North America

Relative permeability (k_r) functions are among the essential data required for the simulation of multiphase flow in hydrocarbon reservoirs. These functions can be measured in the laboratory using different techniques including the steady state displacement technique. However, relative permeability measurement of shale rocks is extremely difficult mainly because of the low/ultralow matrix permeability and porosity, dominant capillary pressure and stress-dependent permeability of these formations.

In this study, the impacts of stress and capillary end effects (CEE) on the measured relative permeability data were investigated. The steady state relative permeability (SS-k_r) measurements were performed on Eagle Ford and Pierre shale samples. To overcome the difficulties regarding the k_r measurements of shale rocks, a special setup equipped with a high-pressure visual separator (with an accuracy of 0.07 cc) was used. The k_r data were measured at different total injection rates and liquid gas ratios (LGR). In addition, to evaluate the impacts of effective stress, the k_r data of an Eagle Ford shale sample were measured at two different effective stresses of 1000 and 3000 psi.

From the experimental data, it was observed that the measured SS-k_r data of the shale samples have been influenced by the capillary end effects as the data showed significant variation when measured at different injection rates (with the same LGR). This suggested that the liquid hold-up (i.e. capillary end effects) depends on the competition of capillary and viscous forces. In addition, it was shown that it is more necessary to correct the experimental kr data measured at the lower LGRs. Furthermore, different relative permeability curves were obtained when the k_r data were measured at different effective stresses. This behavior was explained as the capillary pressure was expected to be more dominant at the higher effective stress.

The results from this study improve our understanding of unconventional mechanisms in shale reservoirs. It is evident that the behavior of unconventional reservoirs can be better predicted when more reliable and accurate relative permeability data are available. The outcomes of this study will be useful for accurate determination of such k_r data.

The fluid pressure, the stress due to the column of the cement in the annulus of oil and gas wells, and the radial pressure exerted on the cement sheath from the surrounding geological layers all affect the integrity of the cement sheath. This paper studies the impact of CO₂-bearing fluids, coupled with the geomechanical alterations within the cement matrix on its integrity. These geochemical and geomechanical alterations within the cement matrix have been coupled to determine the cement lifespan. Two main scenarios including radial cracking and radial compaction, were assumed in order to investigate the behaviour of the cement matrix exposed to CO₂-bearing fluids over long periods. If the radial pressure from the surrounding rocks on the cement matrix overcomes the strength of the degraded layers within the cement matrix, cement failure can be postponed, while on the other hand, high vertical stress on the cement matrix in the absence of a proper radial pressure can lead to a reduction in the cement lifespan. The radial cracking process generates local areas of high permeability around the outer face of the cement sheath. Our simulation results show at the shallower depths the cement matrices resist CO₂-bearing fluids more and this delays exponentially the travel time of CO₂-bearing fluids towards the Earth's surface. This is based on the evolution of CO₂ gas from the aqueous phase due to the reduction in the fluid pressure at shallower depths, and consumption of CO₂ in the reactions which occur at the deeper locations.

Chemical Enhanced Oil Recovery leads to substantial incremental costs over waterflooding of oil reservoirs. Reservoirs containing oil with a high Total Acid Number (TAN) could be produced by injection of alkali. Alkali might lead to generation of soaps and emulsify the oil. However, the generated emulsions are not always stable.

Phase experiments are used to determine the initial amount of emulsions generated and their stability if measured over time. Based on the phase experiments, the minimum concentration of alkali can be determined and the concentration of alkali above which no significant increase in formation of initial emulsions is observed.

Micro-model experiments are performed to investigate the effects on pore scale. For injection of alkali into high TAN number oils, mobilization of residual oil after waterflooding is seen. The oil mobilization is due to breaking-up of oil ganglia or movement of elongated ganglia through the porous medium. As the oil is depleting in surface active components, residual oil saturation is left behind either as isolated ganglia or in down-gradient of grains.

Simultaneous injection of alkali and polymers leads to higher incremental oil production in the micro-models owing to larger pressure drops over the oil ganglia and more effective mobilization accordingly.

