FROM PLUG MEASUREMENTS TO DYNAMIC SIMULATIONS: UPSCALING EFFECTS ON MODELED HYDROCARBON VOLUMES

2021 ◽  
Author(s):  
Iulian N. Hulea ◽  

Building reliable subsurface models requires detailed knowledge of both the rock and fluids involved. One critical petrophysical property determining the viability of a development is the hydrocarbon saturation. In 3D geological models, the saturation is populated via Saturation height models and free fluid levels. In populating a 3D model with meaningful properties, measurements at various scales are integrated. Core measurements acquired at resolution far superior to that used in the 3D models require a change of scale- upscaling step. The process of accurately predicting water saturation in the upscaled model is not trivial. Here we follow this process by employing a saturation height model (SHM) at different scales in relationship to various permeability realizations. Multiple choices available as inputs into the SHM in various ranges of sensitivity with respect to the free water level position as well as different rock quality are looked at. Various degrees of heterogeneity are studied by using synthetic data, the saturation prediction accuracy based on upscaled input rock properties (like arithmetic/geometric and harmonic upscaled permeability) is investigated. For homogeneous rocks a workflow is detailed with the purpose of detecting the upscaling limits highlighting the possible errors that might appear in the upscaling process. A counterintuitive result is that in the transition zone (the focus of this work) permeable rocks are more prone to errors than the less permeable ones. We also conclude that no alteration of the SHM is necessary in the upscaling process. Given the fact that rock quality enters the SHM and that permeability upscaling follows a route that ultimately attempts to honor well performance, a natural question is what the relevance of such a permeability model as input for the SHM is. Our results highlight the best choices for an upscaled SHM input (upscaled) permeability- not necessarily the upscaled permeability used in history matching. Smallest errors are shown to be resulting from using geometrical or 1/3 power law upscaled permeability.

Author(s):  
Omar Al-Farisi ◽  
Hadi Belhaj ◽  
Fatmah Yammahi ◽  
Abdulla Al-Shemsi ◽  
Hocine Khemissa

Rock typing is one of the most important steps in reservoir modeling, and it’s the main task in reservoir characterization. In carbonate, the rock typing work that’s been performed during the last two decades had a little progress in term of providing reliable estimation of reservoir behavior. However, the development of Conjunction Rock Properties Convergence, CROPC, a carbonate rock typing concept that provided an important and easy solution to the carbonate rock typing gaps, has a major breakthrough, even though, CROPC methodology was developed to capture the single pore network through the conjunction of Lithology, permeability, capillary pressure and water saturation. Therefore, the need to identify more complex carbonate pore network had led to the initiation of developing the Carbonate Rock Type Matrix RocMat, which will be detailed in this paper, as part of a Master of Science research project. In this novel concept the carbonate rocks were classified into homogeneous, single pore network, and heterogeneous rocks, dual and triple pore network with the utilization of the effective petrophysical properties of permeability, capillary pressure, saturation, porosity and height above free water level, all were classified in a conjunction matrix that honors these properties and at the same time enables generating sub groups as down scaling and estimation for unseen groups with infinite rock complexity capturing, at the same time it enables the ease to lump the groups and generates upscale-groups that make it easier for utilization by the geologist and reservoir engineers to achieve the objective of better reservoir performance prediction, the work was performed and then tested in two carbonate offshore fields data. This RocMat was structured to be the ultimate catalog for carbonate rock types.


SPE Journal ◽  
2015 ◽  
Vol 20 (06) ◽  
pp. 1384-1396 ◽  
Author(s):  
Asana Wasaki ◽  
I. Yucel Akkutlu

Summary Measured permeability of an organic-rich shale sample varies significantly with applied laboratory conditions, such as the confining pressure, temperature, and the measurement fluid type. This indicates that the measured quantity is influenced by several mechanisms that add complexity to the measurement. The complexity is mainly caused by stress dependence of the matrix permeability. Also, it is because organic-rich shale holds significant volumes of fluids in sorbed (adsorbed, dissolved) states; sorption can also influence the permeability through its own storage and transport mechanisms. The stress-dependence and sorption effects on permeability could develop under the reservoir conditions and influence the production, although we currently do not have a predictive permeability model that considers their coexistence. In this work, this is accomplished by considering that the shale matrix consists of multiple continua with organic and inorganic pores. Stress dependency of the permeability comes along with slit-shaped pores, whereas the sorption effects are associated with nanoscale organic capillaries. A simple conceptual flow model with an apparent shale permeability is developed that couples the molecular-transport effects of the sorbed phase with the stress dependence of the slit-shaped pores. The simulation results show the impact of the permeability model on the production. Sensitivity analysis on the new permeability model shows that the stress dependence of the overall transport is significant at high pore pressure, when the effective stress is relatively low. Diffusive molecular transport of the sorbed phase becomes important as the stress gets larger and, hence, the slit-shaped pores close. The constructed apparent-permeability vs. pore-pressure curves show the dominance of the molecular transport as an increase in permeability characterized by appearance of a minimum permeability value at the intermediate values of the pressure. One can use the new permeability model easily in history matching a well performance and optimizing its production.


