Pore Pressure Prediction in the Point Pleasant Formation in the Appalachian Basin, in Parts of Ohio, Pennsylvania, and West Virginia, United States of America

Pore Pressure Prediction in the Point Pleasant Formation in the Appalachian Basin, in parts of Ohio, Pennsylvania, and West Virginia, United States of America

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

By Bennett Trotter Graduate program of Earth Sciences

The Ohio State University 2018

Thesis Committee: Dr. Derek Sawyer (Advisor)

Dr. Ann Cook (Advisor) Dr. Thomas Darrah

Copyrighted by Bennett Trotter 2018

Abstract

The Ordovician-aged Point Pleasant Formation is an economically important unconventional oil and gas play in the Appalachian Basin, in particular Ohio, western

Pennsylvanian and West Virginia. The Point Pleasant Formation is known to have overpressured pore fluids, that is, pore pressure above hydrostatic conditions. Overpressure is an important rock property to constrain because it exerts a strong control on the mechanical stability of boreholes, the response of the formation to hydraulic fracture stimulation, and volumetric flow rates of produced fluids. However, what is not well known is the spatial distribution, magnitude, and controls on the overpressure within the Point Pleasant Formation. In this study, pore pressure in the Point Pleasant Formation is estimated based on sonic velocity geophysical logs measured in 33 wells as well as mudweight data from 23 wells. From this analysis, a map of overpressure in the Point Pleasant identifies a large area of overpressure centered in southeastern Ohio primarily within the counties of Noble, Monroe, and Washington . This overpressure map may facilitate target selection, safer drilling, and more successful well completions. Areas of significant overpressure have also been linked to enhanced risks of induced seismic events, thus the overpressure map may also indicate areas that have higher probability to trigger induced seismic events during hydraulic fracturing or waste water disposal.

Acknowledgements

I would like to thank professors Derek Sawyer, Ann Cook, and Tom Darrah for advising me throughout my graduate degree process and assisting me with my research. I thank

Professor Dave Cole and the Ohio State Subsurface Energy Resource Center (SERC). I would like to thank ODNR and the Utica Shale Consortium for providing me with data to conduct my research. Finally I would like thank the Ohio State University Basin Research Group and my wife, Hanna Trotter, for supporting me during my research.

Vita

2014………………………………………………………………..B.S. Geological Sciences California State

University of Long Beach

2014…………………………………………………………………Mudlogger, Horizon Well Logging

2015-2016…………………………………...... Field Geologist, August Mack

Environmental

2016-Present………………………………...... Graduate Research Associate, School of

Earth Sciences, The Ohio State University

Fields of Study

Major Field: Earth Sciences

iii

Table of Contents

Abstract ...... i Acknowledgements ...... ii Vita ...... iii Table of Contents ...... iv List of Tables ...... v List of Figures ...... vi 1. Introduction ...... 1 1.1. Overpressure ...... 2 1.2. Geophysical Log Response to Overpressure ...... 5 1.3. Pore Pressure Prediction...... 5 1.4 Geologic Setting ...... 6 2. Materials and Methods ...... 8 2.1. Data Preparation ...... 8 2.2. Derivation of Sonic Porosity Equation Constants ...... 14 2.3. Derivation of Normal Compaction Porosity Equation Constants ...... 16 2.4. Calculation of Pore Pressure and Displaying Results ...... 19 3. Results...... 21 4. Discussion ...... 27 4.1 Pore pressure trends in the Point Pleasant Formation ...... 27 4.2 Potential Causes of Overpressure ...... 30 4.3 Limitations ...... 31 5. Conclusion ...... 32 References ...... 33 Appendix A ...... 36

List of Tables

Table 1 (Wells with Geophysical Logs Inventory Table) ………………………………………………….……11 Table 2 (Wells with Mud Weight Data Inventory Table) ………………………………………………………12 Table 3 (Formation Factor Calculation Table) ……………………………………………………………………...15 Table 4 (Matrix Travel Time and Formation Factor Standards) ……………………………………….……16

