Variations In Rock Properties Research Articles

New Fracture Diagnostic Test Delivers Tight Reservoir Data in 2 Hours or Less, Bolsters Future of Engineered Completions

One of the grand challenges facing the oil and gas industry’s global quest to improve the potential of tight reservoirs involves designing horizontal-well completions that match the often-complex heterogeneity of the target formations. This sums up the general concept most call the “engineered completion.” In theory, tailoring a stimulation job to the varying rock properties found along the lateral section of a horizontal wellbore should result in better production for less capital. In practice, the industry has never attempted to do this on a meaningful scale. Among other reasons, the detailed subsurface data required to shake the bonds of geometric, or “cookie cutter,” designs have long been considered too costly to gather or too time-consuming to analyze. A shift is underway though. This is thanks in part to a number of innovations that have hit the market in recent years to meet rising demand for real-time completions-monitoring services. By interpreting pressure signals and other reservoir responses, the new tools aim to give operators the competency they need to adjust fracture designs as the stimulation progresses. But there is another route to the engineered completion. It begins before the well is hydraulically fractured. This effort to predetermine different fracture-stage designs has established its own distinct arena of innovation. Behnam Zanganeh, a former research student at the University of Calgary, was part of a team that developed one of the latest approaches. It is notable in part because it requires no new technology - just new ways of thinking about some old ideas. In a paper published last month during the virtual Unconventional Resources Technology Conference, Zanganeh and his fellow petrotechnical researchers showed how multiple points in a wellbore can be tested for different reservoir-quality parameters quickly and simply relative to traditional methods (URTeC 2838). This is done by combining and fundamentally altering a test known for being slow: the diagnostic fracture injection test (DFIT). The biggest change it calls for is to start flowback after the injection cycle for flowback analysis (FBA), thus eliminating the lengthy falloff cycle associated with the DFIT. The paper outlines a validation study done with Sydney-based Origin Energy which used the blended DFIT-FBA method in a vertical open hole to test two previously untested horizons in the Beetaloo Basin, a frontier unconventional gas play in the center of Australia’s Northern Territory. The results were integrated into the models Origin ultimately used to select its landing target for its subsequent horizontal program.

Look Ahead of the Bit While Drilling: Potential Impacts and Challenges of Acoustic Seismic While Drilling in the McMurray Formation

SummaryThe oil and gas industry, operating and service companies, and academia are actively searching for ways to look ahead of the drill bit while drilling to reduce the risks and costs of the operation and improve the well-placement process. Optimal drilling in challenging and highly heterogeneous reservoirs, where geological data cannot adequately constrain high-frequency variations in rock properties, requires reliable subsurface information from around and ahead of the drill bit. To provide this, we have developed a seismic-while-drilling (SWD) imaging algorithm using signal processing, drillstring modeling, and prestack wave-equation migration.To extend the visibility ahead of the bit, we use the drill bit as a seismic source and image the changes in acoustic properties of rocks both around and ahead of the drill bit. The common practice is to build reverse vertical seismic profile (R-VSP) gathers. Here, we use a blind deconvolution algorithm to estimate the drill-bit source signature from the data directly. Alternatively, we can estimate such a signature through drillstring modeling and surface measurements (i.e., hookload and hook speed). The drillstring dynamics are modeled and analyzed using Riemann's invariants and a backstepping approach in a field-verified model. Next, we enter the estimated source signature into the prestack wave-equation depth-imaging workflow. Our simulations show that providing the drill-bit source signature to the prestack wave-equation depth migration consistently delivers reliable subsurface images around and ahead of the drill bit.The output of our workflow is a high-resolution subsurface image, which is then applied to provide vital information in oil-sands reservoirs for placement of steam-assisted-gravity-drainage (SAGD) well pairs. Compared with conventional practices, the proposed methodology images around and ahead of the drill bit enable interactive decision making and optimal well placement. The key feature of the presented methodology is that instead of cross correlating the SWD data with the pilot trace and building R-VSP gathers, we use the estimated drill-bit source signature and deliver high-resolution prestack depth-migrated images.Through numerical modeling, we tested the potential impacts, validity, and challenges of the proposed methodology in drilling horizontal wells in SAGD settings with an emphasis on the McMurray Formation. We further compared the results with the conventional drilling practice. In contrast to existing tools that have limited depth of penetration, interpreting SWD data in real time confidently maps key target features ahead of the drill bit. This imaging workflow provides sufficient time to precisely control the borehole trajectory and stay within the desired reservoir zone. Accordingly, it mitigates the risk of intersecting mudstone-filled channels and lean zones.

