Shale gas is becoming increasingly important globally. The nature of these reservoirs pose special considerations in reserves estimation. What follows was written in 2001 and needs to be updated based on current experience. Nonetheless, some of the considerations mentioned remain appropriate. As reported in mid-2000, natural gas produced from shale in the US has grown to be approximately 1.6% (0.3 Tcf annually) of total gas production.
Case studies can be instructive in the evaluation of other coalbed methane (CBM) development opportunities. The San Juan basin, located in New Mexico and Colorado in the southwestern U.S. (Figure 1), is the most prolific CBM basin in the world. It produces more than 2.5 Bscf/D from coals of the Cretaceous Fruitland formation, which is estimated to contain 43 to 49 Tscf of CBM in place. For a long time, the Fruitland formation coals were recognized only as a source of gas for adjacent sandstones. In the 1970s, after years of encountering gas kicks in these coals, operators recognized that the coal seams themselves were capable of commercial gas rates. CBM development benefited greatly from drilling and log data compiled from previous wells targeting the deeper sandstones and an extensive pipeline infrastructure that was built to transport conventional gas. These components, along with a U.S. federal tax credit and the development of new technologies such as openhole-cavity completions, fueled a drilling boom that resulted in more than 3,000 producing CBM wells by the end of 1992. The thickest Fruitland coals occur in a northwest/southeast trending belt located in the northeastern third of the basin. Total coal thickness in this belt locally exceeds 100 ft and individual coal seams can be more than 30 ft thick. The coals originated in peat swamps located landward (southwest) of northwest/southeast trending shoreline sandstones of the underlying Pictured Cliffs formation. The location of the thickest coals (Figure 1) coincides with the occurrence of overpressuring, high gas content, high coal rank, and high permeabilities in the San Juan fairway ("fairway"). The overpressuring is artesian in origin and is caused by water recharge of the coals through outcrops along the northern margin of the basin. This generates high vertical pressure gradients, ranging from 0.44 to 0.63 psi/ft, which allow a large amount of gas to be sorbed to the coal. Coal gas in the San Juan basin can contain up to 9.4% CO2 and 13.5% C2 . Chemical analyses suggest that thermogenic gases have been augmented by migrated thermogenic and secondary biogenic gas sources, resulting in gas contents ranging up to 700 ft 3 /ton. Coal rank in the fairway ranges from medium- to low-volatile bituminous and roughly coincides with those portions of the basin that were most deeply buried. Coals in the fairway typically have low ash and high vitrinite contents, resulting in large gas storage capacities and excellent permeabilities of 10 md from well-developed cleat systems.
A useful first step in the characterization of any new coal area is to compare its characteristics with those of successful CBM projects. Table 2 summarizes the characteristics of several successful projects in the US and includes parameters related to reservoir properties, gas production, gas resources, and economics. The table shows that successful projects have many similarities, including high permeabilities and high gas resource concentration; however, the table does not include aspects such as government incentives or high-value markets, which could elevate a marginal project to commercial status.
The process of drilling and completing coalbed methane (CBM) wells is similar to wells in conventional reservoirs. Coring, however, can pose special challenges. The first step in creating a drilling program for a CBM well involves gathering information about existing wells in a given area. After these data are gathered and analyzed, a preliminary drilling and completion prognosis can be drafted with the input of field operations personnel. An important aspect in drilling frontier or appraisal wells is to keep the drilling procedures relatively simple.
Polymers are used to viscosify the fluid. Crosslinkers are used to change the viscous fluid to a pseudoplastic fluid. Biocides are used to kill bacteria in the mix water. Buffers are used to control the pH of the fracture fluid. Surfactants are used to lower the surface tension. Fluid-loss additives are used to minimize fluid leakoff into the formation. Stabilizers are used to keep the fluid viscous at high temperature. Breakers are used to break the polymers and crosslink sites at low temperature.
Almost simultaneously, advances were made in understanding both the processes within the source rock organic matter that accompany the generation and expulsion of hydrocarbons and in the acquisition, processing, and quantitative interpretation of 3D seismic data. In particular, as organic matter in shales in unconventional plays generates and expels hydrocarbons, porosity is formed in the organic matter and the organic matter becomes more dense and more brittle. As these changes are occurring at a micro-scale, extraction of hundreds of different attributes from a well-imaged 3D seismic volume has made it possible to observe changes at a macro-scale in seismic lines and horizons within that volume. Seismic attributes derived from pre-stack inversions yielding rock mechanical properties from shear (Vs) and compressional (Vp) velocities and density, when calibrated with well log and/or core measurements, can be combined to calculate TOC, pore pressure, rigidity, and compressibility because these properties cause fundamental changes in how seismic waves travel through the rock.