List of Figures

Figure 1 (Map of study area)……………………………………………………………………………………………2 Figure 2 (Pore Pressure Diagram) ……………………………………………………………………………………4 Figure 3 (Map of Depositional Lithofacies) ……………………………………………………………………..7 Figure 4 (Example Well Log Displaying Top and Bottom of Point Pleasant) ………………….…13 Figure 5 (Map of XRD Data Locations) ……………………………………………………………………………15 Figure 6 (Map of Unloading Zones) …………………………………………………………………………..……18 Figure 7 (Unloaded Normal Compaction Porosity Calculation Graph) …………..………………..19 Figure 8 (Map of Interpolated Sonic Velocity) ………………………………………………………………..21 Figure 9 (Map of Interpolated Bulk Density) ………………………………………………………………....22 Figure 10 (Map of Interpolated Modeled Overpressure) …………………………………………….….24 Figure 11 (Map of Interpolated Mud Weight Data) …………………………………………………………25 Figure 12 (Map of Interpolated Combined Data Set) ……………………………………………………….26 Figure 13 (Map of Interpolated Combined Data Set for Southeastern Ohio) …………….……..28 Figure 14 (Map of Induced Seismicity) …………………………………………………………………………….29

1. Introduction

The Point Pleasant Formation is an unconventional oil and gas play in the Appalachian

Basin that is estimated to contain large quantities of oil and natural gas (Patchen and Carter,

2015). Production in the Point Pleasant began to take off in 2013 and there are currently over

30 rigs drilling Point Pleasant wells in 2018 (United States Energy Information Administration).

This study focuses on the central Appalachian Basin where the Point Pleasant play extends from western Pennsylvania to northeastern Kentucky (Figure 1). In some areas the Point Pleasant

Formation is overpressured (Chatellier et al., 2013; Bertoncello and Briguad, 2016). The processes responsible for generating this overpressure and how it is able to be maintained is poorly understood. The highest initial production rates from the Point Pleasant have been observed in wells that have targeted these overpressured areas, suggesting that there is a relationship between overpressure and production. This study seeks to locate and quantify areas of overpressure within the Point Pleasant Formation.

Figure 1. A map of the Eastern United States, with the study area outlined in blue. Well # 30

(black star) is a type well for the Point Pleasant and well will be referenced later in the thesis.

1.1. Overpressure Overpressure in sedimentary basins is common in subsurface rocks (Tingay et al., 2009;

Hermanrud et al., 1998; Zhou, Nikoosokhan, and Engelder, 2017). Overpressure is pressure above hydrostatic pressure (Figure 2). The hydrostatic pressure gradient is the pressure that would be exerted by a continuous column of static fluid, and will vary slightly depending upon the density of the fluid (Osborne and Swarbrick, 1997). Overpressure can be generated by a number of different processes: 1) an increase in compressive stress 2) a change in fluid volume caused by

2 fluid generation or aquathermal expansion, or 3) by fluid movement into, or within, the reservoir driven by differences in densities (Osborne and Swarbrick, 1997). Determining which of these processes is responsible for the overpressure can be difficult considering many of these processes have similar representations in geophysical data and multiple processes can be occurring simultaneously within the a reservoir. If the process generating overpressure can be determined it will allow for the best pore pressure prediction method to be chosen (Bowers, 2001). A method for distinguishing between disequilibrium compaction and a change in fluid volume, has been used in the North Sea (Hermanrud et al., 1998) and in Brunei Darussalam (Tingay et al., 2009).

This method involves comparing density and sonic log response within a zone of overpressure.

Figure 2. Conceptual pressure plot illustrating a zone of overpressure in a sandstone reservoir that is surrounded by shale formations. The lithostatic gradient is the entire weight above the overburden and increases with depth, based on the thickness and density of the overlying rock.

Hydrostatic pressure is the static pressure of pore fluids. The red line is pore fluid pressure.

Overpressure is pore pressure above hydrostatic. Effective stress is the lithostatic minus the pore pressure.

