured Wells Made Easy in Conventional Reservoir Simulations
Authors: Hoegstoel Haakon , Stoeren Jacob , Sjaastad Magne , Lindkvist Gaute
Published: June 2020

The success in shale oil and gas over the last decade is based on massive multi-stage hydraulic fracturing. Applying the same well concept on conventional tight and low permeable reservoirs can bring economically stranded projects into consideration again. However, simulating production over time for multi-stage hydraulic fractured wells using conventional full-field reservoir simulation models can be challenging. Detailed modelling of the hydraulic fractures comes with a large computational cost and typically a number of convergence issues. Simplified methods fail to capture the full pressure loss from the reservoir into the well. In this work, a method with effective Virtual Perforations is described, enabling both efficient simulation and prediction of well performance. A detailed 2D mesh for each hydraulic fracture is used together with the unmodified reservoir model grid, integrating geomechanical fracture propagation simulation results directly into the reservoir simulation workflow.

The Virtual Perforations are defined by the geometrical intersections between the fractures 2D meshes and the reservoir model 3D grid. The numerical solution of the fracture-to-well inflow system provides a set of effective Virtual Perforations transmissibilities for Darcy flow which can be applied in any standard reservoir simulator. In the reservoir simulation model numerical multipliers, in-active grid blocks or gaps in grid model layers can act as barriers for vertical flow in the fractures. Hence horizontal, fractured wells may not capture the full flow potential in reservoir simulations. In this work, the effective Virtual Perforations are calculated based on the vertical fracture mesh to ensure well flow from the full height of the hydraulic fractures. Using a 2D mesh for the fracture, the fracture geometry can be contained within certain grid model layers or truncated by faults. Matrix condensation methods known from degree-of-freedom reduction in structural analysis, are applied to efficiently calculate all the effective Virtual Perforations transmissibilities. Thus, working with well completion design can be done interactively.

For gas reservoirs, a non-Darcy pressure loss model is established based on the Forchheimer model. Fracture width and proppant inertial flow parameter for a given confinement stress are used to calculate the rate-dependent skin factor for each fracture. The rate-dependent skin factors are provided for the all the Virtual Perforations in such a way that they all get the same additional near wellbore non-Darcy pressure loss.

This work has been implemented in the open-source visualization application ResInsight. The application has been used successfully for well planning in field development projects, including as part of automated workflows for ensembles of reservoir models.
A Rigorous Method for Special Core Analysis SCAL Data Correction in the Presence of Capillary End Effects
Authors: Goodarzian Saleh , Sorbie Kenneth S.
Published: June 2020

One way of obtaining water-oil relative permeability curves is from co-injection (of water and oil) experiments at steady-state (SS) condition. The two-phase Darcy Law can be used to calculate the relative permeability directly only when water saturation is constant along the core. However, the capillary end effect (CEE) causes water accumulation or depletion at the end of the core depending upon the wettability. This work describes an improved method for correcting for this effect by modifying the "intercept method" initially proposed by Gupta and Maloney (2014).

Similar to their work, we again envisage carrying out a steady-state co-injection experiment. For each ratio of water to oil flowrate (F=qwqo), we require experiments at several different total flowrates to be carried out. From each run, we obtain pressure drop across the core and average water saturation inside the core.

We demonstrate mathematically that a plot of pressure difference vs. oil flowrate yields a straight line whose slope gives the oil relative permeability which can be used to calculate water relative permeability. A plot of average water saturation vs. reciprocal of oil flowrate gives a straight line whose intercept is the water saturation associated with the oil/water relative permeability values just obtained. It is necessary to perform the same experiment for at least two values of water and oil flowrates while the ratio is constant since we require at least two points to construct a straight line. The same procedure is used for other values of F to obtain more data points to construct the relative permeability curves. We have also mathematically corrected Gupta and Maloney’s work and other works after them and arrived at a simpler and more rigorous method. The details of how our method builds upon and improves their work will be published in due course (Goodarzian and Sorbie, 2020).
Novel Techniques Enable Successful Gravel Packing of Long Horizontal North Sea Wells
Authors: Firth James Andrew , Hamid Hisham , Saldungary Pedro Martin
Published: June 2020

Open hole gravel packing (OHGP) is one of the primary completion techniques in sandstone reservoirs with sanding tendencies. As companies are becoming more experienced with these operations they are starting to explore the options for completing more challenging wells; including longer open holes and more tortuous trajectories. Conventional techniques have limits when it comes to the maximum length and angles that can be gravel packed based on a defined set of parameters. In order to ensure the success of the gravel packing operations in these challenging wells new techniques need to be adopted.

This paper includes a review of the methods that can be utilised to extend the operating limits of open hole gravel packs, so that they can be used in the long geosteered wells that are becoming more common in the North Sea. It includes a case review of the first well gravel packed in the North Sea using Ultra-Lightweight (ULW) proppant, which was also the first ever combined use of ULW proppant and diverter valves. These technologies were required due to the long interval length, 4,880ft, and high angle, maximum 103°. A history match of the gravel pack model was also performed to evaluate the performance of the ULW proppant during a long horizontal gravel pack.
Data Driven Machine Learning Models for Shale Gas Adsorption Estimation
Authors: Wang Lei , Liu Mingliang , Altazhanov Arlybek , Syzdykov Bekassyl , Yan Jiang , Meng Xin , Jin Kai
Published: June 2020

Accurate calculation of adsorbed shale gas content is critical for gas reserve evaluation and development. However, gas adsorption and desorption experiments are expensive and time-consuming, while physics-based models and empirical correlations are unable to accurately capture the adsorption characteristics for different shales. Langmuir adsorption is one of the most commonly used model for calculating the adsorbed gas content in shale gas reservoirs. However, most existing correlations for the Langmuir pressure and Langmuir volume in the model are oversimplified based on limited experimental data points. Thus they are not representative of key geological parameters and are far from accurate for prediction in many cases. We developed a variety of machine learning models that are multivariable controlled to quantify shale gas adsorption.

