The Nuclear Magnetic Resonance (NMR) response of gas in gas shale nanopores is different from that of bulk gas, where relaxation is dominated by spin rotation and diffusion is unrestricted. Gas shales are characterized by very low porosity and ultra low permeabilities. Their porosity is dominated by nanometer-scale pores in the organic kerogen that restricts diffusional motion, in addition to having very high surface-to-volume ratios that enhance surface relaxation. At high pressure, the gas exists as an adsorbed phase on the pore surface and as free gas phase in the pore interior. Thus, relaxation and diffusion properties of gas in gas shales are controlled by the combined effects of adsorption, enhanced surface relaxation, restricted diffusion and molecular exchange between the adsorbed and free phases. One of the biggest challenges is the understanding of such effects in order to determine the quantity of free and adsorbed gas from NMR data, and to devise novel techniques to log these unconventional plays. Proper estimation of fluid volumes also requires the knowledge of the hydrogen index for the gas restricted in the gas shale nanopores, which is yet another challenge. The NMR responses of methane gas in Haynesville shale plugs cored from a well in East Texas, USA were studied in laboratory experiments using a 2 MHz NMR spectrometer at elevated pressures up to 5 kpsi. The effects of adsorption, surface relaxation and restricted diffusion have been characterized, and the hydrogen index of the gas has been measured. Mineralogy, elemental analysis and Brunauer-Emmett-Teller (BET) experiments have also been carried out on the same plugs to understand the formation characteristics. In the samples studied, faster relaxation modes (few tens of milliseconds) and slower apparent diffusion coefficients (an order of magnitude less than their bulk values) for the confined gas molecules in comparison to their bulk properties have been observed for the first time with the help of 2D-NMR experiments at high pressure. It has been observed that the relaxation spectra for bound water and the gas in the small pores overlap. Additional information is required to resolve these two fluids. Subsequently, the diffusion dimension is investigated to resolve the various fluids in the nanopores. We formulate new relaxation and diffusion models for the interpretation of the dynamics of gas restricted in gas shale and propose that multi-dimensional NMR logging with pulse sequences optimized for gas shales be further tested in the field, to help quantify the total gas in place.

In conventional reservoirs, 2D-NMR fluids evaluation targets the free fluid part of the total porosity with the assumption that the bound fluid is irreducible water. As such, pulse sequences are designed for long relaxing fluids, and the interpretation commonly assumes free diffusion of hydrocarbon molecules in water-wet pores. This is clearly not appropriate for unconventional reservoirs such as shale gas and shale oil where the fast-relaxing fluids of interest reside in the bound fluid region. We show a revised 2D-NMR model that focus on fast relaxing fluids. In unconventionals, the three causes of fast relaxation are: small pore size, heavy oils and wettability alteration. The fast relaxation has the following consequences with respect to diffusion. In small pores, fluids cannot diffuse freely, and hence, the free diffusion lines of water, gas and oil must be corrected accordingly. In heavy oils, the oil relaxation can be enhanced by a wettability change to an oil/mixed-wet system. Another case of hydrocarbon-wet systems is hydrophobic kerogen. Consequently, the oil diffusion line as a function of viscosity (T2) must also be modified before the 2D map interpretation. This can be accomplished within the framework of the restricted diffusion model previously applied to water and gas that captures both the effects of surface relaxation and geometric restriction to molecular motion. The results of the revised 2D-NMR model are shown through modeling and log examples in a shale gas reservoir and a shale oil reservoir. In real rocks, there is also a need to take into account simultaneously two models: an unconventional model as described above and a conventional model for long relaxing fluids associated with the matrix of the rock. The 2D-NMR log results are compared with lab results. Essentially, we show that adding diffusion and T1 information to standard T2 relaxation logs improves both the understanding and evaluation of unconventional reservoirs.