1.2. Geophysical Log Response to Overpressure Bulk density and sonic velocity are commonly used to estimate overpressure (Tingay et al., 2009), (Hermanrud et al., 1998), (Zhou, Nikoosokhan, and Engelder, 2017). Bulk density is a measure of the weight of the rock and its pore fluids per unit of volume (Asquith and Gibson,

1982). The sonic tool measures the speed of a P-wave traveling through the rock and its pore fluids (Asquith and Gibson, 1982). As sediments are buried, the vertical effective stress ( 𝜎푒푓푓 ) as defined by (Terzaghi, 1996),

𝜎푒푓푓 = 𝜎푣 − 푃푃 (1)

where 𝜎푣 is overburden stress and PP is the pore pressure, on the rock increases. All symbols are defined in the Nomenclature Table (Page 37). Increasing vertical effective stress results in consolidation, the process by which sediment decreases in volume (Lambe and Whitman,

1969). This also dictates that bulk density and compressional velocity will increase with depth.

This is true for normally consolidated conditions with hydrostatic pore pressure. However, pore fluids may become overpressured, which will reduce the effective stress on the rock. In turn, this will be manifested by a reduction in both bulk density and compressional velocity (Tingay et al., 2009), which ultimately are detectable by bulk density and sonic logs.

1.3. Pore Pressure Prediction Developing an accurate pore pressure prediction model is important for drilling and well completion to identify where the zones of overpressure are and to quantify what the pressures are within those zones (Fertl et. al., 1976). As pore pressure increases, effective stress decreases (Equation 1) (Terzaghi, 1996). The lower the effective stress, the weaker the rock will be, making it more susceptible to deformation (Terzaghi, 1996). During drilling, the mud weight

5 will need to be adjusted to counteract changes in pore pressure and to prevent blowouts or unwanted fracturing of the rock (Gholami et al., 2014). It is also important in target selection and well completion to insure the highest relative pore pressure zones are being targeted and fractured properly to generate the highest possible production rates (Fertl et. al., 1976).

1.4 Geologic Setting The Point Pleasant Formation is middle to late Ordovician in age (470-450 My) and was deposited in a sub-basin within the Appalachian foreland basin, created during the Taconic

Orogeny (Patchen et. al, 2015). The Point Pleasant Formation consists of interbedded limestones and shales, and is overlain by the Utica Shale and underlain by the Trenton

Limestone in northern Ohio and the Lexington Limestone in southern Ohio (Patchen et. al,

2015). The Point Pleasant sub-basin was centered in Ohio and surrounded by two large carbonate platforms to the north and south (Figure 3). The carbonate platform to the north of the sub-basin was the Trenton Platform, it extended from what is now Indiana to New York

(Patchen et. al, 2006). The carbonate platform to the south of the sub-basin was the Lexington

Platform, centered in what is now eastern Kentucky, southwestern West Virginia, and western

Virginia (Patchen et. al, 2006) (Figure 3). The Tippecanoe Transgression is interpreted as a eustatic sea level rise, which began in the early Ordovician and continued into the Silurian

(Sloss, 1963). The Taconic Orogeny was still ongoing, increasing the load on the North American continent causing the Point Pleasant sub-basin to deepen (Rodgers, 1971). During the Late

Ordovician, the Point Pleasant deposition began within the sub-basin (Patchen et. al, 2006). As sea level continued to rise and the basin continued to deepen, the depositional rate of the

Trenton and Lexington carbonate platforms could not keep pace with the rate of sea level rise

6 and widespread deposition of the Utica shale occurred on top of the Point Pleasant Formation and the Trenton and Lexington carbonate platforms (Patchen et. al, 2006). There were two more orogenies, the Acadian, which occurred in the Devonian, and the Alleghanian, which occurred during the Permian; both orogenies continued to create accommodation space allowing for deposition of more sediments, which deeply buried the Point Pleasant (Faill, 1997).

The Point Pleasant has since experienced relative uplift as the overlying mountain belt has been eroding away since the end of the Permian (Faill, 1998).

Figure 3. Lithofacies map for the Appalachian Basin during the middle to late Ordovician. The

Utica/Point Pleasant sub-basin centered in central Ohio, illustrates the extent of deposition of the Point Pleasant in the central Appalachian Basin (modified after Patchen et. al, 2006). The study area is within the Utica/Point Pleasant sub-basin.

