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

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

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

Analysis of fracturing water flowback data from hydraulic fractures in unconventional reservoirs plays an important role in determining key fracture properties and predicting future well performance. Current flowback data analysis tools mostly rely on empirical correlations and/or simplified models. This paper presents a semi-analytical, multiphase solution that is applicable to the analysis of not only water flowback but early gas production data of multi-fractured horizontal gas wells. The proposed solution couples a Green's function-based analytical solution for gas flow in matrix with a finite-difference numerical solution for two-phase (gas and water) flow in fracture domain. The validity of proposed semi-analytical solution is verified against simulation results generated using commercial numerical simulators. Inverse analysis techniques are developed based on the proposed semi-analytical solution and presented in the form of type curves. Synthetic case studies show that the proposed type-curve methods can provide explicit and accurate estimation of fracture and reservoir properties, including fracture conductivity, and fracture pore volume. For all case tested, the proposed model is shown to provide accurate and consistent prediction of reservoir performance and estimations of fracture properties while maintaining the simplicity of explicit, iteration-free calculations.

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

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

Segmentation of X-ray images of rocks is an important step in digital rock technology. Current segmentation methods often suffer from operator bias and can be time-consuming. To overcome these limitations, an automated image segmentation model is created for pore scale images through the use of convolutional neural networks. A dataset of micro-Computed Tomography (CT) images of sandstones is considered. To create the ground truth data for training, Scanning Electron Microscopy 2D and micro-CT 3D images are used to obtain accurate segmentation masks. Three models are trained with the available data: One with limited images, one with the full dataset, and one with augmented data. The data augmentation is achieved by increasing sample size through image partitioning. The data set for each model is divided into training, validation, and testing with a 60/30/10 split, respectively. The U-Net architecture, designed to work with limited training data, is used to develop the models. Further validation of the models is performed on a different dataset unseen by the models. The Minkowski functionals and permeability of the volume generated by the segmented images are computed and compared with the ground truth segmentation. Against the unseen dataset, the models scored a dice coefficient of 0.9479, 0.9518, and 0.9599, respectively. We discuss the potential for improvement by data augmentation and fine-tuning. One limitation of the models is with the deficiency of variety in training data as both SEM and micro-CT is required to obtain the segmentation masks. We also discuss the performance of the model on unseen samples and show the potential improving efficiency in the digital rock technology. The models provide a quick and accurate segmentation for images of sandstones without the influence of operator bias, and the method shows promise for further development and improvement.

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

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

Lab experiments and numerical modeling have indicated that gas injection for IOR in tight oil reservoirs is technically feasible. Several operators have conducted pilots in the Eagleford and Bakken shales for a huff-n-puff IOR strategy with mixed results. Our objective in this work is to study the impact of (a) geomechanical effects during injection and fracture closure during production, (b) injection rate effect during huff-n-puff processes, (c) timing effect in huff-n-puff process, (d) phase behavior effects for huff-n-puff oil recovery, and (e) impact of soak time on oil recovery. We developed and utilized a fully coupled geomechanical compositional fracturing/reservoir simulator for gas injection in tight oil reservoirs. The model calculates stress changes due to both poroelastic (pressure changes) and mechanical (fracture opening and closing) effects. Permeability hysteresis during loading/unloading cycles is also considered. The simulation procedure involves the following steps: (a) The well is produced for a period of time (b) Gas is injected into the well and this is simulated by specifying the injection rate and gas composition (c) The well is produced again after some soaking period, and the results are checked for any improvement in the oil recovery. Based on our simulation studies, we observed several important trends. The degradation of permeability over multiple loading/unloading cycles due to hysteresis together with the poro-elastic effect severely impacts the oil recovery in later cycles. It was found that incremental oil recovery decreases after several huff-n-puff cycles. It was found that if higher gas injection rate gives higher oil recovery, but the oil recovery does not increase linearly with the injection rate. Phase behavior is found to be a key factor in the oil recovery and rich gas injection gives the best results. The impact of timing to initiate the huff-n-puff IOR was also studied. The soak time increases the ultimate oil recovery, but its impact is not significant in the study. Our simulation results provide operators with significant new insights on the design of huff-n-puff IOR. It is shown that fracture widening and closure during huff-n-puff cycles have a significant impact on oil recovery. The novelty of the work is the development and use of compositional geomechanical model for IOR performance evaluation.