The M2 Tidal Tilt Results from USArray Seismic Data from the Western United States

ABSTRACTWe explore the detectability of M2 tidal tilt in the western part of the United States, using seismic velocity data from 40 stations in the EarthScope Transportable Array (TA) network. We augment these data with data from two additional stations both collocated at the Piñon Flats Observatory (PFO) in southern California (networks TA and Incorporated Research Institutions for Seismology [IRIS] International Deployment of Accelerometers [IDA]). We find a good agreement between the acceleration-tilt derived from the TA seismic data with the theoretical model (body Earth and ocean loading for M2). These results are also consistent with prior studies using borehole tiltmeters operated at PFO (Wyatt and Berger, 1980; Wyatt et al., 1982). We find statistically significant M2 tilt anomaly responses that correlate with large lateral variations in rock properties in Yellowstone National Park, which stem from volcanic sources in the region. We also examined deviations in the M2 tidal tilt mode in regions with other geological features including the Cascades volcanic range and a large plutonic body located in Idaho and eastern Oregon. Of these, only the Cascadia data show evidence of lateral variances of elastic properties, similar to that of the Yellowstone Caldera (YC). We conclude that tilt measurements from seismic noise data can successfully identify relatively large structural changes in elastic properties of the crustal Earth (e.g., the YC) and significant change in the elastic properties (e.g., Cascadia subduction zone). But, when the features are smaller and/or have a more muted variation in the elastic properties (e.g., the plutonic body in Idaho and eastern Oregon), the induced changes in the tilt values are too small to be detected using TA data.

Size Reduction Characterization of Underground Mine Tailings: A Case Study on Sandstones

The production of construction and building materials starts with reducing the size of natural, industrial, and waste materials. In addition to strength and durability considerations of natural resources recommended by various institutions, size reduction characterization, specific to rock aggregates, has a vital role in their size-related quality. In this study, various sandstones extracted from underground mines located in northwestern Turkey were investigated for size reduction characterizations. Several mineralogical, textural, and physico-mechanical properties were determined for each rock type. Crushability tests were carried out using a laboratory-scale cone crusher for different feeding size fractions, namely + 11.20 − 16.00 mm (size I), + 9.52 − 16.00 mm (size II), and + 6.30 − 16.00 mm (size III). Based on the crushability tests, crushed particles were analyzed, focusing on production yield, size, and shape properties. Each crushability test was also explored for energy consumption arising from varying rock properties of the sandstones. The laboratory test results demonstrated that the degree of rock crushability (DRC) and specific energy consumption (Ecs, kJ/kg) were associated with the Brazilian tensile strength (BTS, MPa) and apparent porosity (ne, %) of the sandstones. The results also showed that the degree of sorting in mineral constituents, quantified as the sorting coefficient (Sc), affected the DRC. However, mineralogical features of the sandstones have no significant impact on DRC and Ecs. Variations in feeding gradation, irrespective of whether mineralogical, textural, or physico-mechanical properties, have remarkable effects on product flakiness and yields for specific size fractions. In light of the findings obtained, the present study provides knowledge on how the sandstones behave under cone crushing operations.

Defining lithic patterns within river-dominated delta deposits for geostatistical simulation

Reservoir development forecasts depend on accurate descriptions of the spatial distribution of rock properties that impact subsurface fluid-flow pathways and volume connectivity. Reservoir models constructed using geostatistical methods combine analogous facies dimension data with sparse subsurface data to predict spatial variations in rock properties. This study uses a physics-based depositional process model to define realistic facies variations within a river-dominated delta deposit formed during multiple shoreline regressions and transgressions. Geostatistical models are conditioned to varying amounts of information extracted from the depositional model to examine how well they reproduce the facies patterns. Reservoir simulation is used to examine the impact of analogous dimension data and varying conditioning constraints on reservoir performance predictions of water displacing oil. The dimensions of surface depositional features underestimate the continuity of preserved facies patterns, proportional grids following major flooding surfaces allow significantly better predictions than uniform rectangular grids, and trend constraints are more important when defined facies correlation length is significantly less than well spacing. When geostatistical model parameters are poorly chosen, reservoir simulation of the resulting weakly-structured facies patterns overpredict recovery and water breakthrough time. It is demonstrated that process-based depositional models can be used to optimize geostatistical model construction methods and input parameters to reduce uncertainty of reservoir development assessments.