2. Materials and Methods

This study predicts pore pressure in the Point Pleasant Formation on a regional basin scale, utilizing geophysical well logs and mud weight data, and the Eaton pore pressure method

(Eaton, 1975). Geophysical well log data and mud weight data were first compiled and reviewed for quality, and then the top and bottom of Point Pleasant were picked in each well log. Eaton’s estimated for the sonic porosity equation and the normal compaction porosity equation. Then an unloading equation was applied to the normal compaction porosity to account for the unroofing that has occurred in the Appalachian basin. The pore pressure was then predicted in each well for the Point Pleasant utilizing Eaton’s pore pressure prediction equation. The results of the pore pressure prediction calculations were then used to interpolate a pore pressure map for the Point Pleasant across the central Appalachian basin.

2.1. Data Preparation Data from wells that drilled through the Point Pleasant Formation were compiled from publicly available state databases in 2017. These databases included the ODNR database in

Ohio (http://geosurvey.ohiodnr.gov/open-file-materials-pgs/oil-and-gas/digital-geophysical- logs), the WVGS database in West Virginia

(http://www.wvgs.wvnet.edu/utica/playbook/pb_data.aspx), and the EDWIN database in

Pennsylvania

(http://docs.dcnr.pa.gov/topogeo/econresource/oilandgas/EDWIN_home/index.htm). All well data were compiled and reviewed to ensure it was useable for this study. In total, 33 wells with geophysical data measured at 0.5 ft intervals and 23 wells with mud weight data were used in

8 this study (Table 1). For the data to be usable, each well log had to have a high quality gamma ray log, bulk density log, and sonic log through the Point Pleasant. The Point Pleasant Formation was identified at each well by a gradual decrease in gamma ray and relatively low bulk density between the Utica Shale and Trenton Limestone. The gradual decrease in gamma ray is due to the Point Pleasant being a transitional formation between the overlying shale and the underlying limestone. Compared to the overlying Utica Formation, the Point Pleasant

Formation has a high total organic carbon content that is likely related to the low bulk density

(Patchen and Carter, 2015). This relatively low bulk density and gradual decrease in gamma ray were used to pick the top and bottom of the Point Pleasant at each well. A representative example of the gamma ray and bulk density trends is illustrated in Well #30 (Figure 4).

After the Point Pleasant was identified, the bulk density log (𝜌푏푢푙푘) was used to calculate overburden stress (𝜎푣) using (Equation 3) for the first bulk density value (depth = z). Then,

Equation 4 was solved for all bulk density values following to the bottom of the well.

푧 × 휌 × 9.81 𝜎 = 푏푢푙푘 (2) 푣 1000

(푧 −푧 )×푝 ×9.81 𝜎 = 훴 1 2 푏푢푙푘 (3) 푣 1000

When calculating overburden stress, if the bulk density log did not start at ground surface level the first accurate bulk density reading was used to calculate overburden stress back up to ground level. Then once the overburden stress was calculated for each well all the well’s median overburden stress for the Point Pleasant was plotted against the well’s median depth of

9 the Point Pleasant and a linear regression was performed on that plot to derive the following general equation to calculate the overburden stress for entire basin (Equation 5)

𝜎푣 = 0.008 × 푧 − 0.1276, (4) this was done to reduce error caused by poor quality bulk density data.

Table 1. A list of all of wells that were used in this study, with their assigned well identification number for this study in the first column. Their respective World Geodetic System (WGS) 1984referenced latitude and longitude are in columns 2 and 3, referenced from the World Geodetic System (WGS) 1984 geographic coordinate system. *Indicates wells that also have mud weight data.

Table 2. A list of wells that only have mud weight data during drilling of the Point Pleasant.

Figure 4. Well logs from Well # 30 with the Point Pleasant highlighted in yellow. This is an example of the characteristically low bulk density and gradual decrease in gamma ray used to pick the top and bottom of the formation. The location of this well is illustrated in Figure 1 as a black star.

2.2. Derivation of Sonic Porosity Equation Constants To utilize Eaton’s pore pressure prediction equation first the rock’s porosity must be calculated, so it can be compared to the normal compaction porosity. In this study this was done by converting the delta t log to sonic porosity. The sonic porosity ( 휙푠 ) equation

(Equation 6) relies on the acoustic formation factor ( 푓) and matrix travel time ( 훥푡푚푎) to convert the delta t log (훥푡 ), which is in µs/ft (Raiga-Clemenceau et al., 1988) (Equation 6)