2001 ◽  
Vol 4 (06) ◽  
pp. 455-466 ◽  
Author(s):  
A. Graue ◽  
T. Bognø ◽  
B.A. Baldwin ◽  
E.A. Spinler

Summary Iterative comparison between experimental work and numerical simulations has been used to predict oil-recovery mechanisms in fractured chalk as a function of wettability. Selective and reproducible alteration of wettability by aging in crude oil at an elevated temperature produced chalk blocks that were strongly water-wet and moderately water-wet, but with identical mineralogy and pore geometry. Large scale, nuclear-tracer, 2D-imaging experiments monitored the waterflooding of these blocks of chalk, first whole, then fractured. This data provided in-situ fluid saturations for validating numerical simulations and evaluating capillary pressure- and relative permeability-input data used in the simulations. Capillary pressure and relative permeabilities at each wettability condition were measured experimentally and used as input for the simulations. Optimization of either Pc-data or kr-curves gave indications of the validity of these input data. History matching both the production profile and the in-situ saturation distribution development gave higher confidence in the simulations than matching production profiles only. Introduction Laboratory waterflood experiments, with larger blocks of fractured chalk where the advancing waterfront has been imaged by a nuclear tracer technique, showed that changing the wettability conditions from strongly water-wet to moderately water-wet had minor impact on the the oil-production profiles.1–3 The in-situ saturation development, however, was significantly different, indicating differences in oil-recovery mechanisms.4 The main objective for the current experiments was to determine the oil-recovery mechanisms at different wettability conditions. We have reported earlier on a technique that reproducibly alters wettability in outcrop chalk by aging the rock material in stock-tank crude oil at an elevated temperature for a selected period of time.5 After applying this aging technique to several blocks of chalk, we imaged waterfloods on blocks of outcrop chalk at different wettability conditions, first as a whole block, then when the blocks were fractured and reassembled. Earlier work reported experiments using an embedded fracture network,4,6,7 while this work also studied an interconnected fracture network. A secondary objective of these experiments was to validate a full-field numerical simulator for prediction of the oil production and the in-situ saturation dynamics for the waterfloods. In this process, the validity of the experimentally measured capillary pressure and relative permeability data, used as input for the simulator, has been tested at strongly water-wet and moderately water-wet conditions. Optimization of either Pc data or kr curves for the chalk matrix in the numerical simulations of the whole blocks at different wettabilities gave indications of the data's validity. History matching both the production profile and the in-situ saturation distribution development gave higher confidence in the simulations of the fractured blocks, in which only the fracture representation was a variable. Experimental Rock Material and Preparation. Two chalk blocks, CHP8 and CHP9, approximately 20×12×5 cm thick, were obtained from large pieces of Rørdal outcrop chalk from the Portland quarry near Ålborg, Denmark. The blocks were cut to size with a band saw and used without cleaning. Local air permeability was measured at each intersection of a 1×1-cm grid on both sides of the blocks with a minipermeameter. The measurements indicated homogeneous blocks on a centimeter scale. This chalk material had never been contacted by oil and was strongly water-wet. The blocks were dried in a 90°C oven for 3 days. End pieces were mounted on each block, and the whole assembly was epoxy coated. Each end piece contained three fittings so that entering and exiting fluids were evenly distributed with respect to height. The blocks were vacuum evacuated and saturated with brine containing 5 wt% NaCl+3.8 wt% CaCl2. Fluid data are found in Table 1. Porosity was determined from weight measurements, and the permeability was measured across the epoxy-coated blocks, at 2×10–3 µm2 and 4×10–3 µm2, for CHP8 and CHP9, respectively (see block data in Table 2). Immobile water saturations of 27 to 35% pore volume (PV) were established for both blocks by oilflooding. To obtain uniform initial water saturation, Swi, oil was injected alternately at both ends. Oilfloods of the epoxy-coated block, CHP8, were carried out with stock-tank crude oil in a heated pressure vessel at 90°C with a maximum differential pressure of 135 kPa/cm. CHP9 was oilflooded with decane at room temperature. Wettability Alteration. Selective and reproducible alteration of wettability, by aging in crude oil at elevated temperatures, produced a moderately water-wet chalk block, CHP8, with similar mineralogy and pore geometry to the untreated strongly water-wet chalk block CHP9. Block CHP8 was aged in crude oil at 90°C for 83 days at an immobile water saturation of 28% PV. A North Sea crude oil, filtered at 90°C through a chalk core, was used to oilflood the block and to determine the aging process. Two twin samples drilled from the same chunk of chalk as the cut block were treated similar to the block. An Amott-Harvey test was performed on these samples to indicate the wettability conditions after aging.8 After the waterfloods were terminated, four core plugs were drilled out of each block, and wettability measurements were conducted with the Amott-Harvey test. Because of possible wax problems with the North Sea crude oil used for aging, decane was used as the oil phase during the waterfloods, which were performed at room temperature. After the aging was completed for CHP8, the crude oil was flushed out with decahydronaphthalene (decalin), which again was flushed out with n-decane, all at 90°C. Decalin was used as a buffer between the decane and the crude oil to avoid asphalthene precipitation, which may occur when decane contacts the crude oil.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 626
Author(s):  
Jiyuan Zhang ◽  
Bin Zhang ◽  
Shiqian Xu ◽  
Qihong Feng ◽  
Xianmin Zhang ◽  
...  

