reservoir

Saturation evaluation based on resistivity methods have been widely accepted industry standard for the decades. Formation Evaluation in carbonates usually relatively straightforward due to simple lithology and resistivity-based methods works perfectly due to high formation water salinity. However, complexity and variation of carbonate texture and wettability makes estimating of saturation solely on resistivity methods challenging especially in case of the paucity of special core analysis (SCAL) data.

New developments in logging technology, especially in dielectric logging, is aiming to improve the log derived interpretation and reduce the uncertainties of the evaluation. Outputs of dielectric dispersion logs including computation of Archie's parameters (m=n), water-filled porosity enable clearly identified the hydrocarbon-bearing zones despite misleading oil saturation calculated using resistivity-dependent saturation approach in front of most porous reservoir. Water saturation computed with inverted from dielectric measurement Archie's parameters allows accurately identify the type of fluid (hydrocarbon or water) filling the free pore space and gain insight prior to the formation sampling and well test.

The objective of this work is to describe a comprehensive approach integrating dielectric measurement and other advanced sets of wireline logs for petrophysical characterization of carbonate reservoirs. This paper is intended to discuss in detail a case study from the Western Kazakhstan in which the integration of advanced petrophysical logs has enabled a robust reservoir and fluid characterization of carbonate reservoir and provided insights for formation testing results in advance.

The extensive logging suite to address all the key challenges included standard logging, dielectric dispersion, nuclear magnetic resonance, and formation microimager. The reservoir fluids and dynamic properties were characterized by a series of formation sampling. The integration of dielectric, nuclear magnetic resonance and formation microimager measurements has played a major role in characterizing formation heterogeneity and reveal pore structure type, a dielectric multi-frequency measurement is being utilized to measure the flushed zone oil saturation relatively independent of pore fluid salinity, rock texture, and composition.

The comparative analysis of well-logging and well-test results was carried out. Saturation types of 6 tested objects out of 6 obtained from well-test show perfect match with predicted reservoir saturation from petrophysical evaluation.

Complex Toe-to-Heel Flooding (CTTHF) is a short distance flooding technique developed by the authors for sandstone formations. CTTHF applied on horizontal wells and requires at least one barrier and injector hydraulic fracture, also it requires at least one method to control early water production. This paper discusses the design aspects of the CTTHF including the design of barrier fracture, injector fracture, and the produced water control methods. Technical and economical evaluation to rank different design setups is performed and presented.

Advanced commercial reservoir simulator with hydraulic fracturing module was used to simulate different CTTHF setups and reservoir conditions to set the reservoir selection criteria and proper design methodology. In this study, Toe-to-Heel Waterflooding was considered the base case. Sensitivity studies for barrier fracture and injector design has been achieved and presented. Moreover, a sensitivity studies for hydraulic fractures spacing, number of barrier fractures, batch injection scheduling and changing packer location have been performed.

When CTTHF is applied in high permeable sandstone formation, early water production is expected, except produced water control method is used. This study states the feasibility conditions for each proposed produced water control technique. Also, a methodology for candidate reservoir selection, design of barrier and injector fractures is developed and presented. There are multiple fluid systems can be used to create the barrier to seal a pre-determined zone. CTTHF is better reservoir management approach.

The novelty of the CTTHF is giving multiple options for produced water control that maximizes the produced oil and minimizes the water production. CTTHF's produced water control can make some reservoirs economic to produce.

In the past ten years, hydraulic fracturing technology and strategies have made major improvements in the operational efficiency and economic performance of shale well completions. Much of this advancement was derived in the past three years as a response to the global downturn in oil and gas commodity pricing. Mature shale plays across the United States have a surplus inventory of horizontal wells employing highly inefficient completions styles. Amid the low oil pricing environment, operators in the Bakken and Eagle Ford were capable of revitalizing these prior generation wells with great success through re-fracturing programs. In many cases, production of these re-fractured wells rivaled the production of newly drilled and completed shale wells both in terms of initial production post re-fracture as well as extended interval cumulative production. These re-fracturing programs allowed producers to achieve tremendous gains in production while minimizing drilling activity. Although re-fracturing began as a highly economical method to improve production during a time of depressed oil pricing, it is still being used today to improve the production of additional wells recognized as top-tier candidates.

