Though seemingly straightforward, the concept of "net-to-gross" (NTG) is often a source of confusion. Its proper use is still being debated in some portions of the oil and gas industry. NTG is a method to account for non-reservoir quality rock when calculating oil volumes within a reservoir. This is normally accomplished by applying cutoffs to calculated quantities, such as porosity, which then get excluded from the volumetric calculation. To the extent there have been recent discussions of this, the focus has been primarily on how to determine appropriate cutoffs. There has been very little mention of the implications of using NTG in flow equations within a reservoir simulator. The paper discusses the derivation and implied assumptions for the simulator NTG formulation and possible errors and proposes modifications to account for inconsistencies.
Resolving the NTG flow equations can be viewed as an upscaling problem, subject to implied assumptions about reservoir continuity. Many fine-scale reservoir simulations were run to test this and to calibrate the NTG equations. The underlying attributes were sampled from a bimodal distribution, which represent pay and non-pay. The results show the effects of NTG ratio, values of fine-scale attributes and spatial correlation on steady state, single phase effective permeability and immiscible flow displacements. They demonstrate errors in effective horizontal and vertical permeability when using NTG within a simulator. These errors cause potentially significant differences in production responses between underlying detailed fine-scale models and coarser models. The results demonstrate a possible need for corrections to the simulator net-to-gross formulations due to underlying implied assumptions and inconsistencies. Some possible modifications are also presented. Both standard and machine learning techniques were used to analyze the results.
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.
Cronin, Michael (Department of Energy and Mineral Engineering and EMS Energy Institute, The Pennsylvania State University) | Emami-Meybodi, Hamid (Department of Energy and Mineral Engineering and EMS Energy Institute, The Pennsylvania State University) | Johns, Russell (Department of Energy and Mineral Engineering and EMS Energy Institute, The Pennsylvania State University)
We present a new semi-analytical compositional simulator specifically designed for hydrocarbon recovery (primary and cyclic solvent injection processes) in ultratight oil reservoirs based on diffusion-dominated transport within the matrix. The semi-analytical solution consists of a well-mixed tank model for the fractures coupled to diffusive transport within the matrix. Production of oil, gas, and water from the fractures is proportional to its phase saturation. The matrix allows for differing effective diffusion coefficients for each component. Because there are no grid blocks within the matrix the analytical solution is computationally less expensive than numerical simulation while capturing the steep, non-monotonic compositional changes occurring a short distance into the matrix owing to multiple injection cycles. The Peng-Robinson equation-of-state is used to calculate phase behavior within the analytical framework.
The solution is validated with several lab and field-scale cases. For primary recovery, the results show that the diffusion-based simulator correctly reproduces the pressure and oil recovery declines observed in the field. We show that the hydrocarbon recovery mechanism for solvent huff‘n’puff (HnP) is facilitated by greater density reduction and compositional changes (increased compositional gradients). Two solvents are considered in HnP calculations; carbon dioxide (CO2) and methane (CH4). Recovery of heavier components is enhanced with CO2 compared to CH4, but methane has overall greater oil recovery than carbon dioxide for the cases considered. Furthermore, the results demonstrate that multiple huff‘n’puff cycles constrained to surface injection are needed to enhance density and compositional gradients, and therefore oil recovery. While shorter soaks are better for short-term recovery (i.e. 3 to 5 years), longer soak periods maximize recovery over a longer timeframe (i.e. 10 to 15 years). This paper provides a novel way to model the optimum number of cycles and duration and when to start the HnP process after primary recovery for the limiting case of diffusion only transport where matrix permeabilities are very small (k < 200 nd).
Time does not feature in the equations. However, there are significant advantages if time is incorporated into the analysis. For example: a) identifying if all the wells belong to the same reservoir; b) identifying the effect of external energy sources such as gas or water drive; c) incorporating the contribution of communicating tight reservoirs; d) visualization of the results in pressure-time format. The time-based analysis presented in this paper supplements the conventional methods. It helps reduce the non-uniqueness of the solution. In contrast to the conventional Havlena-Odeh plotting variables, which are complex and non-intuitive, the pressure-time plot and corresponding pressure-history match are much easier for an engineer to comprehend and to evaluate the validity or uniqueness of the results.