훥푡 휙 = 1 − ( 푚푎)1/푓 (5) 푠 훥푡

Acoustic formation factor (f) is a constant specific to a formation that describes how fast sound waves move through that formation (Raiga-Clemenceau et al., 1988). Matrix travel time ( 훥푡푚푎) is the speed at which a sound wave travels through 100% rock matrix of a specific formation. To estimate acoustic formation factor and matrix travel time, the average percentages of calcite, dolomite, and silica were calculated for the 7 wells that had X-ray Diffraction (XRD) data (Figure

5). The percentage of calcite, quartz, and dolomite were taken from XRD data and normalized to 100% in each well. Based on the average of these values the Point Pleasant is estimated to contain 8% dolomite, 52% calcite, and 40% silica (Table 3). These percentages were then used to take the weighted average of the formation factors and matrix travel times modeled from

Raiga-Clemenceau et al., (1988) as shown in Table 4, to estimate of the formation factor and matrix travel time. The formation factor estimated for the Point Pleasant was 1.72 and the matrix travel time estimated for the Point Pleasant was 51 µs/ft (19,607 ft/s).

Figure 5. A map illustrating the location of wells with XRD data (black squares)

Table 3, Average formation factor and matrix travel time for the Point Pleasant calculated from

XRD data.

Table 4, Matrix Travel Time and Formation Factor for Quartz, Calcite, and Dolomite (Raiga-

Clemenceau et. al, 1988).

2.3. Derivation of Normal Compaction Porosity Equation Constants

The normal compaction porosity (휙푛) developed by Athy, (1930) (Equation 7) relies on the initial porosity (휙표) and the rock compressibility (훽)

(−훽푧) 휙푛 = 휙표푒 (6)

Initial porosity (휙표) is the porosity of the rock at zero effective stress. Compressibility describes the amount of volumetric loss for a given load and varies based on lithology. To estimate these constants, a normal compaction trend was first developed using an initial porosity for the

Appalachian Basin of 70% taken from Engelder (2014) and a shale compressibility of 0.85 taken from (Rowan, 2006). The study area was then broken up into four zones by degrees of unloading (Figure 6), based upon the amount of unloading modeled by Rowan (2006). The study area was broken up into four zones as follows: Zone 1 includes the Point Pleasant at a present-day depth of less than 3,100ft, with an assumed 1,500ft of unroofing. Zone 2 includes the Point Pleasant at a present-day depth 3,100-6,100ft with an assumed 2,500ft of unroofing.

Zone 3 includes the Point Pleasant at a present day depth of 6,100-12,000ft with an assumed

5,000ft if unroofing. Zone 4 includes the Point Pleasant at a present-day depth of greater than

12,000ft with an assumed 8,000ft of unroofing. An unloading curve was created for each of the four zones by modifying the equation developed by Athy (1930) to (Equation 8)

(−휀푧푟) 휙푢 = 휙푛푒 (7)

unloaded initial porosity (휙푛) is determined from the normal compaction curve, the overburden removed (푧푟) for each zone was estimated based on Rowan’s model, and the elastic constant

(휀) was determined by back solving from areas where mud weights are known. If the pore pressure is known from mud weight data, then the unloaded normal compaction porosity (휙푢) that would yield that pore pressure can be solved for. Once the unloaded normal compaction porosity is determined, the best values for initial unloaded porosity and unloaded shale compressibility to obtain that normal compaction porosity can be estimated. After these values have been estimated, an exponential regression can be performed on the unloaded porosity data and the elastic constant can be varied until the unloaded initial porosity is equal to the one estimated from the unloaded normal compaction trend (Figure 7).

Figure 6. Illustration of the study area broken up into the four zones of unloading.

Figure 7. Normal compaction porosity (휙푛) (blue line) with applied unloading curve (red line) for each unloading zone delineated by the dashed lines. An exponential trend line (orange dotted line) was fitted to the resulting unloaded normal compaction porosity (휙푢) (orange line), where the Y-intercept of the exponential trend line is represents the unloaded initial porosity used in the unloaded normal compaction (Equation 8).