Shale plays have been considered statistical plays by many people in our industry. During the early years of the shale boom and even today, technical teams have looked to find correlations between variables to help explain well performance. Simple one-to-one correlations between individual variables and production performance in the Haynesville Shale appear to be weak because complex relationships may exist. Regression analysis techniques have assumptions and limitations, moreover, such techniques encounter difficulties when analyzing complex relationships. In this study, ordination, a multivariate analysis technique, was applied to subsurface and completion data to identify the variables that seem to influence well performance. The debate of nature versus nurture has often been applied to shale gas developments where some believe an effective well completion can make up for a poor shale reservoir rock quality while others believe a high quality shale reservoir rock is essential to obtain better producers despite an average well completion. The ordination technique successfully separated better performing wells from the less prolific wells and identified the variables that characterize the better producers. The same technique provided various optimum ranges for the different variables that could be used to identify core and non-core areas within the play. Our results suggest that (1) ordination is a viable method for multivariate statistical analysis in the Haynesville Shale; (2) subsurface variables are critical in obtaining better performing wells; and (3) completions variables are secondary but also very important.

No abstract

Recent developments in software are beginning to deliver the use of a single "toolkit" to store, visualize and synthesize geological, geophysical and engineering data - allowing, for the first time, the creation of "true" multidisciplinary Shared Earth Models (SEM). There have been several hurdles to creating these models in the past: First, scale difference - pore scale for a petrophysicist, well scale for the driller, reservoir scale for the RE, and prospect or regional scale for the geoscientist have hindered tighter integration. Second, the wider E&P communities have viewed integration only in terms of their own team foci - partly due to the difficulty of amalgamating domain specific data - the geophysicist's preferred domain being time, a driller's being depth, and a reservoir engineer's being temporal and spatial data. Third, we have limited integration to a subset of the E&P community with, for example, economic models not being an integral component of SEM. As a result, mistakes have commonly been made at interfaces between disciplines as one group hands off its output to another. Using a 3D modeling software platform, a SEM of the Columbus Basin in offshore Trinidad was constructed. Scalability is a key component of the SEM - with support for individual prospects or regional scale. The relational framework facilitates an environment that can rapidly make computations across scales, allowing, for example, a casing design to be generated taking a reservoir scale model and translating it to the well scale.With the advent of 4D data handling, basin evolution, migration of fluids, pressure and other time variant properties are integrated into the SEM. This flexibility allows fluid migration studies to be better linked with prospecting. Creating a unified and scalable model promoted wider ownership and engagement - going beyond the geoscience and reservoir disciplines to engage the drilling, facility, economic and strategy communities. The SEM environment facilitated better cross-functional inferences to be made - with economic models being directly linked to the earth description and associated uncertainties. INTRODUCTION It takes time to collect, prepare, understand and make decisions based on data, one of our biggest assets. Today, not only is this workflow too often inefficient, high-risk business decisions are being made without full recourse to all the available data and, more importantly, without the full knowledge derived from all the data [1]. One of our key challenges is to ensure that each component in the E&P decision process is integrated and can add synergistic value. We should ensure that all data can be enhanced and used by all members of the E&P value chain, whether they are geologists, drillers, production engineers, geophysicists, or economist and business managers. By reducing the time and effort needed to build, maintain and continuously update these models, the "knowledge base" can be fully integrated and better utilized Historically, use of shared earth models has been a means to ensure consistency between views of the reservoir held by people in different subsurface disciplines. The essential principle is that all the disciplines should participate in the definition and construction of a common numerical description of the reservoir, and should use this numerical model as the basis for their respective calculations and interpretations. The SEM is generally implemented as a fine-scaled cellular model held by a suitable geological modeling package containing rock properties, geophysical attributes, and reservoir characteristics, and with a close linkage, through upscaling, to a reservoir simulator [2]. However, expanding the SEM's utility to a wider community, going beyond the traditional G&G disciplines, can provide synergistic benefits. By providing a more encompassing shared view, with scale and domain considerations important to each discipline captured, a wider ownership and engagement can be achieved - going beyond the geoscience and reservoir communities to engage the drilling, facility, economic and strategy communities. Constructing a SEM with the aforementioned issues in mind requires novel considerations of scale and diversity of data. It requires developing the whole picture, whether on a well, a field, a play, or a province. It should allow for not only considerations important on a project scale, but also facilitate strategic level views.