Implementation of a drift-flux (DF) multiphase flow model within a fully-coupled wellbore-reservoir simulator is nontrivial and must adhere to a number of strict requirements in order to ensure numerical robustness and convergence. The existing DF model that can meet these requirements is only fully posed for upward flow from 2 degrees (from the horizontal) to vertical. The work attempts to extend the current DF model to a unified and numerically robust model that is applicable to all well inclinations. In order to achieve this objective, some 5805 experimentally measured data points from 22 sources as well as 13440 data points from the OLGA-S library are utilized to parameterize a new DF model - one that makes use of the accepted upward flow DF model and a new formulation extending this to horizontal and downward flow. The proposed model is compared against 2 existing DF models (also applicable to all inclinations) and is shown to have better, or equivalent, performance. More significantly, the model is also shown to be numerically smooth, continuous and stable for co-current flow when implemented in a fully implicitly coupled wellbore-reservoir simulator.
Cui, Xiaona (Texas A&M University and Northeast Petroleum University) | Song, Kaoping (China University of Petroleum - Beijing) | Yang, Erlong (Northeast Petroleum University) | Jin, Tianying (Texas A&M University) | Huang, Jingwei (Texas A&M University) | Killough, John (Texas A&M University) | Dong, Chi (Northeast Petroleum University)
The phase behavior shifts of hydrocarbons confined in nanopores have been extensively verified with experiments and molecular dynamics simulations. However, the impact of confinement on large-scale reservoir production is not fully understood. This work is to put forward a valid method to upscale the pore-scale fluid thermodynamic properties to the reservoir-scale and then incorporate it into our in-house compositional simulator to examine the effect of confinement on shale reservoir production.
Firstly, a pore-scale fluid phase behavior model is developed in terms of the pore type and pore size distribution (PSD) in the organic-rich shale reservoir using our modified Peng-Robinson equation of state (PR-C EOS) which is dependent on the size-ratio of fluid molecule dynamic diameter and the pore diameter. And the fluid composition distribution and PVT relation of fluids in each pore can be determined as the thermodynamic equilibria are achieved in the whole system. Results show that the initial fluid composition distribution is not uniform for different pore types and pore sizes. Due to the effect of confinement, heavier components are retained in the macropore, and lighter components are more liable to accumulate in the confined nanopores. Then an upscaled equation of state is put forward to model the fluid phase behavior at the reservoir-scale based on our modified PR-C EOS using a pore volume-weighted average method. This upscaled EOS is validated with the pore-scale fluid phase behavior simulation results and can be used for compositional simulation. Finally, two different reservoir fluids from the Eagle Ford organic-rich shale reservoir are simulated using our in-house compositional simulator to investigate the effect of confinement on production. In addition to the critical property shift which can be described by our upscaled PR-C EOS, capillary pressure is also taken into account into the compositional simulation. Results show that the capillary pressure has different effects on production in terms of the fluid type, leading to a lower producing Gas/Oil ratio (GOR) for black oil and a higher GOR for gas condensate. Critical property shift has a consistent effect on both the black oil and gas condensate, resulting in a lower GOR. It should be noted that the effect of capillary pressure on production is suppressed for both fluids with the shifted critical property.
Characterization of key parameters in unconventional assets continues to be challenging due to the geologic heterogeneity of such resources and the uncertainty associated with fracture geometry in stimulated rock. Limited data and the accelerating pace of asset development in plays like the Permian present an increasing need for an efficient and robust assisted history matching methodology that produces better insights for asset development planning decisions, e.g. well spacing.
A multi-scenario approach is presented to build an ensemble of history matched models that take into account existing uncertainty in reservoir description and well completions. We discuss parametrization of key uncertainties in the reservoir rock, fluid properties, fracture geometry and the effective permeability of stimulated rock. Ensemble-based assisted history matching algorithms are utilized to reduce and characterize the uncertainties in the model parameters by honoring various types of data including field dynamic data and measurements. We discuss the implementation of automated schemes for weighting of various types of data in the ensemble-based history matching algorithms. These schemes are introduced to define the history matching objective functions from various types of data including bottomhole pressure data, and the oil, water and gas productions rates. The computational results show that our adaptive scheme obtains better history match solutions.
The presented multi-scenario approach, coupled with the ability to efficiently run a high number of scenarios, enables better understanding of reservoir and fracture properties and shortens the learning curve for new development in unconventional assets. The shown case study illustrates a comprehensive analysis, using thousands of simulation cases, to obtain multiple history match solutions. Given the non-uniqueness of reservoir history matched models presented in the scenarios, this workflow improves forecasting ability and enables robust business decision makings under uncertainty.