2.4. Calculation of Pore Pressure and Displaying Results Finally, pore pressure for the Point Pleasant was calculated using Eaton’s (1975) pore pressure prediction (Equation 9):

1−휙푠 푓 푃푃 = (𝜎푣 − 푃ℎ푦푑푟표) × ( ) . (8) 1−휙푢

Eaton’s method relies on the deviation of the present-day porosity (휙푠) away from the unloaded normal compaction curve (휙푢) and assumes the difference between the two porosities is due to overpressure (Eaton, 1975). Note, this study incorporated the effects of unloading on the in situ porosity while Eaton’s original method does not. The calculated pore

19 pressure (units of MPa) was converted to mud weight (MW in ppg) using (Zhang, 2011)

(Equation 10)

푀푊 = 푃푃/0.052/푧, (9) pore pressure gradient (PPG ppg/ft) ) using (Zhang, 2011) (Equation 11)

푀푊 푃푃퐺 = (10) 19.52 and overpressure ratio (OPR) using (Equation 12)

푃푃−푃ℎ푦푑푟표 =  (11) 푃푙𝑖푡ℎ표−푃ℎ푦푑푟표

Overpressure ratio is the ratio of the overpressure to the hydrostatic vertical effective stress such that a value of 1 indicates pore pressure equals lithostatic and a value of 0 indicated hydrostatic pore pressure.

The calculated pore pressure data were imported into ArcGIS. Interpolation surfaces were created for the median sonic velocity, the median bulk density, the median predicted pore pressure based on geophysical well log data, and pore pressure based on mud weight data.

Then the pore pressure predicted from geophysical well log data and pore pressure based on mud weight data were combined into one data set, and an interpolation surface was then created from this combined data set.

3. Results

We first discuss the spatial distribution of sonic velocity (Figure 8) and bulk density

(Figure 9). The lowest sonic velocity is observed in southeastern Ohio and sonic velocity gradually increases to the north and northeast and rapidly increases in all other directions.

Figure 8. Interpolated sonic velocity surface created from the median sonic velocity from geophysical data of the Point Pleasant Formation at each well location (black triangles).

The lowest bulk density is observed in western Pennsylvania and the bulk density gradually increases to the west and rapidly increases to south (Figure 9).

Figure 9. Interpolated bulk density surface created from the median bulk density from geophysical data of the Point Pleasant Formation at each well location (black triangles).

The wells with lowest bulk densities and sonic velocities in the Point Pleasant occur in southeastern Ohio and western Pennsylvania, which suggests the porosity is highest in the

Point Pleasant Formation in this area.

The modeled overpressure of Point Pleasant is illustrated in Figure 10. The highest pore pressure for the Point Pleasant occurs in southeastern Ohio with a maximum of 48.5 MPa and an overpressure ratio of 0.72. The pore pressure decreases moving away from this area.

Moderate overpressure occurs in eastern Ohio, Western Pennsylvania, and Northern West

Virginia. Pore pressure is modeled to be hydrostatic in the western part of the study area. This is consistent with the fact that the Point Pleasant is much shallower below the surface and has thus not reached sufficient pressure and temperature conditions to become thermally mature, and furthermore, there has been erosion and unroofing of the overburden stress.

Figure 10. Interpolated pore pressure surface created from the median pore pressure modeled from geophysical data for the Point Pleasant Formation at each well (black triangles).

By way of comparison, the spatial distribution of mud weight data information from 23 wells

(Table 1) used to create an independent interpolation surface and is illustrated in Figure 11. The highest mud weight was observed in southeastern Ohio, and mud weights generally decrease radiating away from that location. This is a similar trend as to what was observed in the modeled pore pressure results.

Figure 11. Interpolated pore pressure surface created from the median mud weight used while drilling the Point Pleasant Formation at 23 wells (white circles).

Mud weight used during drilling gives an estimate of the upper limit of pore pressure because the mud is weighted to counteract the pore pressure in the formation. As a result, the modeled pore pressure is very similar to the mud weight data. This made it acceptable to combine them into a single dataset, to increase the density of pore pressure data points for interpolation. The interpolation surface created from this combined data set is illustrated in (Figure 12). The

25 highest pore pressure for the Point Pleasant was still observed in southeastern Ohio, with pore pressure decreases radiating away from this area. The pore pressure decreases at a relatively higher rate moving to the west and a slower rate to the north and east.

Figure 12. Interpolated pore pressure surface created from the median mud weight used while drilling (white circles) and the median pore pressure modeled from geophysical data for the

Point Pleasant Formation at each well (black triangles).