Core flood tests confirm the micro-model experiments and additional data are derived from these tests. Alkali co-solvent polymer injection leads to the highest incremental oil recovery of the chemical agents which is difficult to differentiate in micro-model experiments. The polymer adsorption is substantially reduced if alkali is injected with polymers compared with polymer injection only. The reason is the effect of the pH on the polymers. As in the micro-models, the incremental oil recovery is also higher for alkali polymer injection than with alkali injection only.

To evaluate the incremental operating costs of the chemical agents, Equivalent Utility Factors (EqUF) are calculated. The EqUF takes the costs of the various chemicals into account. The lowest EqUF and hence lowest chemical incremental OPEX are incurred by injection of Na₂CO₃, however, the highest incremental recovery factor is seen with alkali co-solvent polymer injection. It should be noted that the incremental oil recovery owing to macroscopic sweep efficiency improvement by polymer needs to be taken into account to assess the efficiency of the chemical agents.

Recent studies have indicated that Huff-n-Puff (HNP) gas injection has the potential to recover an additional 30-70% oil from multi-fractured horizontal wells in shale reservoirs. Nonetheless, this technique is very sensitive to production constraints and is impacted by uncertainty related to measurement quality (particularly frequency and resolution), and lack of constraining data. In this paper, a Bayesian workflow is provided to optimize the HNP process under uncertainty using a Duvernay shale well as an example.

Compositional simulations are conducted which incorporate a tuned PVT model and a set of measured cyclic injection/compaction pressure-sensitive permeability data. Markov chain Monte Carlo (McMC) is used to estimate the posterior distributions of the model uncertain variables by matching the primary production data. The McMC process is accelerated by employing an accurate proxy model (kriging) which is updated using a highly adaptive sampling algorithm. Gaussian Processes are then used to optimize the HNP control variables by maximizing the lower confidence interval (μ-σ) of cumulative oil production (after 10 years) across a fixed ensemble of uncertain variables sampled from posterior distributions.

The uncertain variable space includes several parameters representing reservoir and fracture properties. The posterior distributions for some parameters, such as primary fracture permeability and effective half-length, are narrower, while wider distributions are obtained for other parameters. The results indicate that the impact of uncertain variables on HNP performance is nonlinear. Some uncertain variables (such as molecular diffusion) that do not show strong sensitivity during the primary production strongly impact gas injection HNP performance. The results of optimization under uncertainty confirm that the lower confidence interval of cumulative oil production can be maximized by an injection time of around 1.5 months, a production time of around 2.5 months, and very short soaking times. In addition, a maximum injection rate and a flowing bottomhole pressure around the bubble point are required to ensure maximum incremental recovery. Analysis of the objective function surface highlights some other sets of production constraints with competitive results. Finally, the optimal set of production constraints, in combination with an ensemble of uncertain variables, results in a median HNP cumulative oil production that is 30% greater than that for primary production.

The application of a Bayesian framework for optimizing the HNP performance in a real shale reservoir is introduced for the first time. This work provides practical guidelines for the efficient application of advanced machine learning techniques for optimization under uncertainty, resulting in better decision making.

Since decades, steam-assisted oil recovery processes have been successfully deployed in heavy oil reservoirs to extract bitumen/heavy oil. Current resource allocation practices mostly involve reservoir model-based open loop optimization at the planning stage and its periodic recurrence. However, such decades-old strategies need a complete overhaul as they ignore dynamic changes in reservoir conditions and surface facilities, ultimately rendering heavy oil production economically unsustainable in the low-oil-price environment. Since steam supply costs account for more than 50% of total operating costs, a data-driven strategy that transforms the data available from various sensors into meaningful steam allocation decisions requires further attention.

In this research, we propose a purely data-driven algorithm that maximizes the economic objective function by allocating an optimal amount of steam to different well pads. The method primarily constitutes two components: forecasting and nonlinear optimization. A dynamic model is used to relate different variables in historical field data that were measured at regular time intervals and can be used to compute economic performance indicators (EPI). The variables in the model are cumulative in nature since they can represent the temporal changes in reservoir conditions. Accurate prediction of EPI is ensured by retraining regression model using the latest available data. Then, predicted EPI is optimized using a nonlinear optimization algorithm subject to amplitude and rate saturation constraints on decision variables i.e., amount of steam allocated to each well pad.