By developing a specific set of criteria to select wells for re-fracturing, these programs can be successfully employed in the Appalachian Basin to improve the economics of gas wells, mitigating the effects of highly discounted natural gas pricing. After the explanation of well candidacy, an economic sensitivity analysis was implemented to illustrate the impacts a strong re-fracturing program could make for operators in the Northeast through a comparison of public data showing production and total reserves for both in and out-of-basin re-fracturing programs. Additionally, while this paper focuses on re-fracturing as it relates to shale formations it also includes information as to how re-fracturing relates to conventional formations.

After looking at the incremental economics of re-fracturing programs implemented in shale plays across the United States and in-basin data, the impacts of gas well re-completion can be fully quantified and understood through the application of probabilistic modeling. Additionally, this modeling further delineates re-completion candidacy by identifying which wells pose higher risks in economic metrics.

Very little information has been published regarding the impacts a re-fracturing program could have in the Appalachian Basin. As the field matures, the topic of re-completions will become increasingly important, and this analysis will allow operators to have a greater understanding of the impacts of refracturing shale gas wells in the Northeast.

Low injected fracturing fluid recovery has been an issue during flowback period that is highly impacted by the fracture closure behavior. Although existing flowback models consider fracture closure volumetrically, they do not represent the true situation of non-uniform fracture closure. In this paper, we proposed a coupled geomechanics and fluid flow model for early-time flowback in shale oil reservoirs. The fluid flow model is coupled with an elastic fracture closure model through finite element methods. In this study, three stages are modeled: fracture propagation, well shut-in and flowback. Cohesive Zone Method (CZM) has been used for modeling fracture propagation. The presented model distinguished the propped part from the unpropped part of the fracture. At the beginning of flowback, the proppants may not be completely compacted in early shut-in time. Thus, permeability evolution during closure is tracked using a smooth permeability transition function. The numerical results have shown that fracture closure during the flowback period is often not uniform. While the uniform fracture closure leads to maximum fracturing fluid recovery, an aggressive pressure drawdown strategy may damage fracture connectivity to the wellbore. An integrated flowback model enables modelling nonuniform fracture closure in a complex fracture network. This study highlights that by choke/pressure drawdown management, operators can influence fluid recovery and even maintain high fracture conductivity. Furthermore, the methodology presented in the paper can also be used for inverse analysis on early flowback data.

This paper presents a simple yet rigorous model and provides a methodology to analyze production data from wells exhibiting three-phase flow during the boundary-dominated flow regime. Our model is particularly applicable to analyze production data from volatile oil reservoirs, and should replace the less accurate single-phase models commonly used. The methodology will be useful in rate transient analysis and production forecasting for horizontal wells with multiple fractures in shales. Our analytical model for efficiently handling multi-phase flow is an adaptation of existing single-phase models. We introduce new three-phase parameters, notably fluids properties. We also define three-phase material balance pseudotime and three-phase pseudopressure to linearize governing flow equations. This linearization makes our model applicable to wells with variable rates and flowing pressures. We optimized the saturation-pressure path and further suggested an appropriate method to calculate three-phase pseudopressures. We validated the solutions through comparisons with compositional simulation using commercial software; the excellent agreement demonstrated the accuracy and utility of the analytical solution. We concluded that, during the boundary-dominated flow regime, the saturation-pressure relation given by steady-state path and tank-type model for volatile oil reservoirs leads to satisfactory results. We also confirmed that our definitions of three-phase fluid properties are well suited for ultra-low permeability volatile oil reservoirs. The computation time of our model is greatly reduced compared to a numerical approach, and thus the methodology should be attractive to the industry. Our model is efficient and practical to be applied for production data analysis in ultra-low permeability volatile reservoirs with non-negligible water production during the boundary-dominated flow regime. This study extends existing analytical model methodology for volatile oil reservoirs and is relatively easy for reservoir engineers to understand.

"Sweet spots" in the unconventional reservoirs such as organic-rich mudrocks are zones with high productivity. However, identifying such regions in unconventional reservoirs depends non-only on their petrophysical and but also on their geomechanical properties. Supervised learning methods can help in integrating numerical simulation and legacy field data in sweet-spot identification workflows and enhance their analysis in complex reservoirs. The objectives of this paper are to: (i) demonstrate the use of supervised learning in parameter selection and evaluation for fracture design and (ii) provide non-linear models for sweet-spot analysis in complex reservoirs.