4. Discussion

4.1 Pore pressure trends in the Point Pleasant Formation This study analyzes spatial distribution of pore pressure in the Point Pleasant Formation using a standard pore pressure prediction approach and also independently with available mud weight data. A key observation from our analysis is that overpressure of the Point Pleasant

Formation is relatively high (* ~0.7) in SE Ohio in Noble, Monroe, and Washington counties

(Figure 13). Elsewhere, pore pressure decreases away from this high pore pressure zone and ultimately declines to hydrostatic pressure in western Ohio (Figure 13). These pore pressure trends are generally consistent with the structural configuration of the Point Pleasant in that overpressure increases as the Point Pleasant deepens into the basin. However, it is not this simple because the highest overpressure would be expected in western Pennsylvania and West

Virginia, where the Point Pleasant is the deepest, at over 4,000 meters (13,123ft). However based upon the modeled results the highest degree of overpressure is observed in southeastern Ohio, which is in a relatively deep part of the basin, but certainly not the deepest at only 3,500 meters (11,282ft). There are other areas in northern Ohio that are buried to comparable depths as the Point Pleasant in southeastern Ohio, but these areas are not as overpressured, which suggests there is some additional, local mechanism in southeastern Ohio that is contributing to the higher degrees of overpressure. The map created based on the mud weight data from drilling of the Point Pleasant also shows the same trend, with highest degree of overpressure in southeastern Ohio, so the model does appear to be accurately predicting the general trends of overpressure conditions in the Point Pleasant. In addition, it has been suggested that there is a higher probability of induced seismic events caused by hydraulic

27 fracturing in formations that are overpressured (Bachman et al., 2012). A map of the distribution of these hydraulic fracturing induced seismic events in the Utica and Point Pleasant from (Skoumal, Brudzinski, and Currie, 2015) correlates well to where the model is predicting the greatest overpressure (Figure 14).

Figure 13. Interpolated pore pressure surface for southeastern Ohio created from the median mud weight used while drilling (white circles) and the median pore pressure modeled from geophysical data for the Point Pleasant Formation at each well (black triangles).

Figure 14. A map of seismic events in Ohio from late 2010 to 2015. Open circles are interpreted as natural seismic events, blue triangles are interpreted as seismic events induced by waste water injection, and red squares are interpreted seismic events induced by hydraulic fracturing of the Utica and Point Pleasant. The smaller cyan triangles are waste water disposal wells and the smaller pink squares are Utica and Point Pleasant wells that were active during this study

(Modified from Skoumal, Brudzinski, and Currie, 2015).

4.2 Potential Causes of Overpressure Based upon the results of this study there is significant overpressure in the Point

Pleasant, but the cause of this overpressure remains uncertain. If the overpressure is being generated by fluid retention during compaction it may be expected to have some degree of overpressure in the western part of the study area where hydrostatic pressures are being observed. It would also be expected that the highest overpressures would be observed in the deepest part of the basin where the highest degree of compaction has occurred, but based on the results this is not the case. Rather, the distribution of overpressure may be better explained by generation of hydrocarbon fluids from catagenesis and water from clay dewatering within the Point Pleasant. Based upon vitrinite reflectance (Ro) data compiled by the Ohio Department of Natural Resources (ODNR), western Ohio is thermally immature with Ro values of less than

6.0, while the eastern border of Ohio is in the dry gas window with Ro values ranging from 1.5 to 2.0. This is consistent with hydrostatic pore pressure observed in the western part of the study area (Figure 12). This would also be consistent with the eastern part of the study area is experiencing lower than expected overpressures because it is thermally over-mature, and may have lost some of its pore fluids overtime. The eastern part of the study area is also the closest to the deformation front, so it was the buried the deepest and has experienced the most unroofing, and thus is likely to be the most faulted and fractured. In addition to the faults and fractures generated by loading and unloading, excessive pore pressure in this area may have exceeded the fracture gradient when the Point Pleasant was at its maximum burial depth and hydraulically fractured the formation. In theory, these faults and fractures may have allowed pore fluids to migrate out of the formation more easily. The eastern part of the study may have

30 at one time been the most overpressured part of the Point Pleasant, but over time it has lost some volume of its pore fluids reducing its pore pressure.