Proposed steam allocation strategy is tested on 2 well pads (each containing 10 wells) of an oil sands reservoir located near Fort McMurray in Alberta, Canada. After exploratory analysis of production history, an output error (OE) model is built between logarithmically transformed cumulative steam injection and cumulative oil production for each well pad. Commonly used net-present-value (NPV) is considered as EPI to be maximized. Optimization of the objective function is subject to distinct operating conditions and realistic constraints. By comparing results with field production history, it can be observed that optimum steam injection profiles for both well pads are significantly different than that of a field. In fact, the proposed algorithm provides smooth and consistent steam injection rates, unlike field injection history. Also, the lower steam-oil ratio is achieved for both well pads, ultimately translating into ~19 % higher NPV when compared with field data.

Inspired from state-of-the-art control techniques, proposed steam allocation algorithm provides a generic data-driven framework that can consider any number of well pads, EPIs, and amount of past data. It is computationally inexpensive as no numerical simulations are required. Overall, it can potentially reduce the energy required to extract heavy oil and increase the revenue while inflicting no additional capital cost and reducing greenhouse gas emissions.

Fractures can be first-order controls on fluid flow in hydrocarbon reservoirs. Understanding the characteristics of fractures such as their aperture, density, distribution, conductivity, connectivity, etc, is key for reservoir engineering and production analysis.

Well testing plays a key role in the the characterisation of fractured reservoirs, especially. New advances in the Pressure Transient Analysis (PTA) have enabled the interpretation of production data in a way where the resulting geological scenarios are in better agreement with fracture patterns observed in outcrop analogues.

Traditionally, Drill Stem Test (DST) data have been the primay source of information for well testing. However, we hypothesise that wireline conveyed tools designed for Interval Pressure Transient Testing (IPTT) could yield a more throrough description of the near-wellbore heterogeneities, including fractures.

Hence, we investigate the applicability of IPTT for characterising fractured reservoirs using detailed numerical simulations models with accurate wellbore representation to generate synthetic IPTT responses that can obtained through a next-generation wireline testing tool called SATURN. We particularly focus on cases where fractures are present in the near-wellbore region but do not intersect the wellbore. The study included parameters such as fracture densities and conductivities, distance between fractures and wellbore and the vertical extension of the fractures across geological beds.

The impact of the different fracture scenarios on the pressure transient tests was recorded as characteristic signatures on diagnostic plots (pressure derivative curves). We have called these curves "IPTT-Geotypes"; they can be used to assist the interpretation process of IPTT responses. To the best of our knowledge, this is the first time pressure derivative type curves for IPTT in fractured reservoirs are presented in the literature.

A field example of an IPTT case was analysed using the concept of geological well testing. We integrated the information from petrophysical logs and the IPTT-Geotypes to assist the calibration of a reservoir model developed to represent the geological setting of the tested reservoir interval. The results provided a sound interpretation of the reservoir geology and quantitative estimation of the matrix and fracture parameters.

The present study provides a comprehensive set of new analytical expressions to help understand and quantify well interference due to competition for flow space between the hydraulic fractures of parent and child wells. Determination of the optimum fracture spacing is a key factor to improve the economic performance of unconventional oil and gas resources developed with multi-well pads. Analytical and numerical model results are combined in our study to identify, analyze, and visualize the streamline patterns near hydraulic fractures, using physical parameters that control the flow process, such as matrix permeability, hydraulic fracture dimensions and assuming infinite fracture conductivity. The algorithms provided can quantify the effect of changes in fracture spacing on the production performance of both parent and child wells. All results are based on benchmarked analytical methods which allow for fast computation, making use of Excel-based spreadsheets and Matlab-coded scripts. Such practical tools can support petroleum engineers in the planning of field development operations. The theory is presented with examples of its practical application using field data from parent and child wells in the Eagle Ford shale (Brazos County, East Texas). Based on our improved understanding of the mechanism and intensity of production interference, the fracture spacing (this study) and inter-well spacing (companion study) of multifractured horizontal laterals can be optimized to effectively stimulate the reservoir volume to increase the overall recovery factor and improve the economic performance of unconventional oil and gas properties.