Physical and micro-structural characteristics of limestone after high temperature exposure

Temperature is a major factor affecting physical and mechanical rock properties. With increasing temperature, a series of variations enlarge the internal defects within rocks, resulting in physical and mechanical rock property variations. To explore the influence of temperature on the physical and micro-structure of limestone, the weighing test and P-wave velocity test were conducted on limestone after exposure to high temperature to reveal the evolution of the limestone mass and P -wave velocity. XRD, XRF, SEM, and mercury intrusion tests were also carried out to examine the mineral composition and content, micro-fracture morphology, porosity, and fractal dimension. The limestone mass and P-wave velocity decrease with increasing temperature. When T ≤ 400 °C, there is no obvious change in chemical composition and crystal structure; when T = 400–500 °C, the diffraction intensity of partial calcite decreases, and dolomite decomposes gradually; when T > 500 °C, illite decomposes gradually, while dolomite decomposes completely; and the diffraction intensity of calcite is significantly reduced. When T ≤ 200 °C, changes in trace minerals or impurities containing K2O and Na2O and the decomposition of illite oxide are dominant; when T = 400–600 °C, illite oxide, trace minerals, or impurities containing K2O and calcium hydroxide begin to decompose. When T = 600–800 °C, magnesite and dolomite begin to decompose. When T ≤ 200 °C, micro-fracture surfaces change slightly. When T = 200–500 °C, micro-fractures begin to develop and propagate gradually, most of which are intergranular cracks with a small number of transgranular cracks. When T > 500 °C, transgranular cracks occur in samples with locally broken crystals, and the cracking of the crystal structure occurs with increasing pore size. With increasing temperature, the limestone pore fractal dimension decreases gradually, and the higher the temperature, the greater the decrease. 400 °C to 500 °C is the temperature threshold interval that causes the pore structure change. These new pores, resulting from the increasing temperature, are primarily mesopores with a pore diameter of 1.0–10.0 μm. This research provides a scientific basis for the design and construction of rock engineering projects to be subjected to high temperatures, deep geological radioactive nuclear waste disposal sites, deep mines, and the exploitation of geothermal resources.

Application of an STFT-Based Seismic Even and Odd Decomposition Method for Thin-Layer Property Estimation

For seismically thin-reservoir layers, variations in rock properties may not be directly linked to seismic amplitude due to the wave interference of layer top and base reflections. In addition, thin-layer reflection signal locally has a different phase from that of the signal wavelet. Signal even and odd components can be considered as amplitudes at different signal phases, which may have a different sensitivity to the variations in thin layer and surrounding layer properties. A novel extension of the spectral decomposition concept is proposed that decomposes seismic signal into its even and odd components via the short-time Fourier transform. Amplitude attributes for the original signal and even and odd part components are compared for their ability to restore the correct “amplitude-layer property” correlation without resolving the thin layer. Numerical modeling analysis shows that amplitude at peak frequency (APF) of the seismic data odd component APF (OAPF) is more sensitive to thin-reservoir property change compared to the conventional APF and even component APF attributes. When applied in analyzing real seismic data in a tight-dolomite reservoir, conventional APF and conventional acoustic impedance inversion did not provide a correct relationship to porosity variations. Meanwhile, the OAPF attribute responds well to porosity measured in boreholes. This suggests that the interpretability of amplitude attributes in thin layers can be improved by signal even and odd decomposition.

