Today everyone seems to agree that ultra-low permeability and shale reservoirs have become the potentials to transform North America's oil and gas industry to a new phase. Unfortunately, transient flow is of long duration (perhaps life of the well) in ultra-low permeability reservoirs, and traditional decline curve analysis (DCA) models can lead to significantly over-optimistic production forecasts without additional safeguards. Stretched Exponential decline model (SEDM) gives considerably more stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale. For an individual well, the SEDM model parameters, can be determined by the method of least squares in various ways, but the inherent nonlinear character of the least squares problem cannot be bypassed. To assure a unique solution to the parameter estimation problem, this work suggests a physics-based regularization approach, based on critical velocity concept. Applied to selected Barnett Shale gas wells, the suggested method leads to reliable and consistent EURs. To further understand the interaction of the different fracture properties on reservoir response and production decline curve behavior, a series of Discrete Fracture Network (DFN) simulations were performed. Results show that at least a 3-layer model is required to reproduce the decline behavior as captured in the published SEDM parameters for Barnett Shale. Further, DFN modeling implies a large number of parameters like fracture density and fracture length are in such a way that their effect can be compensated by the other one. The results of DFN modeling of several Barnett Shale horizontal wells, with numerous fracture stages, showed a very good agreement with the estimated SEDM model for the same wells. Estimation of P90 reserves that meet SEC criteria is required by law for all companies that raise capital in the United States. Estimation of P50 and P10 reserves that meet SPE/WPC/AAPG/SPEE Petroleum Resources Management System (PRMS) criteria is important for internal resource inventories for most companies. In this work a systematic methodology was developed to quantify the range of uncertainty in production forecast using SEDM. This methodology can be used as a probabilistic tool to quantify P90, P50, and P10 reserves and hence might provide one possible way to satisfy the various legal and technical-society-suggested criteria.

Geostatistics and more specifically stochastic modeling of reservoir heterogeneities are being increasingly considered by reservoir analysts and engineers for their potential in generating more accurate reservoir models together with usable measures of spatial uncertainty. Geostatistics provides a probabilistic framework and a toolbox for data analysis with early integration of information. The uncertainty about the spatial distribution of critical reservoir parameters is modeled and transferred all the way to a risk conscious reservoir management. The stochastic imaging (modeling) algorithms allow the generation of multiple, equiprobable, unsmoothed reservoir models yet all honoring the data available. This thesis presents stochastic reserve estimation methods as related to the various stages of development of an oil field. Advances in technology are leading to better deterministic estimates as well as stochastic estimates with narrower ranges. Practices in the industry vary from complete dedication to deterministic or stochastic to a choice of the method depending on the stage of the development. In this study, reserves are calculated from the data available in Southeastern Turkey by using stochastic methods. Probability density functions, number of iterations are important statistical concepts. Increasing number of iterations leads to a normal distribution of histogram.

ABSTRACT UNCERTAINTY ASSESSMENT IN RESERVE ESTIMATION OF A NATURALLY FRACTURED RESERVOIR ERI&Ccedil / OK, &Ouml / zlen M.S., Department of Petroleum and Natural Gas Engineering Supervisor : Prof. Dr. Fevzi G&Uuml / MRAH December 2004, 169 pages Reservoir performance prediction and reserve estimation depend on various petrophysical parameters which have uncertainties due to available technology. For a proper and economical field development, these parameters must be determined by taking into consideration their uncertainty level and probable data ranges. For implementing uncertainty assessment on estimation of original oil in place (OOIP) of a field, a naturally fractured carbonate field, Field-A, is chosen to work with. Since field information is obtained by drilling and testing wells throughout the field, uncertainty in true ranges of reservoir parameters evolve due to impossibility of drilling every location on an area. This study is based on defining the probability distribution of uncertain variables in reserve estimation and evaluating probable reserve amount by using Monte Carlo simulation method. Probabilistic reserve estimation gives the whole range of probable v original oil in place amount of a field. The results are given by their likelyhood of occurance as P10, P50 and P90 reserves in summary. In the study, Field-A reserves at Southeast of Turkey are estimated by probabilistic methods for three producing zones / Karabogaz Formation, Kbb-C Member of Karababa formation and Derdere Formation. Probability density function of petrophysical parameters are evaluated as inputs in volumetric reserve estimation method and probable reserves are calculated by @Risk software program that is used for implementing Monte Carlo method. Outcomes of the simulation showed that Field-A has P50 reserves as 11.2 MMstb in matrix and 2.0 MMstb in fracture of Karabogaz Formation, 15.7 MMstb in matrix and 3.7 MMstb in fracture of Kbb-C Member and 10.6 MMstb in matrix and 1.6 MMstb in fracture of Derdere Formation. Sensitivity analysis of the inputs showed that matrix porosity, net thickness and fracture porosity are significant in Karabogaz Formation and Kbb-C Member reserve estimation while water saturation and fracture porosity are most significant in estimation of Derdere Formation reserves.

This study investigates the use of discretion by oil and gas companies in reporting financial performance and oil and gas reserve estimates during times of high political scrutiny resulting from increases in energy prices. Hypotheses tested in prior literature state that companies facing the risk of increasing taxes or new regulations reduce reported earnings to reduce this risk. This study uses a measure of high profitability (rank order of return on assets relative to industry peers) to identify oil and gas companies more likely to manage earnings during the period from 2002 to 2008. Two measures of discretionary accruals (total and current discretionary accruals), and a measure of discretionary depreciation, depletion, and amortization (DDA) were used as indicators of discretion exercised in reporting earnings. Data on oil and gas reserve disclosures was also hand-collected from Forms 10-K to investigate whether managers use reserve estimate revisions to reduce reported earnings through increasing the annual depletion expense. Results suggest that both oil and gas refining and producing firms use negative discretionary accruals to reduce reported earnings. Results also indicate that profitability is an important determinant of the use of negative discretionary accruals by these companies regardless of the time period examined. There is also evidence that oil and gas producing firms opportunistically revise their oil and gas reserve estimates to increase depreciation, depletion, and amortization expense during periods of high oil prices.