The relative permeability of coal to gas and water exerts a profound influence on fluid transport in coal seams in both primary and enhanced coalbed methane (ECBM) recovery processes where multiphase flow occurs. Unsteady-state core-flooding tests interpreted by the Johnson–Bossler–Naumann (JBN) method are commonly used to obtain the relative permeability of coal. However, the JBN method fails to capture multiple gas–water–coal interaction mechanisms, which inevitably results in inaccurate estimations of relative permeability. This paper proposes an improved assisted history matching framework using the Bayesian adaptive direct search (BADS) algorithm to interpret the relative permeability of coal from unsteady-state flooding test data. The validation results show that the BADS algorithm is significantly faster than previous algorithms in terms of convergence speed. The proposed method can accurately reproduce the true relative permeability curves without a presumption of the endpoint saturations given a small end-effect number of <0.56. As a comparison, the routine JBN method produces abnormal interpretation results (with the estimated connate water saturation ≈33% higher than and the endpoint water/gas relative permeability only ≈0.02 of the true value) under comparable conditions. The proposed framework is a promising computationally effective alternative to the JBN method to accurately derive relative permeability relations for gas–water–coal systems with multiple fluid–rock interaction mechanisms.


2021 ◽  
pp. 1-29
Author(s):  
Eric Sonny Mathew ◽  
Moussa Tembely ◽  
Waleed AlAmeri ◽  
Emad W. Al-Shalabi ◽  
Abdul Ravoof Shaik

Two of the most critical properties for multiphase flow in a reservoir are relative permeability (Kr) and capillary pressure (Pc). To determine these parameters, careful interpretation of coreflooding and centrifuge experiments is necessary. In this work, a machine learning (ML) technique was incorporated to assist in the determination of these parameters quickly and synchronously for steady-state drainage coreflooding experiments. A state-of-the-art framework was developed in which a large database of Kr and Pc curves was generated based on existing mathematical models. This database was used to perform thousands of coreflood simulation runs representing oil-water drainage steady-state experiments. The results obtained from the corefloods including pressure drop and water saturation profile, along with other conventional core analysis data, were fed as features into the ML model. The entire data set was split into 70% for training, 15% for validation, and the remaining 15% for the blind testing of the model. The 70% of the data set for training teaches the model to capture fluid flow behavior inside the core, and then 15% of the data set was used to validate the trained model and to optimize the hyperparameters of the ML algorithm. The remaining 15% of the data set was used for testing the model and assessing the model performance scores. In addition, K-fold split technique was used to split the 15% testing data set to provide an unbiased estimate of the final model performance. The trained/tested model was thereby used to estimate Kr and Pc curves based on available experimental results. The values of the coefficient of determination (R2) were used to assess the accuracy and efficiency of the developed model. The respective crossplots indicate that the model is capable of making accurate predictions with an error percentage of less than 2% on history matching experimental data. This implies that the artificial-intelligence- (AI-) based model is capable of determining Kr and Pc curves. The present work could be an alternative approach to existing methods for interpreting Kr and Pc curves. In addition, the ML model can be adapted to produce results that include multiple options for Kr and Pc curves from which the best solution can be determined using engineering judgment. This is unlike solutions from some of the existing commercial codes, which usually provide only a single solution. The model currently focuses on the prediction of Kr and Pc curves for drainage steady-state experiments; however, the work can be extended to capture the imbibition cycle as well.