Stability of tunnels according to depth and variability of rock mass parameters

Even with the most recent advances in rock mechanics, the stability assessment of underground tunnels continues to involve many uncertainties in the parameters which can significantly affect the calculated factors of safety. In the present work, a straight characterization which can help to evaluate the risk of a tunnel collapse with respect to the depth of excavation is proposed. Following a consolidated Limit Analysis approach and by means of the Hoek-Brown failure criterion, the galleries are divided into shallow, intermediate and deep according to the variability of the mechanical parameters of the rock mass with depth. A solution to the problem of impending collapse in the case of variable rock properties is proposed and examples are presented and discussed both from an analytical and a numerical standpoint.

An integrated deep learning solution for petrophysics, pore pressure, and geomechanics property prediction

In unconventional plays, wells are drilled at an unprecedented rate. This, together with technical challenges in terms of complex stratigraphy, multiple play types, variable rock properties, and various elements of pore pressure, geomechanics, fracturing, and diagenesis, calls for more sophisticated, faster, consistent, and wider ranging analytical tools. Given the scale of the work — i.e., the number of wells — performing classical workflows for petrophysics, pore pressure, and geomechanics prediction can be impractical (if not impossible) due to turnaround considerations. Also such workflows might not use any preexisting regional studies efficiently. In principle, a machine learning approach can mitigate these shortcomings. We show that a supervised deep neural network approach can be an alternative innovative tool for petrophysical, pore pressure, and geomechanics analysis enabling the use of all the previously interpreted data to devise solutions that simultaneously integrate wide-ranging wellbore and wireline logs. Beyond that, a similar approach is taken to predict a certain number of attributes solely from seismically derived properties, which allows one to compute volumetric models. The application of such an algorithm is shown on a Permian case study in which the automatic neural-network-based algorithms achieve reasonable accuracy in a fraction of the time.

Rock properties evaluation for carbonate reservoir characterization with multi-scale digital rock images

Digital rock analysis (DRA) following the digital imaging techniques can be used to image detailed rock microstructures and simulate rock properties, such as porosity and permeability, for reservoir characterization. However, for most carbonate rocks, there are apparent differences in rock texture and minerals and clear variations of rock properties with location. This kind of heterogeneity often leads to a degree of unpredictability in DRA simulation. In addition, smaller sample size is necessary for a higher resolution image but the rock properties derived from bigger physical sample are more representative. Therefore, for a heterogeneous rock sample, it is impractical to predict its rock properties with only single resolution image.In this paper, we evaluate the rock properties using two heterogeneous carbonate rock samples and their corresponding multi-scale digital rock images including thin sections, scanning electron microscope (SEM) and X-ray computed tomography (XCT) images. A DRA upscaling method is also proposed. The analysis and results show that: 1) the simulated porosity and permeability agree well with their lab measurements; 2) the heterogeneity is clearly observed with these 2D and 3D rock images and their corresponding simulations; 3) the rock properties of the two carbonate rock samples are well evaluated by these rock images, lab measurements and numerical simulations.

Technology Update: Optimizing Well Productivity: Horizontal Logs Unlock Critical Geologic Knowledge

Technology Update With drilling on the rise, US oil production is expected to continue to increase. However, many industry professionals are concerned that the “brute force” model, which has seen a massive influx of capital flow into completion and hydraulic fracturing operations, is not an economically sustainable business model. There is a growing belief that better understanding of the effectiveness of completion designs and hydraulic fracturing strategies will require far greater subsurface geological understanding. Moreover, continued well productivity improvements will only be realized through improved reservoir characterization, and by applying formation petro-physical and geomechanical information to optimize methods of drilling, completing, and stimulating wells. There has been considerable media attention focused on how the industry is drilling wells longer and more quickly, as well as applying higher-intensity fractures. Until recently, however, there has been less emphasis on constructing productive wells with less capital. Traditional vertical well tool conveyance methods effectively addressed industry logging requirements for almost a century, but in today’s “horizontal” world, conventional methodologies are either not applicable or expensive and risky. Essentially, the multibillion-dollar logging market has not quite been turned upside down, but has toppled onto its side. Using available industry data, the low-hanging fruit in the growing “big data” boom, geosciences departments have labored to build accurate high-resolution geological models. Given the nonhomogeneous nature of the geology in unconventional reservoirs, applying vertical offset well logs and interpolating field reservoir models is generally accepted as a good start, but hardly the complete solution. To develop an accurate reservoir model, the heterogeneous nature of shale plays requires far greater data resolution than most operators appreciate. If operators are going to efficiently exploit every stage of their wellbore, they need accurate, measured formation insights along every foot of the horizontal wellbore. Geometric completions and fracturing strategies are not practical or effective in these unpredictable heterogenous environments. Along the wellbore, operators are encountering highly variable rock properties that affect fracturing efficiencies, and result in poor or unexpected well production results. This trend is forcing producers to evaluate stage-by-stage production contributions. They are finding that large portions of their wells are not contributing. There is a growing realization that improved well results that are repeatable and predictable are only going to come about by enhancing production at every stage in the wellbore. This requires engineered completions programs and tailored fracturing strategies that account for the considerable rock heterogeneity along the lateral.