Equally important, the escalation in computing power via methods such as machine learning, neural networks, and multivariate statistics has made it possible to interpret large amounts of data. All of these innovations have contributed to better identification of sweet spots within unconventional plays. Such sweet spots include areas with elevated TOC values, enhanced porosity, and zones that can be targeted for fracking.
One of the primary advantages of seismic data is that it provides information in those areas in between control points/wells. This information in turn helps operators to better select targets for wells and for landing zones. Carefully tied 3D seismic inversion and integration with petrophysical and rock data further allow for detailed characterization of unconventional reservoirs. The enhanced ability to identify the best potential drilling targets has significant economic implications in terms of risk reduction and improved chances to find economic prospects.
While 3D seismic data is being used routinely by numerous companies to predict the mechanical properties, density, and associated TOC of many formations, there is yet to be a direct link made between TOC loss, kerogen conversion, and the associated changes in rock properties. This work documents the importance of TOC loss during maturation and its effects on rock properties like porosity, density, brittleness, and how those advances coupled with the advances in quantitative interpretation of 3D seismic data are enabling the unconventional operators to predict location, thickness, landing zone, and sweet spots with appropriately acquired, processed, and interpreted 3D seismic. Meticulously calibrated 3D seismic inversion and integration with petrophysical and rock data permit detailed reservoir characterization of unconventional reservoirs.
Updated methods for the back calculation of original TOC have been developed using well logs, rock measurements, and 3D basin modeling to assist in locating and developing unconventional reservoirs. In addition, petrophysical measurements that reflect TOC and porosity and are related to fundamental properties controlling the seismic response can be extracted from the seismic reflection data. In turn, seismic attributes derived from pre-stack inversions yielding rock mechanical properties from shear (Vs) and compressional (Vp) velocities and density, when calibrated with well log and/or core measurements, can be combined to estimate TOC, pore pressure, rigidity, and compressibility because these properties cause basic modifications in how seismic waves travel through the rock.
This study shows advancements in studies of: 1) TOC loss with increased thermal maturation, 2) how this loss affects the development of organic porosity, 3) how kerogen becomes denser, harder, and more brittle with increasing maturity, and 4) how recent developments in quantitative interpretation workflows for 3D seismic data facilitate estimation of TOC and determination of rock mechanical properties from shear (Vs) and compressional (Vp) velocities and density. Further integration of geochemical, geomechanical, and geophysical technologies and measurements will provide improved estimates of present-day TOC that can in turn be extended to relative maturity and percent conversion.
Examples provided in this work illustrate prediction of present-day TOC, porosity, density, and mechanical properties extracted from high fidelity pre-stack inversion. Pre-stack inversion along with machine learning can be used to predict rock properties such as porosity, TOC, organic matter quality, rigidity, and pressure and to correlate those properties back to well productivity for improved execution. Relating present TOC estimated from seismic to TOC loss and kerogen property changes with increasing maturity is possible by combining the results of these technologies.
Though analysis and inversion of painstakingly acquired modern 3D seismic data is capable of estimating porosity, TOC, matrix strength, and pore pressure, the latest work on rock property changes as hydrocarbons mature and are expelled isn't typically addressed in most studies. Increasing communication between disciplines might improve estimation of these properties and extend the capability to assess the extent of TOC loss during maturation and the porosity increases that accompany it. This ability is especially important in the intra-well regions where the potential of 3D seismic to extend data between control points enables better reserve estimates and high grading of acreage. After carefully calibrating a quantitative 3D seismic interpretation with a 3D basin modeling analysis of the source rock potential and maturity, an operator is better prepared to high grade acreage and attain the most economic development of unconventional resources.
The escalation in computing power means there are hundreds of different attributes that can be extracted or calculated from a well-imaged 3D seismic volume. Using quantitative calibration of fundamental geochemical measurements such as TOC, pyrolysis, and petrographic measurements of vitrinite reflectance that yield the quantity, quality, and maturity of organic matter in combination with well log and seismic data creates a model for identifying sweet spots and the areas in the target formation that exhibit high TOC, high porosity, and elevated brittleness. Further integration and calibration of changes occurring at the micro-level in organic matter in unconventional plays with their impact on the signatures of data at the macro-level can provide information on the types of hydrocarbons most likely to be found in these sweet spots as well as identifying which zone(s) in the target formation are most likely to be amenable to fracking. Used together, the advances outlined here result in a technological evolution that could have a substantial impact on: 1) the approach to and 2) the economics of the exploration and production of unconventional plays.
One of the major challenges associated with the exploitation of unconventional hydrocarbon resources is determining the optimal stimulation design. In this sense, it is necessary to understand how the parameters and variables involved in the completion process impact on production performance; the purpose is to act on such controllable variables and, consequently, maximize production and field development efficiency. Whereas physical driven tools frequently used in the oil industry are very helpful, they always imply a set of assumptions and simplifications regarding the system or phenomenon they try to model; they also require a large amount of unavailable or expensive data to calibrate them. Generally, different combinations of model parameters could explain well production behavior and for each of these solutions the way to optimize completion and development may be different.