The data-driven method subdivides into two procedures: data compilation and machine learning regression. Over 700 data entries, composed of reservoir temperature (T, °C), total organic carbon (TOC, wt%), vitrinite reflectance (Ro,%), Langmuir pressure, and Langmuir volume are compiled from shale gas plays mainly in USA, Canada, and China. Data have been consistently curated, then machine learning approaches, including multiple linear regression (MLR), support vector machine (SVM), random forest (RF) and artificial neural network (ANN), have been built, trained and tested by partitioning the data into 75%:25%. For SVM, RF and NN models, 1000 simulations were run and averaged for performance comparison.

MLR identifies non-negligible parameters and general trends for shale gas adsorption. Nonetheless, the correlation coefficients from MLR are far from satisfactory. For Langmuir pressure, RF models fit best to the data entries and the other models follow the order of SVM > ANN > MLR. Particularly, RF models show the highest performance stability with the averaged R-squared value of 0.84 and the maximum of 0.87, indicating a very strong relationship constructed for these 213 data entries. For 485 Langmuir volume data entries, RF models also perform best while the other three regression methods are comparable. It should be noted that altering machine learning model structure and parameters could significantly affect the regression results.

Robust and universal machine learning models for estimating adsorbed shale gas content with high confidence level are established, which not only provide more accurate estimation and broader parameter adaptation than physics-based and empirical models, but also circumvent the high-cost and time-consuming deficiency of experimental measurements. These machine learning models can be used to estimate adsorbed gas content for shale plays with limited experimental measurements. Moreover, they can be incorporated into reservoir simulators to improve the simulation performance.
Quantifying the Importance of Decisions and the Impact of Data Acquisition on Decisions in Hydrocarbon Field Re-Developments
Authors: Steineder Dominik , Clemens Torsten
Published: June 2020

Hydrocarbon field (re-)development projects require the evaluation of a large number of development options under uncertainty. Furthermore, information of data gathering programs might result in narrowing parameter ranges and change the choice of the preferred development option.

The large number of development options (and decisions accordingly) which have to be taken under uncertainty leads to the necessity to determine the impact of the decisions on the (re-)development project objective. Knowing the sensitivity of the decisions on the project objective (e.g. NPV) allows for resource and data acquisition planning. The impact of decisions on the project value can be determined by performing a Generalized Sensitivity Analysis. This analysis does not replace Value of Information but facilitates planning and allows focusing on important decisions.

To further improve Decision Analysis and focus on important parameters, a Generalized Sensitivity Analysis of uncertain parameters on decisions can be performed. The advantage of such an investigation over sensitivity analysis on Oil Originally in Place (OOIP) or Net Present Value (NPV) is that it includes parameter interactions. Furthermore, it covers the impact of a parameter on the decisions directly rather than indirectly when OOIP or NPV sensitivity is used.

The analysis is shown at an example project in a Decision Analysis framework. The use of decision impact evaluation and parameter assessment on decisions might lead to more focused and faster hydrocarbon field (re-)development project execution.
A Core Scale Investigation of Drainage Displacement
Authors: Arab Danial , Kantzas Apostolos , Torsæter Ole , Bryant Steven L.
Published: June 2020

Water flooding has been applied either along with primary production to maintain reservoir pressure or later to displace the oil in conventional and heavy oil reservoirs. Although it is generally accepted that water flooding of light oil reservoirs in oil-wet systems delivers the least oil compared to either water-wet or intermediate-wet systems, there is a lack of systematic research to study water flooding of heavy oils in oil-wet reservoirs. This research gives some new insights on the effect of injection velocity and oil viscosity on water flooding of oil-wet reservoirs.

Seven different oils with a broad range of viscosity ranging from 1 to 15,000 mPa.s at 25 °C were used in fifteen core flooding experiments where injection velocity was varied from 0.7 to 24.3 ft/D (2.5 × 10−6 m/s to 86.0 × 10−6 m/s). Oil-wet sand (with contact angle of 159.31 ± 3.06°) was used in all the flooding experiments. Breakthrough time was precisely determined using an in-line densitometer installed downstream of the core.

Our observations suggest that drainage displacement does not occur unless non-wetting (water) phase pressure exceeds a critical breakthrough capillary pressure. At the same injection velocity, this non-wetting phase invading pressure is a function of the viscosity of the oil being displaced. For the same viscosity ratio, oil recovery monotonically increases with increasing injection velocity suggesting that the flow regime is viscous-dominant for all the viscosities studied. This is consistent with the classical literature on carbonates (deZabala and Kamath, 1995). However, the current work extends the classical learnings to a much wider operational envelope on oil-wet sandstones.

In this paper, it is demonstrated that in an oil-wet system increasing velocity improves forced drainage to the extent that it takes over viscous fingering. For the viscous oil system (15,000 mPa.s), it was found that wettability critically affects the pressure gradient across the core to the extent that one order of magnitude larger pressure gradient was observed in an oil-wet system compared to the completely same system but water-wet. This notable larger pressure gradient in oil-wet system accompanies with delayed water breakthrough leading to incremental (around 30 % OOIP) oil recovery compared to the water-wet case. This is completely opposite to the classical literature on light oils and needs to be further investigated due to the lack of literature on heavy oil domains. Observations reported in this study can provide some useful information about the sizes of the pores being invaded as a function of oil viscosity and wettability, which is a subject of our future microfluidic studies at the pore scale.