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

The determination of well and reservoir parameters is paramount during exploration, appraisal of new reservoirs, and equally important during the development and production phases of a field. The interpretation of pressure transient-test data is one of the tools to obtain such parameters under dynamic conditions. Often this data is substantially influenced by non-reservoir factors such as gauge drift, adjacent noise due to natural or operational reasons, insufficient gauge resolution and dominant tidal effects. Any of these non-reservoir factors can significantly lead to a misleading interpretation of the formation. Rigorous vigilance against such occurrences is particularly important in designing deep transient well tests. The paper quantifies these effects. Obtaining strong, unequivocal reservoir responses in the pressure data are imperative in extracting the reservoir and well characteristics. Individual and convoluted effects of noise, drift, resolution, periodic tides have been looked into quantitatively to demonstrate the situations when the reservoir signal is too weak to make any meaningful characterization. Reservoir models have been utilized to develop quantitative criteria to describe the dominance and subsidence of the effects of noise, resolution, drift and periodic tides under different operating conditions. These criteria should guide test design so that the subsequent test can produce meaningful data. Depending on the amount of disruption caused in the measurements, there are situations when the test objective may not be achieved at all. Failure to create dominant reservoir responses results from insufficient signal-to-noise ratio due to the rate of production and the pressure drawdown. It is a function of formation, fluid properties or mechanical environment. A minimum rate of production for creating the required magnitude of signal-to-noise ratio must be achieved to interpret correctly the reservoir response. The paper provides guidelines to determine the minimum rate and drawdown needed to obtain the presence of deep heterogeneities or boundaries with a reasonable level of certainty. If a test is run with a rate lower than the minimum value, for example, the data will be biased by other hardware or natural factors, unrelated to the reservoir response. Examples are also presented with artifacts of non-reservoir effects to show how misleading characteristics of the reservoir and the well can be deduced with such distorted data. This study establishes cause-effect relationships due to certain non-reservoir factors so that engineers can select their hardware, choose the methods and timings to mitigate the associated undesirable effects. Such a practical guide to select the most suitable transient test will rightfully fill in its place in the literature. The methodology applies equally to wireline testing operations, deep transient testing, drill-stem testing and production testing.

In recent years, well performance from tight reservoirs in the Delaware Basin has been improving due to enhanced completion practices, better reservoir targeting and improved well designs in the region. One of the key components to the enhanced completion practices has been the implementation of progressively longer laterals. The rate of increase in lateral lengths have slightly slowed in recent years, as operators approach the point of no additional value creation as the well costs supersede the production gained from longer wells. This paper presents a tool created to evaluate the performance and economics of a given well given different reservoir, fluid, well design and completion parameters. The tool is also a probabilistic model that can quantify the impact of input parameters that the user feels uncertain about. As a result, it can provide management teams with an approach to make capital decisions under uncertainty. The proposed methodology presented in this paper is repeatable for different tight rock formations across different basins. An example of the tool's capability is demonstrated in this paper using an asset profile typical of the Delaware Basin's Wolfcamp A.

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

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

The transient volume of investigation extends the concepts of radius and depth of investigation (for radial and linear flow, respectively). However, it is far more general, with much broader applicability. Unlike the specific cases of radius and depth of investigation, the volume of investigation is independent of flow regime, geometry, and model. Thus, the transient volume of investigation is applicable even when no recognizable flow regime is present. The transient volume of investigation is based on fundamental properties common to all constant-terminal-rate solutions to the diffusivity equation. It is defined as the minimum reservoir volume necessary to provide sufficient pressure support to produce the observed rate of change of sand-face pressure as a function of time. The volume of investigation is a paradigm-changing concept. It is the only meaningful reservoir characteristic that is both easily estimated and model independent. It provides a rigorous lower bound on fluid in place investigated as a function of time during a test, independent of flow regime, geometry, model, and even permeability heterogeneity or anisotropy.

After long-time water injection, thief zones (TZ) tend to form and reduce the effectiveness of water flooding in mature oil fields. Several profile control techniques have been developed to resolve this problem. The effect of profile control depends on quantitative calculation of pore-throat size and volume of the thief zones which determines the most critical treatment factors such as the injection particle size and slug volume. Tracer tests or ‘PI’ index were normally used to identify thief zones. However, tracer tests are time-consuming and high-cost, especially for offshore fields; ‘PI’ index only reveals a relatively higher permeability area but not necessarily indicate presence of thief zones. This paper presents a new method to identify TZ as well as pore-throat sizes and volumes calculation by using the variation and derivative of water cut. The procedures are as following: Two theoretical models of injection and production were established to simulate water flooding development by stream tube method. The first model is a standard model and includes only normal reservoirs. The second model is a comparison model with presence of both high permeability zones and normal permeability zones. The water cut of two models was compared to distinguish the key points and curve features of TZ models. The key points and derivative curve were used to identify the existence of TZ. The ratio of high permeability zones to normal permeability zones as well as the absolute permeability, width and height of TZ were figured out using the peak values and their arrival times on the derivative curve of water cut. Calculate pore-throat radius and porosity of TZ using the absolute permeability in step 3 based on mercury injection capillary pressure (MICP) and then the pore volume of the TZ was determined. In a word, the fluctuation of the water cut curve and the multi-peak values of the water cut derivative curve are due to the fact that the injected water first reaches the production well along the high permeability layer of TZ, and then reaches the production well along the normal reservoir. Furthermore, larger pore volume of TZ will have more influence on water cut value and a larger water cut will be seen when the second peak value occurs on water cut derivative curve. This workflow had been applied to QHD32-6 oilfield for the profile control treatment design of over 10 well-groups were planned and achieved commendable results: the maximum water cut reduction reached 8% and the oil production noticeable increased by 300bbls per day with an output ratio over 5:1.