A 3-D model for simulation of weak interface slippage for fracture height containment in shale reservoirs

Shale formations often consist of multiple distinct layers with varying rock properties, in-situ stress states, and interface properties between layers. Weak horizontal interfaces often affect fracture height growth and induced complex fracture geometry. In this paper, a fully three-dimensional displacement discontinuity method is developed to investigate slippage of weak horizontal interfaces and understand the effects of the slippage on fracture height growth. Horizontal fracture segments are regarded as weak horizontal interfaces and vertical fractures would either be arrested or step over interfaces. Results indicate that a width jump of the vertical fracture occurs at the crossing position of the horizontal interface, as a result of shear displacement discontinuities along the horizontal fracture segment. The width jump hinders the vertical fracture growth in the height direction, which is regarded as a new mechanism of fracture height containment. Shear displacement discontinuities and width jump increase with the increment of the distance between the center of the vertical fracture and horizontal fracture segment. The larger the width jump, the more difficult the vertical fracture continues to propagate in the height direction, which implies that the vertical fracture tends to be arrested by the interface when the wellbore is far away from the interface.

Facies and stratigraphic architecture of the Upper Devonian–Lower Mississippian Sappington Formation, southwestern Montana: A potential outcrop analog for the Bakken Formation

This study describes the sedimentology and stratigraphy of the Devonian–Mississippian Sappington Formation in exceptional outcrop exposures in southwestern Montana. The goal was to assess the extent to which these outcrops could be used to define stratigraphic heterogeneity of time-equivalent Bakken Formation reservoir and source rocks of the Williston Basin. Facies analysis of the Sappington Formation shows three depositional sequences deposited along a storm- and wave-influenced coastline. The first sequence encompasses the lower Sappington shale, dominated by organic-rich mudstones that represent an anoxic to dysoxic lower-shelf environment. The second sequence is marked by a basal transgressive surface and initial siltstone deposition. These siltstones are abruptly overlain by basinward-dipping, low-angle clinoforms (<1°) that represent a storm- and wave-influenced shoreface. Facies distributions along clinoforms change along depositional dip over approximately 17 km (∼11 mi) from proximal to distal across the study area. The best reservoir facies are present in the upper foresets of these clinoforms. The upper shale of the Sappington Formation forms the lowest part of the third depositional sequence that continues into the overlying Lodgepole Limestone. The outcrop-based stratigraphy of the Sappington Formation provides insights into the scale of stratigraphic heterogeneity that is likely to be present in the time-equivalent Bakken Formation over the length of a typical approximately 3-km-long (∼2-mi-long) horizontal well. Geosteering horizontal wells in the Bakken along bedding surfaces, that is, along gently dipping clinoforms, is likely to cause variations in rock properties from the toe to heel of a horizontal well.