Substantial computational time is typically a bottleneck for coupled flow-geomechanics simulation in realistic problems despite increasing importance in reservoir geomechanics. This paper presents a new, rapid, coupled flow-geomechanics simulator using the Fast Marching Method (FMM-Geo). The simulator incorporates Diffusive Time-of-Flight (DTOF), which represents the arrival time of the propagating pressure front, as a 1-D spatial coordinate to transform original multi-dimensional model into equivalent 1-D model. DTOF can be obtained by efficiently solving the Eikonal equation using the Fast Marching Method (FMM). FMM-Geo is verified for 2-D models against a benchmark simulator and has achieved order-of-magnitude faster computation while it preserved reasonable accuracy. Finally, the simulator is applied to an assisted history matching example using surface subsidence data to illustrate its computational efficiency and applicability.
A set of different numerical algorithms for non-Darcy flow models is developed and compared to each other in order to estimate functionality of algorithms and their potential of embedding into existing reservoir simulation software. In addition, a question of using such updated software to study an applicability of various non-Darcy flow models for unconventional reservoirs is discussed.
The approaches are based on generalization of a linear Darcy law in which a flow equation is modified by nonlinear expressions of a flow rate and other reservoir values, so various formulations of non-Darcy flows from different research papers can be described as particular cases of such a general formula. Next, this generalized flow equation is applied to the modified black-oil equations, but an exclusion of a flow rate as unknown is impossible due to properties of the generalization. A finite volume discretization and Newton linearization are performed, and several techniques of computationally efficient solution are observed.
A prototype of reservoir simulation program based on obtained mathematical model is constructed. Several numerical experiments are performed in order to verify numerical solutions and applied algorithms. Convergence rates of calculations by different approaches to non-Darcy flows are studied. The most significant finding is an existence of common approaches to exclude discretized and linearized flow equations at each iteration of nonlinear solver. This is important due to a presence of different non-Darcy models derived from different prerequisites (such as Forchheimer quadratic law and power law for non-Newtonian fluid) which can be studied through general algorithm as a research framework. Equally important is that the developed approaches are practically efficient and could be implemented in previously developed software without significant rearrangement of their code and algorithms in order to immediately gain practically useful simulations of non-Darcy flows or to explore their applicability, which is still an issue to resolve.
The novelty of the considered approaches is in ability to embed non-Darcy flow models into present reservoir simulation software keeping most of existing algorithms and data structures implemented. Taking into account that the algorithms are based on a generalized form of non-Darcy flows, it is possible to calculate a wide range of models preserving computational complexity.
Field development decisions are directly related to the original hydrocarbon in-place that leads to proper estimation of recoverable volumes and establish project economics. Oil and gas industry has had pressure core technology that is available to extract and preserve cores from reservoirs near in-situ conditions to determine hydrocarbon in-place values. Pressure core technology is an emerging one and prone to incomplete or partial data acquisition due to design limitations and inadequate implementations. Simulation modeling tool, typically used for reservoir modeling purposes, can augment the underperformances in data acquisition with a lab scale core simulation program.
Noble Energy has developed a modeling approach that allows hydrocarbon desorption rates from a pressure core sample to be simulated by emulating the lab conditions. Early time fluid losses for various reason such as fluid losses while encapsulating the core or during transport via wellbore and to the lab are common. Late time fluid desorption rates are difficult to obtain due to the time constraint that exists for performing experiments in the lab since it’s limited to hours to days timeframe. Both early and late time desorption rates can be augmented by simulation that yields better estimation of in-place volumes and expected recovery values over time while honoring the lab measured data in between.
Pressurized wireline rotary sidewall coring used by the vendors can have seal failures and the procedures implemented would not provide assurance of zero fluid losses since the mechanical equipment has expected operational limitations. The data obtained from such acquisitions may be deemed a failed experiment or even discarded if the losses cannot be quantified properly. Simulation enhancement revitalizes the data acquired and adds value to even partially successful pressure coring programs.
Noble Energy developed modeling approach to simulate fluid flow from the center of a core plug to the exterior surfaces of the plug emulating the lab environment complements the lab measurements even the pressure core had issues during and after acquisition. Simulation enhances pressure core data that may be incomplete or partially acquired based on possible early time losses and provide extended answers for late time desorption by eliminating impractical lab measurement timeframe. Reduced uncertainty in original hydrocarbon in-place volumes will allow better valuation of assets and robust field development plans.