Reliable and representative models and detailed characterization of a geologically complex reservoir are crucially important in having better understanding of the reservoir behavior and directly guiding to the most efficient implementation of the field development plan. This study focused on developing models of the Upper Cretaceous Waha carbonate and Bahi sandstone reservoirs and the Cambrian-Ordovician Gargaf sandstone reservoir in the Meghil field, Sirte Basin, Libya. The goals of the study were to characterize the vertical and lateral spatial continuity of each of the three formations and to calculate deterministic and probabilistic volumetrics. The Meghil Field, discovered in 1959, is located on the Zelten Platform and regionally classified as an extensional area of the larger Zelten field. Nineteen wells were drilled targeting the primary reservoir interval of interest at a drilled depth of around 8000 feet. A 3D seismic program was conducted to develop detailed structural maps for the Kalash and Waha/Bahi/Gargaf formations to evaluate future gas field development program. The field is characterized by three slightly asymmetrical anticlinal traps trending NW-SE. Major and minor faults that cut the interior of the structure were detected in the seismic block. The available drill stem DST and production tests were used to evaluate the level of communication between the structures. The structural framework for a 3D reservoir model is based on the interpretation and integration of the seismic volume and the available well logs. The well log data show that the net hydrocarbon bearing zone thickness is about 270 feet, the average porosity ranges from 4% in the Bahi/Gargaf sandstone to 13% in the Waha limestone. The average water saturation ranges from 15% to 32% in the Waha limestone and the Bahi/Gargaf sandstone respectively. Geostatistical models were developed using the well log and core data along with the structural model developed from the 3D seismic volume. The models suggest that porosity decreases towards the flanks and that separate flow units are likely present. The deterministic and stochastic give estimates of the original gas in place of about 830 Bscf and 732.2 Bscf for the upper and lower reservoir intervals, respectively. This study demonstrated the potential for significant additional hydrocarbon production from the Meghil field as well as the potential impact of heterogeneity on well placement and spacing.

Knowing that accurate yet time-efficient multihpysical reservoir simulation is a major challenge, we have developed a deep neural network (DNN) based multiphysical simulator to acceletate the geomechanical calculation. We first generated 20,000 pressure -stress pairs by conducting regious multiphysical simulation with various mechanical properties using a full physics reservoir simulator. All data pairs are simulated by 128 *128 grid blocks. We then developed a U-Net network, a proven structure in image segmentation based on convolutional neural network (CNN), and trained the network with the generated data using Tensorflow. The U-Net network takes the pressure field as the input and regresses the stress field in a pixel-to-pixel manner. The model is trained with 100 epochs using Adam optimizer with a learning rate of 0.001 on GPU. The trained network is thereafter deployed in the reservoir simulator to predict the stress field from numerically solved pressure field at time step level. Hence the geomechanical simulation is replaced by the DNN proxy. Our results show that the accuracy of the U-Net network is above 97%, in the metric of mean square error. Moreover, the U-Net network possesses excellent capability for dimension generalization. With the implementation of the proxy DNN simulator, the simulation time spent in the geomechanical module has been reduced by more than 95% on a 256*256 case study. The novelty of our work lies in the pioneering application of DNN method to train and predict the time-dependent stress field, avoiding the curse of dimensionality. Our trained model can be conveniently connected with an existing reservoir simulator, which greatly saves the efforts of code development.

Conventional well test interpretation methods do not consider the special seepage characteristics of ultra-low permeability reservoirs, resulting in pessimistic well test interpretation of permeability and undervalued skin effect caused by reservoir damage. This study has established a well test interpretation model considering stress sensitivity/start-up pressure gradient and mud invasion for ultra-low permeability oil fields. The well test interpretation results have been applied to guide the formulation of overall development plan in South China Sea. The mathematical expressions of stress sensitivity and start-up pressure gradient were obtained by using real core experiments. The quantitative characterization of mud invasion time-varying skin was realized by using numerical core experiments. Based on the new characterization method, a seepage model considering three factors above was established. The real space solution was obtained by using Laplace transform and Stehfest numerical inversion methods, a series of new standard plates were drawn, and corresponding ultra-low permeability well test interpretation software was compiled. Based on the numerical simulator considering stress sensitivity and starting pressure gradient, an average permeability of 5md mechanism model with 0.6m near well bore damage zone was built. A well test design was then implemented to get pressure buildup data for well test interpretation. The authors compared the conventional well test methods and improved ultra-low permeability well testing method with same data base. A conclusion can be drawn that both permeability and skin have been seriously underestimated by using conventional well test methods. However, the permeability and additional pressure drop interpreted by improved ultra-low permeability well testing method is coincidence with mechanism model, which proved the validity of our new methods. Thus the well test permeability obtained by new methods can be used for productivity evaluation of low permeability oil field development and the skin factor can be used to guide mud system preparation and formation protection process design. The influence of stress sensitivity/start-up pressure gradient and mud invasion damage of ultra-low permeability reservoirs have been pioneering discovered, and well test interpretation plates and software considering three factors above have been implemented for the first time in the industry.