We used fracture simulator that combines with fracture deformation with fluid-flow in discrete fracture networks. We started by selecting different geomechanical rock properties related to its fracability. We then used quasi-random design approach to obtain wide variation in aforementioned properties and performed 200 fracture simulations using the hydraulic fracturing simulator. We used the short-term Stimulated Reservoir Volumes (SRV) obtained at the end of numerical simulations, to quantify the performance of hydraulic fracturing operations. We used supervised learning techniques like support vector machines, decision trees, and random forests to perform parameter ranking and create non-linear regression models that can correlate the SRV to formation geomechanical properties.

The inputs for the analysis are: initial aperture, toughness, dilation angle, closure stress, and friction coefficient of initial fractures, stress anisotropy, shear modulus and a ratio of the reservoir rock. We analyzed the results using β-linear and multinomial regression, support vector machines, decision trees, and random forests. The linear models and non-linear models can explain up to 89.1% of output variance. The classification accuracy of support vector machines was at most 35% higher than other algorithms like random forests. Parameter rating using non-linear models showed that stress anisotropy and dilation angle demonstrated the highest effect on SRVs. Shear modulus and fracture toughness show minimal effect on the SRV but these parameters might still be useful they could be correlated to other formation parameters.

The outcomes of this paper demonstrated that parameters pertaining to unpropped fracture conductivity play a significant role in determining the success of hydraulic fracturing treatments. We have also compared the performances of supervised machine learning algorithms in assessing the impact of rock properties on fracturing treatments. Such supervised machine learning algorithms can help integrate field legacy data and numerical simulation outputs to develop proxy models that improve sweet-spot analysis and production estimates in unconventional reservoirs.

Horizontal wells with hydraulic fractures enable economical hydrocarbon extraction from unconventional reservoirs, and the associated transient production data is a reliable source for reservoir characterization. However, the complicated convolution of rate-pressure-time history leads to a less informative analysis of true reservoir characteristics. This paper presents a novel data-driven deconvolution approach using physics-based superposition to reconstruct constant-rate-drawdown pressure responses, which are further translated into diagnostic plots for efficient production analysis.

Traditional deconvolution in pressure transient analysis is usually an ill-conditioned "inverse" process that requires systematic curve-fitting, and the deconvolution response is highly sensitive to noise. Our proposed approach uses superposition equations as training features to honor the transient physics, and further projects them into higher dimensional ‘reservoir’ space (kernel-space) for the purpose of rigorous regression. Additionally, by implementing Laplacian eigenmaps, our algorithm is relatively insensitive to noise owing to its locality-preserving character. After training, the constant-rate-drawdown pressure response is reconstructed and a diagnostic plot is generated to identify key reservoir characteristics such as flow regimes.

We first validated our approach with two synthetic cases, a horizontal well with single and multiple transverse fractures (MTFW), and the drawdown pressure responses were obtained through simulation using a highly variable flow rate history. Additionally, we added artificial white Gaussian noise to the simulation output to mimic measured signals collected in the field, and we input this data into our model for deconvolution. The model-reconstructed constant-rate-drawdown pressure responses were used to determine flow regimes and reservoir properties such as permeability and stimulated reservoir volume (SRV) using traditional transient testing diagnostic tools and specialized plots. The deconvolved responses for each case were in alignment with the fractured-basement reservoir model proposed by Kuchuk et al. (2012), and the flow regimes identified during MTFW production followed the theory proposed by Song et al. (2011). All deconvolved responses were further validated through comparison with both simulation results and analytical solutions. Through the inherent locality-preserving character, our proposed algorithm was able to handle a moderate level of noise in addition to the variation of pressure-rate signals. We then applied the methodology to field cases with "known" reservoir properties presented in the literature, and the outcomes were satisfactory.

This study showed that our proposed methodology is a reliable diagnostic tool to interpret pressure-rate data using traditional pressure transient analysis for unconventional reservoirs. Rapid and accurate deconvolved pressure responses greatly enhance the analysis of data with moderate noise and highly variable production histories, enabling engineers to recognize flow patterns and estimate reservoir properties. We demonstrated the versatility and applicability of our proposed approach with synthetic and field cases.