2021 ◽  
Author(s):  
Yair Gordin ◽  
Thomas Bradley ◽  
Yoav O. Rosenberg ◽  
Anat Canning ◽  
Yossef H. Hatzor ◽  
...  

Abstract The mechanical and petrophysical behavior of organic-rich carbonates (ORC) is affected significantly by burial diagenesis and the thermal maturation of their organic matter. Therefore, establishing Rock Physics (RP) relations and appropriate models can be valuable in delineating the spatial distribution of key rock properties such as the total organic carbon (TOC), porosity, water saturation, and thermal maturity in the petroleum system. These key rock properties are of most importance to evaluate during hydrocarbon exploration and production operations when establishing a detailed subsurface model is critical. High-resolution reservoir models are typically based on the inversion of seismic data to calculate the seismic layer properties such as P- and S-wave impedances (or velocities), density, Poisson's ratio, Vp/Vs ratio, etc. If velocity anisotropy data are also available, then another layer of data can be used as input for the subsurface model leading to a better understanding of the geological section. The challenge is to establish reliable geostatistical relations between these seismic layer measurements and petrophysical/geomechanical properties using well logs and laboratory measurements. In this study, we developed RP models to predict the organic richness (TOC of 1-15 wt%), porosity (7-35 %), water saturation, and thermal maturity (Tmax of 420-435⁰C) of the organic-rich carbonate sections using well logs and laboratory core measurements derived from the Ness 5 well drilled in the Golan Basin (950-1350 m). The RP models are based primarily on the modified lower Hashin-Shtrikman bounds (MLHS) and Gassmann's fluid substitution equations. These organic-rich carbonate sections are unique in their relatively low burial diagenetic stage characterized by a wide range of porosity which decreases with depth, and thermal maturation which increases with depth (from immature up to the oil window). As confirmation of the method, the levels of organic content and maturity were confirmed using Rock-Eval pyrolysis data. Following the RP analysis, horizontal (HTI) and vertical (VTI) S-wave velocity anisotropy were analyzed using cross-dipole shear well logs (based on Stoneley waves response). It was found that anisotropy, in addition to the RP analysis, can assist in delineating the organic-rich sections, microfractures, and changes in gas saturation due to thermal maturation. Specifically, increasing thermal maturation enhances VTI and azimuthal HTI S-wave velocity anisotropies, in the ductile and brittle sections, respectively. The observed relationships are quite robust based on the high-quality laboratory and log data. However, our conclusions may be limited to the early stages of maturation and burial diagenesis, as at higher maturation and diagenesis the changes in physical properties can vary significantly.


2019 ◽  
Vol 8 (4) ◽  
pp. 1484-1489

Reservoir performance prediction is important aspect of the oil & gas field development planning and reserves estimation which depicts the behavior of the reservoir in the future. Reservoir production success is dependent on precise illustration of reservoir rock properties, reservoir fluid properties, rock-fluid properties and reservoir flow performance. Petroleum engineers must have sound knowledge of the reservoir attributes, production operation optimization and more significant, to develop an analytical model that will adequately describe the physical processes which take place in the reservoir. Reservoir performance prediction based on material balance equation which is described by Several Authors such as Muskat, Craft and Hawkins, Tarner’s, Havlena & odeh, Tracy’s and Schilthuis. This paper compares estimation of reserve using dynamic simulation in MBAL software and predictive material balance method after history matching of both of this model. Results from this paper shows functionality of MBAL in terms of history matching and performance prediction. This paper objective is to set up the basic reservoir model, various models and algorithms for each technique are presented and validated with the case studies. Field data collected related to PVT analysis, Production and well data for quality check based on determining inconsistencies between data and physical reality with the help of correlations. Further this paper shows history matching to match original oil in place and aquifer size. In the end conclusion obtained from different plots between various parameters reflect the result in history match data, simulation result and Future performance of the reservoir system and observation of these results represent similar simulation and future prediction plots result.