4.3 Limitations The analyses used here estimates pore pressure in the Point Pleasant at a regional, basin scale. This model is based on geophysical well log data and mud weight data. Some assumptions inherent in our analysis are a constant lithology of the Point Pleasant using average mineralogical data and we also assume large differences in unloading across the basin.

The level of confidence of the model is highest in areas that are in close proximity to well locations where geophysical well log or mud weight data are known.

The general trend of the mud weight and model are the same, both of which show the highest overpressure in southeastern Ohio that decreases radially away from that area.

Compared to the mud weight data, the model over predicts pore pressure in the eastern part of the study area by 10 to 20 percent and under predicts pore pressure in the western part of the study area by 20 to 30 percent. These differences in the mud weight data and the model are partially due to the sparsity of data points in both data sets.

5. Conclusion

Pore pressure is predicted within the late Ordovician Point Pleasant Formation in Ohio and parts of Pennsylvania and West Virginia based on geophysical log and mud weight data from 33 wells. The model estimates that overpressure is highest in southeastern Ohio, with a maximum overpressure ratio of 0.72. Overpressure decreases radially away from this region to hydrostatic conditions in western Ohio, and it decreases more rapidly to the west and south compared to the east and north. Mud weight data from 23 wells is consistent with the modeled pore pressure. The model results and mudweight data are combined to produce a map of overpressure for the Point Pleasant Formation. More data on how the Point Pleasant changes laterally across the basin would be needed to refine conclusions on why the overpressure is so high in southwestern Ohio. However, based on the available data, this work suggests that fluid generation from catagenesis and clay dewatering is the most likely cause of the overpressure.

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Appendix A

1. Equation 1 Effective Stress:

𝜎푒푓푓 = 𝜎푣 − 푃푃 2. Equation 2 First RHOB value to Overburden Stress: 푧 × 휌 × 9.81 𝜎 = 푏푢푙푘 푣 1000 3. Equation 3 RHOB to Overburden Stress: (푧 −푧 )×푝 ×9.81 𝜎 = 훴 1 2 푏푢푙푘 푣 1000 4. Equation 4 General Equation for Overburden Stress:

𝜎푣 = 0.008 × 푧 − 0.1276 5. Equation 5 Sonic porosity: 훥푡 휙 = 1 − ( 푚푎)1/푓 푠 훥푡 6. Equation 6 Normal Compaction: (−훽푧) 휙푛 = 휙표푒

7. Equation 7 Unloading curve: (−휀푧푟) 휙푢 = 휙푛푒

8. Equation 8 Eaton’s Pore Pressure Prediction: 1−휙푠 푓 푃푃 = (𝜎푣 − 푃ℎ푦푑푟표) × ( ) 1−∅푛 9. Equation 9 Mud Weight: 푀푊 = 푃푃/0.052/푧 10. Equation 10 Pore Pressure Gradient: 푀푊 푃푃퐺 = 19.52 11. Equation 12 Overpressure Ratio:

푃푃−푃ℎ푦푑푟표 = 푃푙𝑖푡ℎ표−푃ℎ푦푑푟표

Nomenclature

Symbol Variable Name Units

𝜌푏푢푙푘 Bulk Density Grams/cubic centimeter (g/cc) z Depth Meters (m) 𝜎푒푓푓 Effective Stress Mega Pascals (MPa) 휀 Elastic Constant 1/Meters (m-1) f Formation Factor - 휙0 Initial porosity Percent (%) MW Mud Weight Pounds/ Gallon (ppg) 훥푡푚푎 Matrix Travel Time Microseconds/feet (µs/ft) 휙푛 Normal Compaction Porosity Percent (%) 푧푟 Overburden Removed Meters (m) 𝜎푣 Overburden stress Mega Pascals (MPa)  Over Pressure Ratio - V P-wave Velocity Feet/Second (ft/s) PP Pore Pressure Mega Pascals (MPa) PPG Pore Pressure Gradient Mega Pascals/meters (MPa/m) 훽 Shale Compressibility 1/Meters (m-1) 휙푠 Sonic Porosity Percent (%) ∆푡 Travel Time Microseconds/feet (µs/ft) 휙푢 Unloaded Normal Compaction Porosity Percent (%)