In this paper, we investigate the effect of pore size heterogeneity on multicomponent multiphase hydrocarbon fluid composition distribution and its subsequent influence on mass transfer through shale nano-pores. We use a compositional simulation model with modified flash calculation, which considers the effect of large gas-oil capillary pressure on phase behavior. We consider different average pore sizes for different segments of the computational domain and investigate the effect of the resulting heterogeneity on phase and composition distributions, and production. A two dimensional formulation is considered here for the application of matrix-fracture cross mass transfer. Note that the rock matrix can also consist of different regions with different average pore sizes. Both convection and molecular diffusion terms are included in the mass balance equations, while different reservoir fluids such as Bakken and Marcellus are considered. The simulation results show that since oil and gas phase compositions depend on the pore size, there is a concentration gradient between the two adjacent pores with different sizes. Considering that shale permeability is small, we expect the mass transfer between two sections of the reservoir/core with two distinct average pore sizes to be diffusion-dominated. This observation implies that there can be a selective matrix-fracture component mass transfer during both primary production and gas injection EOR as a result of confinement-dependent phase behavior. Therefore, molecular diffusion term should be always included in the mass transfer equations, for both primary and gas injection EOR simulation of heterogeneous shale reservoirs.

Minagish Oolite reservoir is a prolific limestone reservoir in Umm Gudair field underlain by an active aquifer situated in West Kuwait. The field has been on production for over 50 years and has been experiencing rising water production levels in the recent years. Understanding the movement of water in the reservoir is vital for maximizing oil recovery.

During the producing life of the reservoir, the vertical movement of water is influenced by presence of flow barriers / baffles in the reservoir and how they are distributed in the vertical as well as areal direction. Understanding the lateral distribution of the flow barriers to fluid movement in the vertical direction has been a challenge throughout the production history of the field. Efforts have been ongoing in the past, to understand the movement of aquifer water in the vertical direction based on analysis of openhole log data, structural configuration, stratigraphy, well performance, production logging (PLT) results etc. These have resulted in developing a respectable level of understanding of the distribution and strength of barriers/baffles and their effectiveness in the field performance.

In a recent campaign to reduce the rapidly increasing volume of water produced from Minagish Oolite reservoir, a large number of workovers were carried out based on the current understanding of the vertical barriers / baffles, resulting in bringing down the water-cut level appreciably. The paper analyzes the results obtained from carrying out the numerous workovers for water shut-off in the recent campaign. This analysis has been utilized in an attempt to improve the history match in the dynamic reservoir simulation, especially the water-cut history match. Whereas good match of long water-cut history before the recent water shut-off jobs indicates absence of serious issue of well integrity, transmissibility modifiers in the simulation model were required, in order to improve water-cut history match in the post water shut-off period. Thus, there is vast improvement in the simulation team's understanding of the lateral distribution and strength of barriers / baffles. This has greatly aided in the formulation of more pragmatic plans for future workovers involving water shut-off by squeezing-off or isolating watered out layers. The result is a more robust prediction of production profile from the future field development activities.

The paper presents how the integrated approach of the open-hole, cased hole logs data with field performance in the history match process of simulation helps in the improvement of reservoir simulation modeling.

The compositional flow simulation model was frequently used to evaluate the miscible water alternating CO₂ flooding (CO₂-WAG). The uncertainty and sensitivity analysis have to be conducted to examine the parameters mostly affecting the performance of the process. Accordingly, multiple simulation runs require to be constructed which is a time-consuming procedure and finally increase the computational cost. This paper presents a simplistic approach to assess the miscible CO₂-WAG flooding in an Iraqi oilfield through developing a statistical proxy model. The Central Composite Design (CCD) was employed to build the proxy model to determine the incremental oil recovery (ΔFOE) as a function of seven reservoir and operating parameters (permeability, porosity, ratio of vertical to horizontal permeability, cyclic length, bottom hole pressure, ratio of CO₂ slug size to water slug size, and CO₂ slug size). In total, 81 compositional simulation runs were conducted at field-scale to establish the proxy model. The validity of the model was investigated based on statistical tools; the Root Mean Squared Error (RMSE), R-squared statistic and the adjusted R-squared statistic of 0.0095, 0.9723 and 0.9507 confirmed the reliability of the model. The most influential and the optimum values of the parameters that lead to the higher ΔFOE during miscible CO₂-WAG process were identified through proxy modeling analysis. The developed model was created based on the Nahr Umr reservoir in Subba oilfield and can be applied to roughly estimate the ΔFOE during the miscible CO₂-WAG process at the same geological conditions as Nahr Umr reservoir.