Because of these drawbacks, and the big number of unconventional wells available, data-driven workflows have gained popularity in the last years. These models represent an excellent complement to physical driven tools in the attempt to optimize the completion and development strategy in shale plays. Several publications used both parametrical and non-parametrical models in the search of the Holy Grail: a statistical model capable of predicting how stimulation design affects productivity. The aim of this paper is to develop a novel methodology to understand the relation between formation parameters, completion design variables and production performance. An artificial neural network model (ANN) was chosen for this study.
Public production and stimulation data was merged with geological and petrophysical properties maps for almost 13.000 horizontal wells landed in Eagle Ford formation. A back propagation ANN algorithm was trained with this data-set and a cross-validation criterion was used for hyper-parameters optimization. Once the optimal model was selected, a bootstrap algorithm was run to assess for uncertainty in model prediction; these models were trained to determine which part of the input space presented enough data to get a clear signal and in which part the amount of data was not enough to differentiate signal from noise.
ANN models proved to be a fine method for this purpose obtaining R-Squared values between 0.5 and 0.7 for cross-validation sets. Significant relations were observed between production performance and lateral length, true vertical depth, porosity and fracture fluid intensity.
The methodology presented in this paper introduces a novel feature in comparison to previous publications regarding model uncertainty assessment. The coupling of the ANN model with the bootstrap re-sampling technique allowed to better understand which conclusions were statistically significant and which not, a fact that proved to be vital to correctly interpret results. It was demonstrated that such methodology is a good complement to physical-driven models in the aim to comprehend the relation between formation parameters, completion design variables and production performance.
A new approach that uses logs derived from wireline and surface drilling data to extract an interface proxy is presented and illustrated in the Montney. The derived interface proxy logs are propagated in the entire reservoir volume using artificial intelligence-based reservoir modeling. Blind wells confirm the ability to predict the interface proxy at any reservoir location. The derived interface proxy propagated in 3D was validated with moment tensor showing that the microseismic shear plane events occur mainly where the presence of the interfaces is the highest.
Using the derived interface proxy as an input, the Material Point Method (MPM) and Anisotropic Damage Mechanics (ADaM) are used to solve the geomechanical modeling of a hydraulic fracture propagating in a layered medium containing any type of interfaces including the weak interfaces. The geomechanical simulation confirms the major impact these weak interfaces could have on the fracture height growth.
The geomechanical analysis confirmed the importance of mapping in 3D the interfaces and modeling their effects in an accurate manner to better capture their effect on fracture height growth and the resulting proppant placement. The application of the new geomechanical workflow was illustrated on two Montney wells and was able to provide some explanation on their production differences that could be attributed to interfaces.
There is an ongoing paradigm shift in the processes and technologies employed in making field development decisions in unconventional reservoirs. Expensive trial and error exercises in multiple reservoirs have returned the verdict: there is no single prescribed treatment for a given reservoir, which always maximizes production and eliminates risk of frac hits and well interferences. In many situations, lateral growth of hydraulic fractures has been the major concern amongst operators, but as the economics of unconventional production shift, and the industry moves to more wine-racking and cube development plans, it has become abundantly clear that current hydraulic fracturing design software have multiple shortcomings such as not being able to fully account for natural fractures and predicting the subsequent frac-complexity as well as including the critical effects of weak interfaces. One of the consequences of this poor representation of the physics occurring during hydraulic fracturing of unconventional wells is the overprediction of hydraulic fracture heights. All commonly used industry frac design software are neither able to predict microseismicity to prove their ability to reproduce the observed frac complexity nor capable of including the effects of weak interfaces, or bedding and laminations (geologically speaking) on hydraulic fracture propagations in the vertical direction. Since microseismicity has been successfully predicted to capture the lateral stress gradients created by the natural fractures, the focus in this study is quantifying at any well the characteristics of the interfaces and their impact on the fracture height. Geomechanical logs derived from commonly available surface drilling data are used to capture zones of high interface potential and their characteristics. The resulting interface positions and their mechanical properties are input in a geomechanical simulator using the Material Point Method (MPM) to simulate the effect of the weak interfaces on hydraulic fracture height growth. These simulations provide the necessary information required by frac design software that now can incorporate not only the lateral stress gradients created by the natural fractures but also the vertical complex effects created by the weak interfaces. The results of this fast-practical decoupled workflow are a better estimate of the spacing needed for wine-rack systems and more realistic fracture geometries inputs to fluid flow models which can provide realistic geometries of depletion profiles affecting well interference potentials driven by production.