Stability Analysis of a Large Gold Mine Open-Pit Slope Using Advanced Probabilistic Method

A large gold reserve was recently discovered at Haveri district of Karnataka state of India where open-pit mining was planned to extract these deposits. Stability analysis for open-pit mine slope at this site is presented in the article. Extensive geological investigations and laboratory testing suggested high variability in geological features of discontinuities, rock mass quality and intact rock properties. Hence, it was decided to perform stability analysis of the rock slope using probabilistic approach along with deterministic approach. Deterministic analysis was carried out with average properties of rock, and reliability analysis of the rock slope was carried out using both traditional and advanced probabilistic methods. In traditional probabilistic method, rock mass strength properties were treated as random variables without considering spatial variation of rock properties and reliability index was evaluated by Monte Carlo (MC) simulation on augmented radial basis function-based response surface. In advanced probabilistic analysis, spatial variability of rock mass strength properties was considered by generating anisotropic random field using Fourier series method with spatial averaging over finite difference zones. Reliability index was then estimated by performing MC simulation using random finite difference method. A comparison was provided between the results of stability analysis of slope from all these approaches. Rock slope was found to be stable in both deterministic and probabilistic approaches; however, the degree of stability predicted was different for both methods. Deterministic approach was found to be inappropriate to analyse the stability of slope having rock mass with variable properties. Further, reliability index and expected performance level of slope were highly underestimated by traditional probabilistic method as compared to advanced probabilistic method.

Introduction to this special section: The Permian Basin

The Permian Basin of west Texas and New Mexico currently contains many of the most actively pursued unconventional plays in the world. The 75,000-square-mile continental depocenter is split into the Delaware Basin on the west and the Midland Basin to the east and is the largest petroleum-producing area in the United States. According to IHS Markit, the basin produced a record 815 million barrels of oil last year, 97 years after its first discovery. What is even more astounding is that as many as 1 million additional wells may remain to be drilled in the foreseeable future. Though production is on land and relatively shallow, the Permian Basin presents technical challenges in terms of complex stratigraphy, multiple play types, variable rock properties, and multiple periods of faulting, fracturing, and diagenesis.

Permeability Sensitivity Functions and Rapid Simulation of Hydraulic‐Testing Measurements Using Perturbation Theory

AbstractSingle‐well pressure‐diffusion simulators enable improved quantitative understanding of hydraulic‐testing measurements in the presence of arbitrary spatial variations of rock properties. Simulators of this type implement robust numerical algorithms which are often computationally expensive, thereby making the solution of the forward modeling problem onerous and inefficient. We introduce a time‐domain perturbation theory for anisotropic permeable media to efficiently and accurately approximate the transient pressure response of spatially complex aquifers. Although theoretically valid for any spatially dependent rock/fluid property, our single‐phase flow study emphasizes arbitrary spatial variations of permeability and anisotropy, which constitute key objectives of hydraulic‐testing operations. Contrary to time‐honored techniques, the perturbation method invokes pressure‐flow deconvolution to compute the background medium's permeability sensitivity function (PSF) with a single numerical simulation run. Subsequently, the first‐order term of the perturbed solution is obtained by solving an integral equation that weighs the spatial variations of permeability with the spatial‐dependent and time‐dependent PSF. Finally, discrete convolution transforms the constant‐flow approximation to arbitrary multirate conditions. Multidimensional numerical simulation studies for a wide range of single‐well field conditions indicate that perturbed solutions can be computed in less than a few CPU seconds with relative errors in pressure of 5%, corresponding to perturbations in background permeability of up to two orders of magnitude. Our work confirms that the proposed joint perturbation‐convolution (JPC) method is an efficient alternative to analytical and numerical solutions for accurate modeling of pressure‐diffusion phenomena induced by Neumann or Dirichlet boundary conditions.

A probabilistic approach for assessing failure risk of cutting tools in underground excavation

Accurate assessment of failure risk of cutting tools is essential to the optimization of cutter and drum design as well as the operation of mechanical excavators. In reality, factors involved in the risk assessment often have many uncertainties, e.g., the variations in rock properties and cutting tip material properties. In current practice, these uncertainties have not been considered adequately. The conventional deterministic approach based on mean values or extreme values normally generates a binary assessment (safe or unsafe) and can lead to over- or under-estimation of cutting tool failure risks. To address this issue, a probabilistic risk assessment approach is proposed in this paper, with a case study on the application of the proposed approach to the failure probability assessment of cutting tools for underground roadway development with a continuous miner. In this approach, the property variations of cutting tools and rock are modelled using probability theory, the continuous rock cutting process is discretized, and the failure risk of cutting tools is estimated based on reliability theory. The new approach enables designers and operators to estimate how likely a cutting tool would fail in a given operational condition, and then adjust their design and operation decisions accordingly to achieve an optimal balance between cutting productivity and cutting tool failure risk.