This study is based on the premise that most of the trapped hydrocarbons can be produced, if we substitute them with another ‘acrificial’ fluid that has amplified interactions with organic pore walls, such as CO₂. For the presented study, a downhole shale sample is analyzed in the laboratory to predict gas storage properties such as pore-volume, pore compressibility, and gas adsorption capacity. Then a series of pressure pulse decay measurements are performed to delineate transport mechanisms and predict stress-sensitive permeability. These coefficients are obtained as the calibration parameters of a simulation-based optimization for injection and production. Simulation model considers compositional gas flow in a deformable porous media and includes a multi-continuum porosity, with organic and inorganic pores, and micro-fractures. The experimental and simulation results show that most of the injected CO₂ is adsorbed in the organic matrix and are not produced back. This is because CO₂ molecules have significantly larger adsorption capacity when compared to methane. The strong adsorption of CO₂ improves the release of natural gas from kerogen pores. This indicates that the separation of produced CO₂ will be a minimal cost. Transport in kerogen has significant pore wall effects, and includes large mass fluxes of the adsorbed molecules by the walls due to surface diffusion. In essence, the adsorbed CO₂ molecules significantly influence transport of methane. The results also show core-plug permeability is stress-sensitive due to presence of micro-fractures. Forward simulation results using optimum parameters indicate that closure stress developing near the fractures could significantly control the volume of CO₂ injected. This raises operational issues on when to start injecting, and how to inject CO₂. Using a simulation study of a production well with single-fracture, we show that fracture closure stress develops rapidly and production rate becomes a slave of the fracture geo-mechanics, e.g., strength of the proppants and the level of proppant embedment.

The objective of this work is to characterize the fault system and its impact on Mishrif reservoir capacity in the West Quran oil field. Determination and modelling of these faults are crucial to evaluate and understanding fluid flow of both oil and water injection in terms of distribution and the movement. In addition to define the structure away from the well control and understanding the evolution of West Qurna arch over geologic time.

In order to achieve the aim of the work and the structural analysis, a step wise approach was undertaken. Primarily, intensive seismic interpretation and building of structure maps were carried out across the high resolution of 3D-seismic survey with focusing on the main producing Mishrif reservoir of the field. Also, seismic attributes volumes provided a good information about the distribution and geometry of faults in Mishrif reservoir. The next step, it constructs 3-D fault model which will be later merged into the developed 3D geological model. West Qurna/1 oil field situated within the Zubair Subzone, and it is structurally a part of large anticline towards the north. The observation of seismically derived faults near Mishrif reservoir indicated en-echelon faults which refer to strike-slip tectonics along with extensional faults. The statistic of Mishrif interval faulting indicates a big number faults striking north-south along western wedge of anticline. The seismic interpretation, in combination with seismic attributes volumes, deliver a valuable structural framework which in turns used to build a better geological model.

In this paper, the work demonstrates a better understanding for the perspectives on the seismic characterization of the structural framework in the Mishrif reservoir, and also for similar heterogeneous carbonate reservoirs. Further, this work will ultimately lead to improve reservoir management practises in terms of production performance and water flooding plan.

Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) reckons on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability and hydrocarbon saturation still rely on model calibration using core measurements. Furthermore, assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include (a) developing a new multiphysics workflow to simultaneously quantify rock fabric features (e.g., porosity, tortuosity, and effective throat size) and hydrocarbon saturation from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements, (b) introducing rock physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure, and (c) validating the reliability of the new workflow in pore- and core-scale domains.

To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid substitution algorithm to estimate the T₂ distribution corresponding to fully water-saturated rocks from the interpretation of NMR measurements. We use the estimated T₂-distribution for assessment of porosity, pore-size distribution, and effective pore-body size. Then, we develop a new physically meaningful resistivity model and apply it to obtain the constriction factor and, consequently, throat-size distribution from interpretation of resistivity measurements. Finally, throat-size distribution, porosity, and tortuosity are used to calculate directional permeability and saturation-dependent capillary pressure. We test the reliability of the new multiphysics workflow in core- and pore-scale domains on rock samples at different water saturation levels.

The introduced multiphysics workflow provides accurate description of the pore structure and fluid distribution in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. Finally, since the new workflow relies on fundamental rock physics principles, hydrocarbon saturation, permeability, and saturation-dependent capillary pressure can be estimated from well-logs with minimum calibration efforts, which is another unique contribution of this work.