2021 ◽  
Author(s):  
Anton Vasilievich Glotov ◽  
Anton Gennadyevich Skripkin ◽  
Petr Borisovich Molokov ◽  
Nikolay Nilovich Mikhailov

Abstract The article presents a new method of determining the residual water saturation of the Bazhenov Rock Formation using synchronous thermal analysis which is combined with gas IR and MS spectroscopy. The efficiency of the extraction-distillation method of determining open porous and residual saturation in comparison with the developed method which are considered in detail. Based on the results of studies in the properties of the Bazhenov Rock Formation, a significant underestimation of the residual water saturation in the existing guidelines for calculating reserves was found, and the structure of the saturation of rocks occurred to be typical for traditional low-permeability reservoirs. The values of open porous and residual water saturation along the section of the Bazhenov Formation vary greatly, which also contradicts the well-established opinion about the weak variability of the rock properties with depth.


2021 ◽  
Author(s):  
Aymen Alhemdi ◽  
Ming Gu

Abstract Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand creates long skinny fractures and maximizes the stimulated reservoir volume (SRV). However, due to the fast settling of sand in the water, lots of upper and deeper areas are not sufficiently propped. Reducing sand size can lead to insufficient fracture conductivity. This study proposes to use three candidate ultra-lightweight proppants ULWPs to enhance the fractured well performance in unconventional reservoirs. In step 1, the current sand pumping design is input into an in-house P3D fracture propagation simulator to estimate the fracture geometry and proppant concentrations. Next, the distribution of proppant concentration converts to conductivity and then to fracture permeability. In the third step, the fracture permeability from the second step is input into a reservoir simulator to predict the cumulative production for history matching and calibration. In step 4, the three ULWPs are used to replace the sand in the frac simulator to get new frac geometry and conductivity distribution and then import them in reservoir model for production evaluation. Before this study, the three ULWPs have already been tested in the lab to obtain their long-term conductivities under in-situ stress conditions. The conductivity distribution and production performance are analyzed and investigated. The induced fracture size and location of the produced layer for the current target well play a fundamental effect on ultra-light proppant productivity. The average conductivity of ULWPs with mesh 40/70 is larger and symmetric along the fracture except for a few places. However, ULWPs with mesh 100 generates low average conductivity and create a peak conductivity in limited areas. The ULW-3 tends to have less cumulative production compared with the other ULWPs. For this Marcellus Shale study, the advantages of ultra-lightweight proppant are restricted and reduced because the upward fracture height growth is enormous. And with the presence of the hydrocarbon layer is at the bottom of the fracture, making a large proportion of ULWPs occupies areas that are not productive places. The current study provides a guidance for operators in Marcellus Shale to determine (1) If the ULWP can benefit the current shale well treated by sand, (2) what type of ULWP should be used, and (3) given a certain type of ULWP, what is the optimum pumping schedule and staging/perforating design to maximize the well productivity. The similar workflow can be expanded to evaluate the economic potential of different ULWPs in any other unconventional field.


2021 ◽  
Author(s):  
Bashar Alramahi ◽  
Qaed Jaafar ◽  
Hisham Al-Qassab

Abstract Classifying rock facies and estimating permeability is particularly challenging in Microporous dominated carbonate rocks. Reservoir rock types with a very small porosity range could have up to two orders of magnitude permeability difference resulting in high uncertainty in facies and permeability assignment in static and dynamic models. While seismic and conventional porosity logs can guide the mapping of large scale features to define resource density, estimating permeability requires the integration of advanced logs, core measurements, production data and a general understanding of the geologic depositional setting. Core based primary drainage capillary pressure measurements, including porous plate and mercury injection, offer a valuable insight into the relation between rock quality (i.e., permeability, pore throat size) and water saturation at various capillary pressure levels. Capillary pressure data was incorporated into a petrophysical workflow that compares current (Archie) water saturation at a particular height above free water level (i.e., capillary pressure) to the expected water saturation from core based capillary pressure measurements of various rock facies. This was then used to assign rock facies, and ultimately, estimate permeability along the entire wellbore, differentiating low quality microporous rocks from high quality grainstones with similar porosity values. The workflow first requires normalizing log based water saturations relative to structural position and proximity to the free water level to ensure that the only variable impacting current day water saturation is reservoir quality. This paper presents a case study where this workflow was used to detect the presence of grainstone facies in a giant Middle Eastern Carbonate Field. Log based algorithms were used to compare Archie water saturation with primary drainage core based saturation height functions of different rock facies to detect the presence of grainstones and estimate their permeability. Grainstones were then mapped spatially over the field and overlaid with field wide oil production and water injection data to confirm a positive correlation between predicted reservoir quality and productivity/injectivity of the reservoir facies. Core based permeability measurements were also used to confirm predicted permeability trends along wellbores where core was acquired. This workflow presents a novel approach in integrating core, log and dynamic production data to map high quality reservoir facies guiding future field development strategy, workover decisions, and selection of future well locations.


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