Thermo-mechanical Properties of Upper Jurassic (Malm) Carbonate Rock Under Drained Conditions

The present study aims to quantify the thermo-mechanical properties of Neuburger Bankkalk limestone, an outcrop analog of the Upper Jurassic carbonate formation (Germany), and to provide a reference for reservoir rock deformation within future enhanced geothermal systems located in the Southern German Molasse Basin. Experiments deriving the drained bulk compressibility C were performed by cycling confining pressure p c between 2 and 50 MPa at a constant pore pressure p p of 0.5 MPa after heating the samples to defined temperatures between 30 and 90 °C. Creep strain was then measured after each loading and unloading stage, and permeability k was obtained after each creep strain measurement. The drained bulk compressibility increased with increasing temperature and decreased with increasing differential pressure p d = p c − p p showing hysteresis between the loading and unloading stages above 30 °C. The apparent values of the indirectly calculated Biot coefficient α ind containing contributions from inelastic deformation displayed the same temperature and pressure dependencies. The permeability k increased immediately after heating and the creep rates were also temperature dependent. It is inferred that the alteration of the void space caused by temperature changes leads to the variation of rock properties measured under isothermal conditions while the load cycles applied under isothermal conditions yield additional changes in pore space microstructure. The experimental results were applied to a geothermal fluid production scenario to constrain drawdown and time-dependent effects on the reservoir, overall, to provide a reference for the hydromechanical behavior of geothermal systems in carbonate, and more specifically, in Upper Jurassic lithologies.

Reservoir history matching using constrained ensemble Kalman filtering

The high heterogeneity of petroleum reservoirs, represented by their spatially varying rock properties (porosity and permeability), greatly dictates the quantity of recoverable oil. In this work, the estimation of the spatial permeability distribution, which is crucial for predicting the future performance of a reservoir, is carried out through a history matching technique based on constrained ensemble Kalman filtering (EnKF). The main contribution in this work is the novel implementation of hard and soft constraints in the recursive EnKF estimation methodology for petroleum reservoirs. Hard data is obtained from the actual values of the reservoir parameters at discrete locations obtained by core sampling and well logging, while the soft data considered is obtained from correlograms, which characterize the spatial correlation of the rock properties in a reservoir. In each time update, the parameter estimates obtained from the unconstrained EnKF are modified by one of two novel algorithms. In the first, the correlation matrix obtained after the unconstrained EnKF update is transformed to honour the true correlation structure from the correlogram by applying a projection‐based method. The second algorithm involves the use of a technique for soft constrained covariance localization. We observe that the soft data constrained localization method results in the best estimates of the permeability and also reduces the computational time significantly. We quantify the improvement in estimation performance of each of the constrained methods over unconstrained estimation. The method, while developed for estimation in petroleum reservoirs, is also generally applicable to systems with spatial heterogeneity and underlying spatial correlations.

From geology to production: a completion optimization case study from Cleveland Sand, Oklahoma

Oil companies seldom acquire the necessary data to help them understand subsurface heterogeneity when they design multi- stage completions for lateral wells. In particular, well logs are rarely run in the lateral section. In the absence of such subsurface information, operators generally adhere to ‘geometric’ completion designs or equally spaced stages in the lateral section. While this approach seems reasonable and follows industry norms, it may not be very effective for heterogeneous rock (Far et al., 2015; Ashton et al., 2013; Ganguly and Cipolla, 2012). The geometric completion design may result in a limited stimulated reservoir volume (SRV) and lower well production than could be achieved with an optimized design based on subsurface information. Geoscientists, completion engineers and reservoir engineers focus on different aspects of the complex problem of fracture spacing in a horizontal well. In the comprehensive study presented in this article, the authors have developed an integrated reservoir model combining reservoir characterization, petrophysical, geophysical, drilling and completion data. A fully coupled reservoir/geomechanical simulation model was built to capture the variation in rock properties in the lateral section, and to assess the impact of this variation on the simulation of injection and production processes. This single model was used to simulate both the injection and production times for the well.